JP2006106885A - Multi-dimensional database management device, multi-dimensional database management method, and multi-dimensional database management program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To conduct a data analysis without restructing the data structure of a multi-dimensional database even if data belonging to the same hierarchy and/or different hierarchies in the same dimension are simultaneously selected. <P>SOLUTION: A multi-dimensional database management device 1 processes a multi-dimensional database constituted of multi-dimensional data obtained by converting hierarchical data into multi-dimensional data. The multi-dimensional database management device 1 is provided with; an external storage part 12 which stores an MDB 12b; an input/output control part 11 which receives the input of selection information for specifying a plurality of data belonging to the same hierarchy or different hierarchies, as the analysis-object data to be analyzed, from data belonging at least to a dimension among multi-dimensions; and an analysis object data extraction part 15b which extracts, from the MDB 12b, a plurality of analysis data specified by selection information after the selection information is received. The input/output part 11 outputs the plurality of analysis data thus extracted in a prescribed format. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a multidimensional database management apparatus, a multidimensional database management method, and a multidimensional database management program for performing various processes on a multidimensional database.

  Traditionally, a multidimensional database (MDB) constructed by associating various data in a multidimensional manner, and a multidimensional database management device (MDBMS) for performing various database operations using this multidimensional database : Multi Dimensional Database Management System). The data structure in such a conventional multidimensional database is configured by combining data extracted from a relational database (RDB) in a multidimensional manner. For example, a multidimensional database having a three-dimensional configuration is It is called “Cube”. Each dimension in this multi-dimensional database is expressed as one “axis”. For example, a three-dimensional multi-dimensional database is composed of three “axes”. Each axis is associated with a plurality of data, and the plurality of data of each axis is hierarchized in a plurality of hierarchies from an upper hierarchy to a lower hierarchy as necessary.

  Various analysis methods such as online analysis (OLAP: On-Line Analytical Processing) and data mining can be applied to the multidimensional database constructed in this way by using a multidimensional database management device. As a result, data analysis from various angles can be performed, and the results can be displayed in a table, a graph, or the like. For example, one or a plurality of data belonging to any one hierarchy is selected by a predetermined method from a plurality of data associated with each axis of the multidimensional database. Then, data (variables) matching the selected combination of data in each axis is extracted, and the extracted data is displayed on a monitor or the like in a table or graph of a predetermined format (for example, Patent Document 1 and Patent Reference 2).

  As an example, consider a three-dimensional database having three axes of “date”, “region”, and “product” and having “sales amount” data as a variable. In this case, for example, “2000”, “2001”,. . . , “2004”, which is composed of data such as “2004”, “January”, “February”,. . . , “December” and other data belonging to the middle class “Month”, “1st”, “2nd”,. . . , Which is composed of data such as “31 days”, is associated with data belonging to a lower hierarchy “day”.

  The regional axis is, for example, “Hokkaido district”, “Tohoku district”, “Kanto district”. . . , “Kyushu / Okinawa area” data, which belongs to the upper hierarchy of “district”, “Ibaraki prefecture”, “Tokyo”,. . . , Data that belongs to the middle hierarchy called “prefecture” composed of data such as “Kanagawa prefecture”, “Chiyoda Ward”, “Minato Ward”,. . . , “Hachioji City”, which is composed of data such as “Hachioji City”, is associated with data belonging to a lower hierarchy “city”.

  The product axis includes, for example, “product category A”, “product category B”,. . . , “Product category Z”, which is composed of data such as “product category Z”, “product category”, “product A-1”, “product A-2”,. . . , And data belonging to the middle hierarchy “product category”, which is composed of data such as “product A-10”.

  In such an example, “2000” from the data belonging to the upper hierarchy of the date axis, “Tokyo” from the data belonging to the middle hierarchy of the regional axis, and the data belonging to the lower hierarchy of the product axis. Select “Product A-2”. Then, in “2000”, the “sales amount” of the product “product A-2” sold in “Tokyo” is displayed.

JP 2002-304403 A JP 2004-70791 A

  However, such a conventional multi-dimensional database management apparatus can only perform static data analysis in accordance with the structure of the multi-dimensional database. That is, for each dimension, it is only possible to select and display one piece of data belonging to one hierarchy, and it is possible to analyze by summing up multiple values belonging to the same hierarchy in the same dimension at the same time. Multiple values belonging to the hierarchy could not be combined and analyzed at the same time. For this reason, data analysis depends on the structure of the multidimensional database, and analysis from a point of view beyond this structure cannot be performed. For example, in the above example of the three-dimensional database, the data selection from the regional axis can select only one of the upper hierarchy data, the middle hierarchy data, and the lower hierarchy data. For example, “Tokyo” and “Kanagawa” were selected from the middle hierarchy and displayed in parallel, but these data could not be added together and displayed, so the user It was necessary to visually check the target display and add up by yourself. Also, select “Tokyo” from the middle level and select “Kawasaki City” from the lower level to display the sum of the sales amount of products sold in “Tokyo + Kawasaki City”. I could not.

  Such a problem is caused by the fact that the data structure assumed at the time of designing the multidimensional database is different from the data structure that is actually desired for analysis. In other words, at the time of designing a multidimensional database, it was determined that it would be sufficient to stratify regions by district, prefecture, and municipality. If there is a need to perform data analysis in a category that does not match the standardization, conventional multi-dimensional database management devices have a low degree of freedom in data selection as described above, and can satisfy analysis needs. There was no case.

  In order to solve such a problem, when multiple data belonging to the same hierarchy or different hierarchies in the same dimension are selected by the user at the same time, the structure of the multi-dimensional database is changed according to the new selection request. It is also possible to reconstruct a multidimensional database. However, such reconstruction of the database is not practical because it takes time and cost.

  Further, when the user simultaneously selects a plurality of data belonging to the same hierarchy or different hierarchies in the same dimension, the number of selection items increases and the selection combination becomes complicated. For this reason, it is conceivable that the operation of the database becomes complicated, an item to be selected is not selected by mistake, or an item that should not be selected is selected by mistake.

  The present invention has been made in view of the above problem, and even when a plurality of data belonging to the same hierarchy or different hierarchies in the same dimension are selected at the same time, the data analysis is performed without rebuilding the data structure of the multidimensional database. It is another object of the present invention to provide a multidimensional database management device, a multidimensional database management method, and a multidimensional database program that can perform data selection and can perform data selection easily and reliably.

  In order to solve the above-described problems and achieve the object, a multidimensional database management device according to claim 1 is a multidimensional database that performs processing on a multidimensional database configured by multileveling hierarchical data. A multi-dimensional database management device for storing the multi-dimensional database; and a plurality of data belonging to the same hierarchy and / or different hierarchies from the data belonging to at least one dimension of the multi-dimensions The selection information input means for receiving the selection information for specifying the analysis target data to be analyzed, and after the selection information is received by the selection information input means, the received selection information The plurality of analysis target data specified in the above are stored in the multidimensional database stored in the multidimensional database storage means. And analyzed data extracting means for al extracting, the plurality of analyzed data extracted by the analysis target data extracting means, characterized in that it comprises a data output means for outputting a predetermined format.

  The multi-dimensional database management method according to claim 11 is a multi-dimensional database management method for performing processing on a multi-dimensional database configured by multi-dimensionalizing hierarchical data. A selection information input step for accepting input of selection information for identifying a plurality of data belonging to the same hierarchy and / or different hierarchies as analysis target data to be analyzed from among the data belonging to at least one of the dimensions; After the selection information is received in the selection information input step, the plurality of analysis target data specified by the received selection information are selected from the multidimensional database stored in a predetermined storage unit. The analysis target data extraction step to extract, and the plurality of analyzes extracted in the analysis target data extraction step Elephants data, characterized in that it comprises a data output step of outputting a predetermined format.

  The multidimensional database management program according to claim 19 is a multidimensional database management program for causing a computer to execute a method for performing processing on a multidimensional database configured by multidimensionalizing hierarchical data. The selection information for specifying a plurality of data belonging to the same hierarchy and / or different hierarchies as analysis target data to be analyzed from among the data belonging to at least one dimension of the multi-dimensions A selection information input step for receiving an input; and after the selection information is received in the selection information input step, the plurality of pieces of analysis target data specified by the received selection information are stored in a predetermined storage unit. An analysis target data extraction step for extracting from the multidimensional database; and the analysis target data Said plurality of analyzed data extracted in data extraction step, characterized in that it comprises a data output step of outputting a predetermined format.

  According to the present invention, input of selection information for specifying a plurality of data belonging to different hierarchies from among data belonging to one dimension as analysis target data to be analyzed is received and specified by this selection information. By extracting multiple data to be analyzed, the degree of freedom in selecting data from a multidimensional database can be increased, the diversity of data analysis can be increased, and the added value of multidimensional database management can be increased. There is an effect.

  Further, according to the present invention, since reference information is presented to the user, an error in data selection that may occur to the user due to an increase in the degree of freedom of data selection can be eliminated, and simple and quick data selection is possible. There is an effect that can be.

  Further, according to the present invention, the reference information stored in the reference information storage means is updated based on the reference information, so that the latest reference information can be automatically presented to the user.

  Further, according to the present invention, since reference information is dynamically generated based on a multidimensional database, there is an effect that reference information that matches the contents of the multidimensional database can be easily presented to the user.

  Further, according to the present invention, the comprehensive item information related to the comprehensive item for comprehensively selecting multiple data belonging to different hierarchies is presented as reference information, so that the user can select multiple data comprehensively. Thus, it is possible to easily and quickly select data.

  Further, according to the present invention, the recommended information related to data recommended to be selected as a plurality of data belonging to different hierarchies is presented as reference information, so that a combination of data recommended to be selected can be presented to the user. As a result, it is possible to grasp the data, and it is possible to easily and quickly select data.

  In addition, according to the present invention, a combination of data that is not recommended to be selected is grasped by the user by presenting as reference information non-recommended information related to data that is not recommended to be selected as a plurality of data belonging to different hierarchies. This has the effect of preventing errors during data selection.

  In addition, according to the present invention, since predetermined calculation is performed on a plurality of pieces of analysis target data, there is an effect that the analysis target data can be used in different forms depending on purposes.

  Further, according to the present invention, since subtraction for subtracting the analysis target data belonging to the lower hierarchy from the analysis target data belonging to the upper hierarchy is performed, when data overlapping between different hierarchies in the same dimension is selected by mistake The effect of this duplication can be eliminated and the accuracy of data analysis can be improved.

  Further, according to the present invention, the actual inventory quantity is calculated by subtracting the effective usage quantity and the usage loss quantity from the purchased quantity, and the actual inventory quantity and the target inventory quantity are displayed. In addition, it is possible to grasp the transition of the actual usage amount and the contents thereof, and predict the excess or shortage of the actual inventory amount with respect to the target stock amount, thereby adjusting the purchase amount.

  Embodiments according to the present invention will be described below in detail with reference to the accompanying drawings. [II] First, the basic concept of the present invention will be described, then [II] each embodiment of the present invention will be described, and [III] Finally, modifications to each embodiment of the present invention will be described.

[I] Basic concept of the present invention First, the basic concept of the present invention will be described. The present invention relates to an apparatus, a method, and a program for performing processing on a multidimensional database. Here, the number of dimensions, data contents, data configuration, system configuration, etc. in the multidimensional database are arbitrary.

  The present invention for such a multidimensional database generally includes (1) free combinations of data selection for data analysis using a multidimensional database without being constrained by the data structure of the multidimensional database. In order to enable the selection of data, data for analyzing a plurality of data belonging to the same hierarchy and / or different hierarchies from among data belonging to at least one dimension (hereinafter referred to as analysis target data). (2) Information to be used as reference for selection so that analysis target data can be selected easily and quickly when selecting data in this free combination (hereinafter referred to as reference information). And (3) to prevent problems that may occur in the analysis results when the analysis target data is selected in a free combination. Alternatively, in order to improve the utility value of the analysis result, it performs a predetermined operation to analyzed data, etc. as main features.

  Here, the specific content of the reference information is arbitrary. For example, (2-1) information on comprehensive items for comprehensively selecting a plurality of data belonging to the same layer and / or different layers (hereinafter referred to as comprehensive item information) ), (2-2) Information related to data recommended to be selected as a plurality of data belonging to the same hierarchy and / or different hierarchy (hereinafter referred to as recommended information), and selected as a plurality of data belonging to the same hierarchy and / or different hierarchy Information relating to data that is not recommended to be performed (hereinafter referred to as “no recommended information”) can be presented as reference information. The reference information acquisition method is arbitrary, but can be set in advance by the user, or can be automatically updated and stored based on the user's selection behavior. A specific example of this reference information will be described later.

  In addition, the specific content of the predetermined arithmetic processing on the analysis target data is arbitrary, but, for example, when data of different hierarchies of the same dimension is selected as the analysis target data, there is duplicate data in this analysis target data (If data belonging to the upper hierarchy and data belonging to the lower hierarchy are selected at the same time, data belonging to the lower hierarchy is also included in the upper hierarchy.) In order to eliminate the duplication, subtraction for subtracting the analysis target data belonging to the lower hierarchy from the analysis target data belonging to the upper hierarchy can be performed. A specific example of such calculation processing will be described later.

[II] Embodiments of the Present Invention Next, embodiments of the present invention will be described. However, the present invention is not limited to the embodiments.

[Embodiment 1]
First, Embodiment 1 according to the present invention will be described. In the following, the configuration of the multidimensional database management apparatus will be described first, and then the processing contents of the multidimensional database management method and multidimensional database management program executed using this multidimensional database management apparatus will be described.

(System configuration)
First, the configuration of the multidimensional database management apparatus according to this embodiment will be described. FIG. 1 is a block diagram illustrating a functional concept of the configuration of the entire system including a multidimensional database management apparatus. As illustrated in FIG. 1, a multidimensional database management device 1 and a plurality of client devices 2 are connected via a network 3 so that they can communicate with each other. Then, the user accesses the multidimensional database management device 1 using the client device 2 to perform various operations such as registration of data in the multidimensional database and selection of analysis data, and the analysis result is stored in the client device 2. It can be displayed.

(Configuration of multidimensional database management device)
Next, the configuration of the multidimensional database management apparatus 1 will be described. FIG. 2 is a block diagram illustrating the configuration of the multidimensional database management apparatus 1 in terms of functional concept. As illustrated, the multidimensional database management apparatus 1 includes an input / output control unit 11, an external storage unit 12, a main storage unit 13, a medium reading unit 14, and a control unit 15 in terms of functional concept. They are configured to be communicable with each other via a bus 16.

  Among these, the input / output control unit 11 is an input / output control interface for controlling input / output of various types of information to / from the multi-dimensional database management apparatus 1. Here, the input / output control unit 11 is a communication control interface for performing communication control with the network 3. is there. The input / output control unit 11 selects a plurality of data belonging to the same hierarchy and / or different hierarchies from among data belonging to at least one of the multi-dimensions as analysis target data to be analyzed Means for accepting input of information, means for accepting input of reference information, means for outputting a plurality of analysis object data extracted by the analysis object data extracting unit 15b described later in a predetermined format, and the input / output control unit 11 When receiving the input of the selection information, it functions as means for presenting the reference information stored in the storage unit to the user. In other words, the input / output control unit 11 corresponds to selection information input means, reference information input means, data output means, and reference information output means in the claims.

  The external storage unit 12 is storage means for storing information necessary for each process of the multidimensional database management apparatus 1, and corresponds to the multidimensional database storage means and the reference information storage means in the claims. . The external storage unit 12 stores RDB 12a, MDB 12b, and reference information 12c, and various programs such as a multidimensional database management program (not shown) are installed. The external storage unit 12 can be configured by a non-volatile storage device such as an HD (Hard Disk), for example.

  Here, the RDB 12a is data storage means for storing original data of data to be analyzed in a relational database format. Since the specific configuration of the RDB 12a can be the same as the conventional configuration, a detailed description thereof will be omitted.

  The MDB 12b is means for extracting data to be analyzed from the original data stored in the RDB 12a and holding it in a predetermined configuration, and corresponds to a multidimensional database in the claims. Since the specific configuration of the MDB 12b can be the same as the conventional configuration, detailed description thereof will be omitted. For example, the MDB 12b can associate a plurality of data with each axis corresponding to each dimension. The plurality of data of each axis is hierarchized in a plurality of hierarchies from an upper hierarchy to a lower hierarchy as necessary.

  An example of the data structure of the MDB 12b is conceptually shown in FIG. Here, the example of MDB12b comprised by the 7-dimensional data regarding a dispensing pharmacy is demonstrated. In other words, the dispensing pharmacy needs to manage the inventory of purchased drugs, and if the drug expires, it may be resold to another medical institution. Inventory management was difficult. In order to solve such a problem, the purpose is to improve management loss due to expiration or the like by analyzing inventory quantity from various angles using a multidimensional database. In order to achieve such an object, the MDB 12b has seven types of analysis axis, drug axis, purchase cost axis, region axis, expiration date axis, medical institution axis, and time axis corresponding to each dimension. A shaft is provided. Each axis is associated with data included in a dimension associated with the axis in a hierarchical manner. It is assumed that the variables (count data to be output) are “amount” and “quantity” of the medicine.

  Specifically, only the hierarchy “type” exists in the analysis type axis, and “inventory target” data and “actual result” data are associated with this hierarchy “type”. In addition, in the drug axis, in order from the superordinate concept to the subordinate concept, “total value” data in the hierarchy “total”, data for each medication type such as “external use” data and “internal use” data in the hierarchy “dose classification”, “New drug” data and “generic drug” data in the hierarchy “first and last class”, data for each drug name such as “drug A” data and “drug B” data in the hierarchy “drug”, “powder” in the hierarchy “drug type” ”Data,“ tablet ”data, etc., data for each dosage form,“ 5 ml ”data,“ 10 ml ”data for each sales volume, etc. Data for each sales packaging form such as “100 packets” data is associated with each other.

  Similarly, in the order from the high-level concept to the low-level concept, in the purchase cost axis, “total” data in the hierarchy “total”, “sales” data in the “management item 1”, “purchase cost” data, “ “Purchase amount” data, etc., “Management item 2”, “Drug delivery” data, “Usage loss” data, etc., “Management item 3”, “Expiration date” data, “Fax pre-production” data, “Dispensing” Miss ”data,“ Other ”data, etc., data that identifies the reason why the drug can no longer be used. On the regional axis,“ Total ”data for the“ Total ”level,“ Saitama ”data for the“ Prefecture ”level, Data by prefecture such as “Chiba” data, “Tokyo” data, etc., and data for each specific area within each prefecture, such as “Northern Tokyo” data and “Central Tokyo” data, In the hierarchy “pharmacy”, “pharmacy A” data and “pharmacy B” Pharmacy-specific data, such data are associated respectively.

  In the order from the upper concept to the lower concept, in the expiration date axis, the “expiration date” data in the hierarchy “expiration date”, “total” data in the hierarchy “whole”, and the hierarchy “medical institution” in the medical institution axis “University hospital” data, “National public hospital” data, “Other” data, etc., data by medical institution classification, “Doctor”, “Doctor D1” data, “Doctor D2” data, etc. On the time axis, data for each year such as “2003” data and “2004” data in the hierarchy “year”, “first half” data or “second half” data in the hierarchy “half year”, and “ Monthly data such as “January” data, “April to June” data, “July to September”, “October to December” data, “Month”, “January” data, “February” data, etc. Data is associated with each other.

  The reference information 12c is information that serves as a reference when simultaneously selecting a plurality of data belonging to the same hierarchy and / or different hierarchies as described above, and includes comprehensive item information, recommended information, and non-recommended information.

  Among these items, the comprehensive item information is information on comprehensive items for comprehensively selecting a plurality of data belonging to the same hierarchy and / or different hierarchies. The comprehensive item information is stored in the external storage unit 12 as a table as shown in FIG. 4, for example. This table is configured by associating each axis, a comprehensive item name in each axis, comprehensively selected data and its hierarchy.

  Specifically, for the drug axis, as the generic item name “relatively new drug”, the selection information “new drug” belonging to the hierarchy “first-and-following category” of the drug axis and “drug” belonging to the hierarchy “drug” of the drug axis L-drug P ”data are associated with each other. For example, “drug A” to “drug Z” belong to the hierarchy “drug” in the drug axis, and only “drug A” to “drug K” are new drugs, and “drug L” to “drug P” are generic. Drugs (drugs with expired patents) and generic drugs (after the patent expires), "Drug Q" to "Drug Z" become generic drugs It is assumed that more than one year has passed since then. Here, when the user wants to perform data analysis for “new drug” and “medicine less than one year after becoming generic drug”, by selecting this comprehensive item name “relatively new drug”, “New drug” data and “drug L” to “drug P” data can be comprehensively selected.

  Further, in FIG. 4, regarding the regional axis, the comprehensive item name “Tokyo Metropolitan area and Tama River area”, “Tokyo data” belonging to the regional axis hierarchy “prefecture”, and “ The data is associated with “Eastern Kanagawa Prefecture” data. For example, if you want to perform data analysis for "Tokyo" and "Areas outside of Tokyo but along the Tama River", you can select "Tokyo" Data and "East Kanagawa" data can be selected comprehensively. Such reference information 12c is registered by the user in the analysis target data selection process described later.

  The recommended information is information related to data recommended to be selected as a plurality of data belonging to the same hierarchy and / or different hierarchies. For example, the recommended information is stored in the external storage unit 12 as a table as shown in FIG. This table is configured by associating each axis with data and its hierarchy. Specifically, regarding the drug axis, “drug A, drug C, drug L” data belonging to the hierarchy “drug” of the drug axis is associated with “tablet” data belonging to the hierarchy “drug type” of the drug axis. It has been. For example, the current dosage form of “drug A, drug C, drug L” is “powder”, but for a variety of reasons, such as “drug A”, “drug C, When it is considered preferable to comprehensively analyze the “drug L” data and the “tablet” data, the recommended combinations can be displayed to prompt the user to make a selection.

  In FIG. 5, regarding the regional axis, “East Chiba” data belonging to the hierarchical level “region” of the regional axis and “pharmacy K, pharmacy P” data belonging to the hierarchical level “pharmacy” of the regional axis are associated with each other. Yes. For example, “Pharmacy K, Pharmacy P” is strictly located in “Western Ibaraki”, but is very close to “East Chiba”, or “Pharmacy K, Pharmacy P” has recently moved from “East Chiba” to other areas. Because of the fact that it has just been done, it is possible to comprehensively analyze "East Chiba" data and "Pharmacy K, Pharmacy P" data for various reasons such as that the sales results so far are those in "East Chiba" When it seems preferable, these recommended combinations are displayed to prompt the user to make a selection. Such recommended information is determined in advance by an expert who is familiar with the contents of the data, and is registered in advance by an arbitrary method.

  The non-recommendation information is information relating to data that is not recommended to be selected as a plurality of data belonging to the same hierarchy and / or different hierarchies. This rejection recommendation information is stored in the external storage unit 12 as a table as shown in FIG. 6, for example. This table is configured by associating each axis with data and its hierarchy. Specifically, regarding the drug axis, the selection information “drug B, drug D” data belonging to the hierarchy “drug” of the drug axis is associated with “powder” data belonging to the hierarchy “drug type” of the drug axis. ing. For example, since the drug form of “drug B, drug D” is “tablet”, the user easily mistakes “drug powder”, so the user duplicates “drug B, drug D” data and “tablet” data. When it seems that it is not preferable to include “drug B, drug D” data and “powder” data at the same time for analysis due to various reasons such as By displaying these unrecommended combinations, the user can be alerted not to make such a selection.

  In FIG. 6, regarding the regional axis, “northern Tokyo” data belonging to the hierarchy “region” of the regional axis and “pharmacy B” data belonging to the hierarchy “pharmacy” of the regional axis are associated with each other. For example, when “pharmacy B” is on the prefectural border between “Tokyo” and “Saitama” and “pharmacy B” is classified as “northern Tokyo” for convenience, the user “pharmacy B” is “ It is misunderstood that it is classified as “Nippon Saitama”, and there is a high possibility that “Northern Tokyo” data and “Pharmacy B” data are selected redundantly. ”And“ Pharmacy B ”data are considered to be undesirable for inclusion in the analysis at the same time, these unrecommended combinations are displayed so that the user is not allowed to make such a selection. You can call attention. Such no-recommendation information is determined in advance by an expert who is familiar with the contents of the data, and is registered in advance by an arbitrary method. Note that the recommended information and the non-recommended information can be determined in any combination for any reason other than the above.

  The main storage unit 13 is a main memory used when the control unit 15 executes control. The main storage unit 13 is configured by a volatile storage medium such as a RAM (Random Access Memory), for example, and various programs such as a multidimensional database management program installed in the external storage unit 12 are stored in the main storage unit 13. The unit 13 is loaded as necessary.

  The medium reading unit 14 is a medium reading unit that reads information recorded on an arbitrary computer-readable recording medium 14a such as a CD-ROM (Compact Disk Read Only Memory) or a DVD (Digital Video Disk). . By reading the recording medium 14 a storing various programs such as a multidimensional database management program by the medium reading unit 14, these various programs can be installed in the external storage unit 12. In addition, various programs such as a multidimensional database management program can be installed by an arbitrary method. For example, the programs can be installed via the network 3 without using the recording medium 14a.

  The control unit 15 is a control unit that controls each unit of the multidimensional database management apparatus 1. The control unit 15 is configured by combining, for example, a central processing unit such as a CPU (Central Processing Unit) and a ROM (Read Only Memory) that stores a control program for the CPU. By interpreting and executing various programs such as the loaded multidimensional database management program, the method defined by this program is executed. The control unit 15 is functionally conceptually configured to include an MDB basic management unit 15a, an analysis target data extraction unit 15b, a reference information update unit 15c, and an analysis calculation unit 15d.

  Among these, the MDB basic management unit 15a is a processing means for executing basic management processing of MDB in the conventional multidimensional database management device, and executes, for example, access control to the MDB 12b. More specifically, the analysis target data is acquired by accessing the MDB 12b based on a request from the analysis target data extraction unit 15b. The specific processing by the MDB basic management unit 15a can be performed in the same manner as in the prior art, and is therefore omitted. For example, as adopted in the product “Oracle9i OLAP R9.2.0” manufactured by Oracle, a predetermined mathematical expression that defines the contents of access control for the MDB 12b is prepared, and a request using this mathematical expression is made from the request source. If received, access control is performed based on this mathematical expression, and the access result is returned to the request source.

  In addition, when the selection information is received via the input / output control unit 11, the analysis target data extraction unit 15b stores the plurality of analysis target data specified by the received selection information in the MDB 12b. A means for extracting from a multidimensional database.

  When the reference information 12c is received via the input / output control unit 11, the reference information update unit 15c stores the reference information 12c stored in the external storage unit 12 based on the received reference information 12c. It is a means to update.

  The analysis calculation unit 15d is a means for performing a predetermined calculation on a plurality of pieces of analysis target data specified by the received selection information when the selection information is received via the input / output control unit 11. is there.

  The analysis target data extraction unit 15b, the reference information update unit 15c, and the analysis calculation unit 15d correspond to the analysis target data extraction unit, the reference information update unit, and the analysis calculation unit in the claims, respectively. Although specific processing of each of these units will be described later, processing other than special processing is assumed to be performed by the control unit 15.

(Configuration of client device)
Next, the configuration of the client device 2 will be described. FIG. 7 is a block diagram illustrating the configuration of the client device 2 in terms of functional concept. As illustrated, the client device 2 includes an input / output control unit 21, an input device 22, an output device 23, an external storage unit 24, a main storage unit 25, and a control unit 26 in terms of functional concepts. They are configured to be communicable with each other via a bus 27.

  Among these, the input / output control unit 21 is an input / output control interface for controlling input / output of various information to / from the client device 2. Here, the input / output control unit 21 performs input / output control for the input device 22 and the output device 23. It functions as an output control interface and a communication control interface that controls communication with the network 3.

  The input device 22 is an input means for inputting arbitrary information to the client device 2. For example, a keyboard, a mouse, or a network terminal can be used. The monitor described later also realizes an input function as a pointing device in cooperation with the mouse.

  The output device 23 is an output means for outputting arbitrary information from the client device 2 to a user or an arbitrary device. For example, a monitor or a network terminal can be used.

  The external storage unit 24 is storage means for storing information necessary for each process of the client device 2. Various programs such as a Web browser program and an MDB operation program (not shown) are installed in the external storage unit 24. The external storage unit 24 can be configured by a nonvolatile storage device such as an HD.

  The main storage unit 25 is a main memory used when the control unit 26 executes control. The main storage unit 25 is configured by a volatile storage medium such as a RAM, for example, and various programs such as a Web browser program and an MDB operation program installed in the external storage unit 24 are stored in the main storage unit 25. Loaded as needed.

  The control unit 26 is a control unit that controls each unit of the client device 2. The control unit 26 is configured by combining, for example, a central processing unit such as a CPU, a ROM that stores a control program for the CPU, and the like, and a Web browser program and an MDB operation program loaded in the main storage unit 25. The method prescribed | regulated by this program is performed by performing interpretation and execution of various programs, such as these. The control unit 26 includes a Web browser 26a and an MDB operation unit 26b in terms of functional concept. Among these, the Web browser 26a communicates with the multi-dimensional database management apparatus 1 via the network 3 based on a predetermined communication protocol, and transmits / receives data, output control for outputting received data to the output apparatus 23, and the like. I do. The MDB operation unit 26b is a database application for performing various operations on the MDB 12b of the multidimensional database management apparatus 1, and accesses the multidimensional database management apparatus 1 in cooperation with the web browser 26a as necessary. Input / output various data.

  The multi-dimensional database management apparatus 1 and the client apparatus 2 configured as described above include, for example, a database server, a workstation, a personal computer, a home game machine, an Internet TV, a PDA (Personal Digital Assistant), a mobile phone, It can be configured as a mobile communication terminal such as PHS (Personal Handy Phone System) or a car navigation system.

(Network configuration)
Next, the network 3 in FIG. 1 will be described. The network 3 can be any network as long as the multidimensional database management device 1 and the plurality of client devices 2 are communicably connected. For example, the Internet 3, LAN (Local Area Network), or WAN (Wide Area Network) or the like can be used.

(Processing content)
Next, the content of the multidimensional database management method performed using the multidimensional database management apparatus 1 configured as described above will be described in detail.

  First, the flow of the entire process will be described. This process is broadly divided into a “data input process” in which the user inputs data using the client device 2 to construct the MDB 12b, and a “data analysis process” in which data is analyzed using the MDB 12b. . However, the data input process is performed in the same procedure as in the prior art under the control centered on the MDB basic management unit 15a, and thus detailed description thereof is omitted. Hereinafter, the following data analysis process will be described on the assumption that the MDB 12b as shown in FIG. 4 is constructed by the data input process.

(Processing content-data analysis processing)
An overall flowchart of this data analysis processing is shown in FIG. As shown in the figure, the data analysis processing is further divided into analysis target data selection processing (step SA-1) and analysis target data calculation output processing (step SA-2).

(Processing-Analysis target data selection process)
First, analysis target data selection processing will be described. This process is mainly executed under the control of the analysis target data extraction unit 15b in the multidimensional database management apparatus 1. A flowchart of this process is shown in FIG. First, the user activates the MDB operation unit 26b by a predetermined method via the input device 22 at an arbitrary timing, and instructs activation of the data analysis processing. Then, an activation instruction for data analysis processing is transmitted from the MDB operation unit 26b to the multidimensional database management apparatus 1 via the Web browser 26a.

  The analysis target data extraction unit 15b of the multidimensional database management apparatus 1 that has received this activation instruction accesses the MDB 12b via the MDB basic management unit 15a and sequentially extracts data from the first axis (for example, from dimension 1 to dimension 7). When performing, the data of all the hierarchy of the analysis classification axis | shaft corresponding to the dimension 1 are acquired (step SB-1). Further, the analysis target data extraction unit 15b acquires reference information 12c of the first axis (analysis type axis as described above) stored in the external storage unit 12 (step SB-2). Then, the analysis target data extraction unit 15b generates display data based on the acquired selection items and the reference information 12c, and transmits this display data to the client device 2 (step SB-3). When this display data is received by the client device 2, it is displayed on the output device 23 via the Web browser 26a.

  FIG. 10 shows an example of the data selection screen displayed in this way. This selection screen is a screen for selecting each data corresponding to the analysis type axis, and the display column 40 for displaying the data of the hierarchy “type”, and selecting or canceling the data to be analyzed data among these data Selection buttons 41 and 42 for display, a display field 43 for displaying data selected as analysis target data, and a selection button 44 for instructing transition to a selection screen for data of the next axis Has been. Then, the data to be analyzed is selected by clicking on the data displayed in the display column 40 via the input device 22 such as a mouse, and when the selection button 41 is pressed, the clicked data is displayed. It is displayed in the display column 43. FIG. 11 shows a state where “actual result” data is selected by such an operation. In addition, when data to be canceled is selected by clicking on the data displayed in the display column 43 and the selection button 42 is pressed, the clicked data is deleted from the display column 43. By performing such an operation, analysis target data can be selected. When the selection button 44 is pressed via the input device 22 such as a mouse after the selection is completed, the selected analysis target data is transmitted from the MDB operation unit 26b to the multidimensional database management device 1 via the Web browser 26a. The At this time, the next axis data and the reference information transmission request are transmitted together.

  On the other hand, the analysis target data extraction unit 15b of the multidimensional database management device 1 monitors whether or not the analysis target data is transmitted from the client device 2 (step SB-4), and receives this analysis target data (step SB-4). This analysis target data is stored in the external storage unit 12 (corresponding to the selection information input step in the claims) (step SB-5). Next, the analysis target data extraction unit 15b determines whether or not the selection for all axes has been completed (step SB-6). If not, the analysis target data extraction unit 15b determines whether the selection is completed in the MDB 12b via the MDB basic management unit 15a. Access to acquire data of the next axis (for example, drug axis corresponding to dimension 2). At the same time, the analysis target data extraction unit 15b acquires reference information 12c of the next axis (the drug axis as described above) stored in the external storage unit 12. Then, the analysis target data extraction unit 15b generates display data based on the acquired data and the reference information 12c, and transmits this display data to the client device 2 (again, step SB-3). When this display data is received by the client device 2, it is displayed on the output device 23 via the Web browser 26a. Thereafter, similarly, the same processing is repeated until selection for all axes is completed (until determined as Yes in step SB-6).

  Next, FIG. 12 shows an example of a drug axis data selection screen. In this screen, as display columns for selection target data, display columns 50 to 56 for data of hierarchy “total” to hierarchy “packaging”, a selection button 57 corresponding to each, and display of analysis target data Columns 58-64 are included. Then, the user can select data to be analyzed with respect to the drug axis from the same or different hierarchies in the same manner as in the analysis type axis selection screens of FIGS.

  Here, for example, as described above, the selection item “drug” in the lower hierarchy includes “drug A” to “drug Z”, of which only “drug A” to “drug K” are new drugs and “drug L”. It is assumed that “drug P” is less than one year after becoming a generic drug, and “drug Q” to “drug Z” have been over one year since becoming a generic drug. Here, when a user wants to perform data analysis for “new drug” and “medicine less than one year after becoming a generic drug”, conventionally, it was not possible to select data in a different hierarchy. Therefore, “drug A” to “drug P” had to be individually selected. On the other hand, since this apparatus can select data of different hierarchies, the selection is simpler. Specifically, it is only necessary to select “new drug” from the selection item “starting / following category” and individually select “drug L” to “drug P”, and the degree of freedom of data selection is improved. Conventionally, even if the user selects a plurality of data in the same hierarchy, for example, “drug A” and “drug B” at the same time, they can be simply displayed side by side. The sum total could not be displayed. On the other hand, in the present apparatus, a plurality of data on the same hierarchy can be simultaneously selected and added, so the degree of freedom in data analysis is improved.

  In addition, the selection screen is provided with an area for displaying and registering comprehensive item information among the reference information 12c acquired in step SB-2 of FIG. Specifically, a display column 70 for displaying a generic item name corresponding to the drug axis, a display column 71 for displaying data corresponding to the generic item name, and generic item information are registered. A registration button 72 is included. Here, in the display column 70, a comprehensive item name “relatively new medicine” is displayed. In the display column 71, “new drug” and “drug L” to “drug P” are displayed as data corresponding to the generic item name “relatively new drug”. Here, when the user wants to perform data analysis on a new drug and a drug that is less than one year old after becoming a generic drug, this comprehensive item name “relatively new drug” is selected, and a selection button 65 is selected. Press down. Then, this generic item name is transmitted to the multidimensional database management apparatus 1, data corresponding to this generic item name is acquired from the reference information 12c of the external storage unit 12, and stored in the external storage unit 12 as analysis target data. (Step SB-5 in FIG. 9 above). Therefore, a plurality of data of the same hierarchy or different hierarchies can be selected at a time, and the convenience of data selection is improved.

  Registration and acquisition of such comprehensive item information are performed as follows. That is, the user inputs an arbitrary comprehensive item name in the display field 70 on the selection screen in FIG. 12, and inputs data to be associated with the comprehensive item name input in the display field 70 in the display field 71. Then, by pressing the registration button 72, the input data and data for specifying the axis at that time are transmitted from the client apparatus 2 to the multidimensional database management apparatus 1. Receiving this transmission, the reference information updating unit 15c updates the table of FIG. 4 stored in the external storage unit 12 based on the transmitted data (step SB-5 in FIG. 9 above). This corresponds to the reference information storing step and the reference information updating step in FIG. The updated comprehensive item information is called in the next analysis target data selection process (SB-2 in FIG. 9), transmitted to the client apparatus 2, and displayed as shown in FIG.

  Further, the selection screen of FIG. 12 includes a display field 73 for displaying recommended information and a display for displaying non-recommended information of the reference information 12c acquired in step SB-2 of FIG. A column 74 is provided. Specifically, “drug A, drug C, drug L, tablet” is displayed as recommended information, and “drug B, drug D, powder” is displayed as non-recommended information. Therefore, the user selects data in a combination that matches the recommended information while viewing the recommended information, or the data that does not match the rejected information while viewing the recommended information. By making this selection, appropriate data selection can be performed, and data selection can be performed easily and quickly.

  Next, FIG. 13 shows an example of a screen for selecting regional axis data. In this screen, as display columns for selection target data, display columns 80 to 83 for data of hierarchy “total” to hierarchy “pharmacy”, a selection button 84 corresponding to each of these, and display of analysis target data Columns 85-88 are included. Then, the user can select data to be analyzed with respect to the regional axis from the same or different hierarchies as in the analysis type axis selection screens of FIGS.

  In addition, the selection screen is provided with an area for displaying and registering comprehensive item information among the reference information 12c acquired in step SB-2 of FIG. Specifically, a display column 90 for displaying a generic item name corresponding to the regional axis, a display column 91 for displaying data corresponding to the generic item name, and generic item information are registered. A registration button 92 is included. Here, in the display column 90, the comprehensive item name “around Tokyo and the Tamagawa” is displayed. In the display column 91, “Tokyo” and “East Kanagawa Prefecture” are displayed as data corresponding to the comprehensive item name “Tokyo and the vicinity of Tamagawa”. Here, if you want to analyze data for Tokyo and the Tama River area, you can select multiple items of the same or different levels at once by selecting this comprehensive item name “Tokyo and the Tama River area”. This improves the convenience of data selection.

  In addition, the selection screen in FIG. 13 includes a display column 93 for displaying recommended information and a display for displaying non-recommended information in the reference information 12c acquired in step SB-2 in FIG. A column 94 is provided. Specifically, “East Chiba, Pharmacy K, Pharmacy P” data is displayed as the recommended information, and “Northern Tokyo, Pharmacy B” data is displayed as the recommended information. Therefore, the user selects data in a combination that matches the recommended information while viewing the recommended information, or the data that does not match the rejected information while viewing the recommended information. By making this selection, appropriate data selection can be performed, and data selection can be performed easily and quickly. In addition, for the axes other than those described above, that is, the purchase cost axis, the expiration date axis, the medical institution axis, and the time axis, the selection screen display, data selection, and analysis target are substantially the same as described above. Data is stored, but detailed description thereof is omitted.

  Then, as shown in FIG. 9, when the data selection for all the axes is completed (step SB-6, Yes), the analysis target data extraction unit 15b creates a totaling formula based on the selection result for each axis. (Step SB-7). That is, for each axis, a mathematical expression for acquiring data selected as analysis target data is generated, and this is integrated to generate one aggregate expression. The formula for each axis is generated by, for example, using information for specifying the selected data as a parameter, and incorporating this parameter into a predetermined formula that defines the content of access control for the MDB 12b. In particular, by acquiring the data to be analyzed by generating mathematical formulas in this way, the MDB 12b is not actually reconstructed, but a database corresponding to the data selected by the user is virtually constructed. For this reason, compared with the case where MDB12b is reconstructed, analysis object data can be acquired rapidly and at low cost.

  Finally, the analysis target data extraction unit 15b acquires the analysis target data using the generated aggregation formula (step SB-8, corresponding to the analysis target data extraction step in the claims). That is, the analysis target data extraction unit 15b passes the generated aggregation formula as an argument to the MDB basic management unit 15a. The MDB basic management unit 15a interprets the contents of the aggregation formula, acquires the analysis target data by accessing the MDB 12b based on the interpretation result, and returns the analysis target data to the analysis target data extraction unit 15b. This ends the analysis target data selection process.

  Next, the calculation output process (step SA-2) of the analysis target data in FIG. 8 is executed. This process is mainly performed under the control of the analysis calculation unit 15d of the multidimensional database management apparatus 1 in FIG. A flowchart of this process is shown in FIG. The analysis calculation unit 15d acquires the analysis target data obtained in the previous analysis target data selection process (step SC-1).

  Then, the analysis operation unit 15d performs predetermined four arithmetic operations on the analysis target data (corresponding to the analysis operation step in the claims). Specifically, it is determined whether or not there is data duplication in different layers of the same dimension in the analysis target data (step SC-2). If there is duplication (step SC-2, Yes). ) Subtracting the overlapping lower layer data from the overlapping upper layer data is used as new analysis target data (step SC-3).

  The significance of such subtraction is as follows. That is, in the analysis target data selection process, data selection in different hierarchies of the same dimension is allowed, so that there is a possibility that part of the selected data overlaps. For example, in the drug axis, when “drug A” data belonging to the hierarchy “drug” and “tablet” data of the hierarchy “drug type” lower than this hierarchy “drug” are selected simultaneously, In the case where half of “A” is sold as “powder” and the other half is sold as “tablet”, the portion corresponding to “tablet” in the “drug A” data of the hierarchy “drug” and the hierarchy Of the “tablet” data of “drug form”, the portions corresponding to “drug A” overlap each other. Therefore, in order to eliminate this overlapping portion and perform accurate data analysis, the portion corresponding to the “drug A” data in the “tablet” data of the hierarchy “drug type” from the “drug A” data of the hierarchy “drug” Is subtracted. In particular, if the user is not familiar with the data structure of the MDB 12b and its contents, the subtraction process is useful because there is a high possibility that such a redundant selection will be made by a careless mistake.

  After performing such subtraction, or when it is determined in step SC-2 that there is no data duplication, the analysis calculation unit 15d determines whether or not it is necessary to calculate the actual inventory amount (step SC-4). . Here, the actual inventory amount is the amount of medicine actually in stock at the pharmacy. This actual inventory quantity is calculated by subtracting the actual usage quantity from the purchased quantity for normal products, but especially for drugs, various usage losses (dispensing errors, which are losses due to dispensing errors). ”,“ Fax pre-made ”and“ due expiry date ”of the drug, etc. that occurred due to the fact that the customer did not come to pick up after receiving a dispensing reservation at Fax. Amount = Calculated as Purchase amount-Actual use amount-Use loss amount. The necessity of this calculation is determined by, for example, providing an item for selecting whether or not the actual usage amount is necessary on the selection screen displayed on the client device 2 in the analysis target data selection process. Is instructed by the user, it is determined that it is necessary to calculate the actual usage amount. Alternatively, when the selected data includes “purchase amount” data, “actual usage amount” data, and “use loss amount” data, it may be determined that the actual usage amount is calculated. And when the calculation unit 15d needs to calculate the actual amount of inventory (step SC-4, Yes), by subtracting the actual usage amount (herein, drug delivery) and the usage loss amount from the purchased amount, The actual inventory quantity is calculated (step SC-5).

  After calculating the actual inventory quantity in this way, or when determining that it is not necessary to calculate the actual inventory quantity (step SC-4, No), the analysis operation unit 15d performs the analysis target based on the analysis target data. Output data for displaying the data on the output device 23 of the client device 2 is generated in a predetermined format (step SC-6), and this output data is transmitted to the client device 2 (step SC-7. Claims) Corresponding to the data output step). This completes the calculation output processing of the data to be analyzed. The MDB operation unit 26 b of the client device 2 that has received the output data displays the output data using the output device 23.

  The output screen displayed in this way is illustrated in FIG. This output screen is an example of a “use result analysis” screen that shows the use results of medicines from January to April 2004 in pharmacy A in comparison with their use targets. Here, in the process of selecting the analysis target data, “Actual” data and “Inventory target” data of the “Type” hierarchy of the analysis type axis, “Total” data of the “Total” level of the drug axis, Hierarchy of the purchase cost axis “Management item 1” “sales” data and “purchase amount” data and “management item 2” “medicine delivery (actual use amount)” data and “use loss amount” data, regional axis hierarchy “pharmacy” “Pharmacy A”, “expiration date” data of the “expiration date” hierarchy “expiration date”, “total” data of the “all” medical care facility hierarchy, “January 2004-” of the “month” time axis hierarchy It is assumed that “April 2004” is selected.

  In this screen, the horizontal axis of the graph shows time, and the vertical axis shows quantity. Inside the graph, the purchase amount, actual inventory quantity, and inventory target quantity are displayed in the upper half of the graph. In half, the amount of use loss and drug delivery (actual use amount) are displayed. As a result, the user can grasp the transition of the actual inventory amount and the actual usage amount and their contents, and adjust the purchase amount by predicting the excess or deficiency of the actual inventory amount with respect to the target inventory amount. it can.

  Another output screen example is illustrated in FIG. This output screen is an example of an “expiration expiration loss analysis” screen that analyzes loss due to expiration for a specific medicine and region. Here, in the analysis target data selection process, “inventory target” data and “actual result” data of the hierarchy “type” of the analysis type axis, “drug A” data, “drug A ′” of the hierarchy “drug” of the drug axis Data, “drug E” data, “drug E ′” data, “sales” data and “purchase cost” data in the hierarchy “management item 1” of the purchase cost axis, “drug delivery” in the hierarchy “management item 2” Data and “Usage loss” data, “Expiration date” data of “Management item 3”, “Fax. Preliminary” data, “Dispensing error” data, “Other” data, “Axis” of the regional axis “Pharmacy” “Pharmacy A” data, “Pharmacy B” data, “Pharmacy C” data, “Expiration date” data of the “Expiration date” hierarchy of the “Expiration date” axis, “Total” data of the “Whole” of the medical institution axis, The level “Month” is “January 2004-December 2004” It is deemed to have been-option.

  In this screen, the management item data for each month is displayed in a table format on the upper side, and the breakdown of the usage loss amount for each month is displayed in a graph format on the lower side. Thereby, the user can grasp the cause and transition of the use loss, and can refer to it when considering the elimination.

  As described above, according to the present embodiment, a plurality of data belonging to the same hierarchy and / or different hierarchies can be simultaneously selected as analysis target data to be analyzed from among data belonging to one dimension, and so on. It is possible to increase the degree of freedom in selecting data from the multidimensional database, increase the diversity of data analysis, and increase the added value of multidimensional database management.

  In addition, according to the present embodiment, reference information is automatically presented to the user, so that an error in data selection that may occur to the user due to an increased degree of freedom in data selection can be eliminated, and simple and quick data selection There is an effect that can be made possible.

  Further, according to the present embodiment, since the reference information stored in the external storage unit is updated based on the reference information, the latest reference information can be automatically presented to the user.

  In addition, according to the present embodiment, by presenting, as reference information, comprehensive item information related to comprehensive items for comprehensively selecting multiple data belonging to the same hierarchy or different hierarchies, multiple data is comprehensively presented to the user. It can be selected, and simple and quick data selection can be made possible.

  In addition, according to the present embodiment, recommended data that is recommended to be selected by presenting recommended information related to data recommended to be selected as a plurality of data belonging to the same hierarchy or different hierarchies as reference information. The combination can be grasped by the user, and simple and quick data selection can be made possible.

  In addition, according to the present embodiment, it is possible to display data that is not recommended to be selected by presenting as reference information non-recommended information related to data that is not recommended to be selected as a plurality of data belonging to the same hierarchy or different hierarchies. The combination can be grasped by the user, and an error at the time of data selection can be prevented.

  In addition, according to the present embodiment, the predetermined calculation is performed on a plurality of pieces of analysis target data, so that the analysis target data can be used in different forms depending on the purpose. As one form, since subtraction is performed to subtract the analysis target data belonging to the lower hierarchy from the analysis target data belonging to the upper hierarchy, even when data overlapping between different hierarchies in the same dimension is selected by mistake , The influence of this duplication can be eliminated and the accuracy of data analysis can be improved.

  Further, according to the present embodiment, the actual inventory amount is calculated by subtracting the effective usage amount and the usage loss amount from the purchased amount, and the actual inventory amount and the target inventory amount are displayed. It is possible to grasp the transition and the contents of the actual amount and the actual usage amount, and to predict the excess or deficiency of the actual amount of inventory with respect to the target stock amount and adjust the purchase amount.

[Embodiment 2]
Next, a second embodiment according to the present invention will be described. In the first embodiment, basically, reference information preset by experts and the like is used and updated as necessary. However, in the present embodiment, reference information is dynamically generated. This is different from the first embodiment. Unless otherwise specified, the configuration and processing are the same as those in the first embodiment, and the same components and processing steps are denoted by the same reference numerals as those in the first embodiment as necessary.

(System configuration)
First, the configuration of the multidimensional database management apparatus 100 according to the present embodiment will be described. FIG. 17 is a block diagram illustrating a functional concept of the configuration of the multidimensional database management apparatus 100. As illustrated in FIG. 17, the multidimensional database management apparatus 100 is functionally conceptually configured with an input / output control unit 101, an external storage unit 102, a main storage unit 103, a medium reading unit 104 that reads a recording medium 104a, and A control unit 105 is provided, and these units are connected to each other via a bus 106 so as to communicate with each other. Among these units, the input / output control unit 101, the main storage unit 103, the medium reading unit 104, and the recording medium 104a are the input / output control unit 11, the main storage unit 13, the medium reading unit 14, and the recording medium of the first embodiment, respectively. The configuration can be the same as 14a.

  Further, the RDB 102a, the MDB 102b, and the prescription history DB 102c are stored in the external storage unit. An example of the data structure of the MDB 102b is conceptually shown in FIG. Here, the example of MDB102b comprised by the three-dimensional data regarding the prescription record of the medicine in a hospital is demonstrated. In other words, the patient's medical condition is diagnosed and the drug is prescribed, and this prescription history is sometimes made into a database, but the effect of the prescribed drug on the patient is not made into a database, In order to select a drug to be prescribed next with reference to past effects, the doctor had to refer to the medical chart one by one. Therefore, doctors sometimes confused drugs that had been effective in the past with drugs that had no effect.

  In order to solve such problems, the present embodiment aims to improve the accuracy and efficiency of prescription by analyzing the effects of prescription drugs from various angles using a multidimensional database. To do. In order to achieve such an object, the MDB 102b is provided with three axes corresponding to each dimension: a patient axis, a drug axis, and a time axis. Each axis is associated with data included in a dimension associated with the axis in a hierarchical manner. It is assumed that the variable is “amount” or “quantity” of the medicine.

  Specifically, in the patient axis, data for each patient such as “patient A” data and “patient B” data is associated with the hierarchy “patient”. In the drug axis, in order from the superordinate concept to the subordinate concept, the data for each drug effect such as “cold medicine” data and “stomach medicine” data in the hierarchy “medication”, “external use” data and “ Data for each type of medication such as “internal use” data is associated with each other. The data on the other layers of the drug axis and the time axis are the same as in the first embodiment.

  An example of the data structure of the prescription history DB 102c is conceptually shown in FIG. Here, the patient name, the drug name of the medicine prescribed to each patient so far, and the effect (either good or bad) of each drug are stored in association with each other.

  In addition, the control unit 105 is a control unit that controls each unit of the multidimensional database management apparatus 100, and functionally conceptually includes an MDB basic management unit 105a, an analysis target data extraction unit 105b, a reference information generation unit 105c, and prescription history information. The update unit 105d and the analysis calculation unit 105e are provided. Among these, the MDB basic management unit 105a, the analysis target data extraction unit 105b, and the analysis calculation unit 105e can be configured similarly to the MDB basic management unit 15a, the analysis target data extraction unit 15b, and the analysis calculation unit 105e of the first embodiment. The reference information generation unit 105c is a unit that dynamically generates reference information based on data stored in the MDB 102b. In addition, when the prescription history information is received via the input / output control unit 11, the prescription history information update unit 105d receives the prescription history information stored in the external storage unit based on the received prescription history information. It is a means to update.

  The analysis target data extraction unit 105b, the reference information generation unit 105c, the prescription history information update unit 105d, and the analysis calculation unit 105e are respectively an analysis target data extraction unit, a reference information generation unit, and a prescription history information update in the claims. This corresponds to the means and the analytical calculation means. Although specific processing of each of these units will be described later, processing other than special processing is assumed to be performed by the control unit 105.

(Processing content)
Next, the contents of the multidimensional database management method performed using the multidimensional database management apparatus 100 configured as described above will be described in detail. The data analysis processing of the present embodiment is roughly divided into analysis target data selection processing and analysis target data calculation output processing. The analysis target data calculation output processing is conceptually the same as in the first embodiment. Therefore, only the analysis target data selection process will be described.

(Processing-Analysis target data selection process)
The analysis target data selection process will be described. A flowchart of this process is shown in FIG. First, when prescribing a medicine to a patient, a doctor activates the MDB operation unit 26b by a predetermined method via the input device 22 and instructs activation of data analysis processing. Then, an activation instruction for data analysis processing is transmitted from the MDB operation unit 26b to the multidimensional database management apparatus 100 via the Web browser 26a.

  The analysis target data extraction unit 105b of the multidimensional database management apparatus 100 that has received this activation instruction acquires all data of the patient axis (step SD-1). Further, the reference information generation unit 105c generates reference information based on the acquired data (step SD-2). However, here, reference information is generated only for the drug axis, and generation is not performed for the patient axis and the time axis. Then, the analysis target data extraction unit 105b generates display data based on the acquired data, and transmits this display data to the client device 2 (step SD-3). When this display data is received by the client device 2, it is displayed on the output device 23 via the Web browser 26a.

  FIG. 21 shows an example of the data selection screen displayed in this way. This selection screen is a screen for selecting patient axis data, a display column 110 for displaying data of the hierarchy “patient”, and a selection button for instructing transition to the selection screen for data of the next axis 111 and a display column 112 for displaying data of a selected patient (a patient to be analyzed). Then, when the doctor selects the patient data to be analyzed from the data displayed in the display column 110 via the input device 22 such as a mouse by clicking or the like and presses the selection button 111, the click is performed. The equalized data is displayed in the display column 112. After the selection is completed, when the doctor presses the selection button 113 via the input device 22 such as a mouse, the selected analysis target data is transferred from the MDB operation unit 26b to the multidimensional database management device 100 via the Web browser 26a. Sent to. At this time, the next axis data and the reference information transmission request are transmitted together.

  On the other hand, in FIG. 20, the analysis target data extraction unit 105b of the multidimensional database management apparatus 100 monitors the presence / absence of transmission of analysis target data and the like from the client apparatus 2 (step SD-4). (Corresponding to the selection information input step in the claims), the analysis object data is stored in the external storage unit 102 (step SD-5). Next, the analysis target data extraction unit 105b determines whether or not selection for all axes has been completed (step SD-6). If not, the next axis (for example, dimension 2 is supported). To obtain the drug axis).

  Here, the reference information generation unit 105c acquires prescription history information corresponding to the previously selected patient from the prescription history DB 102c, and based on this prescription history information, reference information (general information, recommended information, non-recommended information). Is dynamically generated (step SD-2). For example, as comprehensive information, drugs that do not match the prescription history information are selected from drugs belonging to the hierarchy “drug” on the drug axis, and these are comprehensively grouped under the concept of “unprescription drugs”. In addition, among the drugs belonging to the hierarchy “drug” on the drug axis as the recommended information, the drug having the effect “good” is selected from the drugs prescribed to the patient in the prescription history information. In addition, among the drugs belonging to the hierarchy “drug” on the drug axis as the non-recommendation information, the drug having the effect “not good” is selected from the drugs prescribed to the patient in the prescription history information.

  Then, the analysis target data extraction unit 105b generates display data based on the acquired data and the generated reference information, and transmits this display data to the client device 2 (again, step SD-3). When this display data is received by the client device 2, it is displayed on the output device 23 via the Web browser 26a. Thereafter, similarly, the same processing is repeated until selection for all axes is completed (until determined as Yes in step SD-6).

  Next, FIG. 22 shows an example of a drug axis data selection screen. In this screen, as display columns for data to be selected, display columns 120 to 126 for data of the hierarchy “medicinal effect” to hierarchy “packaging”, a selection button 127 corresponding to each, and display of analysis target data Columns 128-134 are included. The user can select data to be analyzed with respect to the drug axis from the same or different levels using these fields.

  Here, the selection screen is provided with an area for displaying reference information (general information, recommended information, non-recommended information) dynamically generated in step SD-2 of FIG. Specifically, a display column 140 for displaying the comprehensive information name and a display column 141 for displaying data corresponding to the comprehensive information name are displayed. Here, in the display column 140, a comprehensive item name “unprescription medicine” is displayed. In the display column 141, “drug L” to “drug O” are displayed as data corresponding to the generic item name “unprescription drug”. Here, when the doctor wants to analyze unprescription medicines for the patient collectively, this comprehensive item name “unprescription medicine” is selected, and the selection button 144 is pushed down. Then, this generic item name is transmitted to the multidimensional database management apparatus 1, and data corresponding to this generic item name is stored in the external storage unit 12 as analysis target data (step SD-5 in FIG. 20 described above). Therefore, a plurality of data of the same hierarchy or different hierarchies can be selected at a time, and the convenience of data selection is improved.

  In addition, the selection screen in FIG. 22 is provided with a display field 142 for displaying recommended information and a display field 143 for displaying non-recommended information. Specifically, “drug C, drug L” is displayed as the recommended information, and “drug B, drug D” is displayed as the recommended information. Therefore, doctors can select drugs that have had good past prescription results while viewing recommended information, or select drugs that have had poor prescription results while viewing recommended information. By excluding from the above, an appropriate drug can be selected, and data selection can be performed easily and quickly. Thereafter, as in the first embodiment, the data selected by the doctor is added together and the analysis result is displayed (steps SD-7 and SD-8).

  Further, after referring to the analysis result, either before or after the doctor finally prescribes the drug, the analysis target data extraction unit 105b generates screen data as shown in FIG. 23 and transmits it to the client device. On this screen, a display field 160 for displaying the medicine prescribed for the patient last time and a selection button 161 for inputting the effect of the medicine are displayed. The medicine prescribed for the patient last time is acquired from the prescription history information acquired from the prescription history DB 102c. Then, the doctor makes an inquiry to the patient, determines the effect of the medicine prescribed last time, and inputs the determination result with the selection button 161. The screen also includes a display field 162 for displaying the currently selected medicine, a selection button 163 for selecting the medicine to be finally prescribed this time, and a display field 164 for displaying the medicine thus selected. Is provided. Then, the doctor can select a medicine by selecting a medicine to be prescribed this time from among the medicines displayed in the display field 162 and pressing down the selection button 163. After such selection, when the doctor presses the registration button 165, the selected information is transmitted to the multidimensional database management apparatus 100. Then, the prescription history information updating unit 105d updates the prescription history information in the prescription history DB 102c based on the transmitted information. In this way, by updating the prescription history information, it is possible to dynamically generate the reference information in step SC-2 of FIG. 20 based on the latest prescription history information.

  As described above, according to the present embodiment, in addition to the same effects as the first embodiment, the reference information is dynamically generated based on the multidimensional database, so that the reference information that matches the contents of the multidimensional database. Can be easily presented to the user.

[III] Modifications to Each Embodiment Although the embodiments of the present invention have been described above, the specific configuration and method of the present invention are within the scope of the technical idea of each invention described in the claims. It can be arbitrarily modified and improved. Hereinafter, such a modification will be described.

(About information content)
The contents of the specific information stored in the RDBs 12a and 102a and the MDBs 12b and 102b and the contents of information calculated based on this information can be arbitrarily changed. For example, in addition to data related to dispensing pharmacies, these data include information on restaurant opening results and store opening plans (for example, restaurant type, location, local resident composition, customer unit price, etc. The sales amount of the store may be used as a variable). In this case, the store opening analysis of the restaurant can be performed.

(Combination of reference information)
In addition, as comprehensive item information, not only data of different hierarchies of the same dimension, but also a plurality of data belonging to the same hierarchy of the same dimension or multi-dimensional data may be selected comprehensively. Further, the recommended information and the non-recommended information may also be recommended or not recommended for a plurality of data belonging to the same hierarchy of the same dimension or a combination of data of a plurality of dimensions. For example, when a plurality of data belonging to the same hierarchy of the same dimension is used as recommended information, the drug names of similar drugs having the same efficacy are displayed as recommended information on the drug axis so that these drugs are selected simultaneously. The user may be prompted. Alternatively, when a plurality of data belonging to the same hierarchy of the same dimension is used as non-recommendation information, drug names of drugs having different units (grams, packaging, ml, etc.) are displayed as non-recommendation information on the drug axis. You may make it not select simultaneously.

(Registering reference information)
Further, the comprehensive item information has been described as being registered by the user in the first embodiment, but an expert or the like may be registered in advance in the external storage unit 12 as in the case of recommended information or not recommended information. On the contrary, although it has been described that the recommended information and the non-recommended information are registered in advance by an expert or the like, the user may be able to register as in the comprehensive item information. These various types of information can also be provided to the multidimensional database management apparatus 1 as needed via the network 3 or the recording medium 14a. Alternatively, the external storage unit 12 in which these pieces of information are recorded is arranged independently, and the external storage unit 12 is accessed from a plurality of multidimensional database management apparatuses 1 via the network 3 so that the latest information is required. You may make it acquire according to it.

(How to obtain reference information)
In addition, as in the second embodiment, various other methods can be adopted as a method for dynamically acquiring reference information. For example, when the user inputs an item such as “early January 2004” as a time axis comprehensive item, the analysis target data extraction unit 105b of the multidimensional database management apparatus 100 uses the time axis hierarchy “month”. Of the “January 2004” data, data corresponding to “early January 2004” (that is, data from January 1, 2004 to January 10, 2004) may be automatically extracted. . When the data necessary for this extraction (in this case, data in units of days) is not included in the MDB 102b, the data can be acquired from the RDB 102a and used. In this way, by using information that can be automatically determined from known information as reference information, the reference information is dynamically acquired as necessary, and the user and an expert are required to register the reference information 12c. It can be omitted.

(How to use reference information)
In the above embodiments, the comprehensive item information, the recommended information, or the no-recommendation information is output to the output screen so that the user can refer to it. However, it can be used in other forms. For example, only these data can be output to the display field of the output screen so that only data that matches the combination specified in the comprehensive item information or data that matches the recommended combination in the recommended information can be selected, or These data can be excluded from the display field of the selection screen in advance so that data matching a combination not recommended in the rejection recommendation information is not selected. Alternatively, if only some of the data that matches the recommended combination in the recommended information is selected and the others are not yet selected, a message indicating that they have not been selected is displayed on the selection screen. Unselected data may be blinked on the selection screen, or when all data that matches a combination not recommended in the rejection recommendation information is selected, a message to that effect is displayed on the selection screen. May be. Such processing is performed, for example, every time the user selects data on the selection screen, and the contents are transmitted to the multidimensional database management device 1, and the analysis target data extraction unit 15 b includes the selected data, the comprehensive item information, This can be achieved by determining whether or not the recommended information or the non-recommended information matches or not, generating screen data including a message or warning according to the determination result, and outputting the screen data to the client device 2. By these things, a user's attention can be called.

  Alternatively, the reference information can be fed back to the designers of these databases in order to make reference when the RDBs 12a and 102a and the MDBs 12b and 102b are constructed. For example, when the designer's email address is stored in the external storage unit 12 and the reference information update unit 15c updates the reference information 12c, the reference information 12c is applied to the email address and transmitted as an email. You may do it. Alternatively, the designer may browse the latest reference information 12c updated by the reference information update unit 15c and stored in the external storage unit 12 at an arbitrary timing and method. In this case, the designer can grasp the reference information requested by the user, and can reference it when the RDBs 12a and 102a and the MDBs 12b and 102b are constructed.

(Calculation of analysis target data)
In addition to the above-described subtraction of duplicate data, any calculation including four arithmetic operations can be performed as the calculation of the analysis target data. For example, when particular data is to be emphasized, the user selects the data to be emphasized on the selection screen, and the analysis target data extraction unit 15b selects a predetermined coefficient (or the selected data) The data may be weighted by multiplying by a numerical value etc. that the user inputs on the selection screen. For example, when only “drug A” is important, only the “drug A” data is displayed by multiplying it by 1.2, and the data of other drugs are displayed as they are. Can be emphasized.

(About analysis data output)
The output format of the analysis target data can be arbitrarily changed. This determination method is also arbitrary. For example, when the analysis target data selection process is started, an analysis menu is presented to the user, and output is performed in a format corresponding to the user's selection result for the analysis menu. May be. For example, after the selection process of the analysis target data is started, a selection button that can select either “Actual usage analysis” or “Expiration loss analysis” is displayed on the output device 23 of the client device 2 and selected. The transmitted contents are transmitted to the multidimensional database management apparatus 1. Further, the external storage unit 12 includes output data generation logic to be executed when “use result analysis” is selected, and output data generation logic to be executed when “expiration loss analysis” is selected. And are stored. At the time of generating the output data of the analysis target data, the analysis calculation units 15d and 105d acquire the generation logic corresponding to the user selection result from the external storage units 12 and 102, and based on this generation logic, the analysis target data Totals and generates output data. Further, when the analysis target data that does not match the predetermined logic is selected by the user, a predetermined error screen may be transmitted to the client device 2.

(About problems to be solved and effects of the invention)
The problems to be solved by the invention and the effects of the invention are not limited to the above-described contents, and the present invention solves the problems not described above or produces the effects not described above. In addition, only a part of the described problems may be solved or only a part of the described effects may be achieved. For example, even in the case where a plurality of data belonging to different hierarchies can be selected simultaneously for only some of the plurality of axes, some of the problems of the present application are solved.

(About configuration and control)
In addition, all or any part of the control described as being automatically performed in each embodiment may be performed manually, and conversely, all or any of the control described as being performed manually is performed. The part may be automated based on a known technique or the above-described idea. In addition, each functional block of the control units 15, 26, and 105 shown in each embodiment may be configured with a hard wired logic. Further, each of the electrical components described above is functionally conceptual and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each part is not limited to the one shown in the figure, and all or a part thereof may be functionally or physically distributed / integrated in arbitrary units according to various loads and usage conditions. Can be configured. For example, the client device 2 may have a part or all of the configuration of the multidimensional database management device 1. In addition, the processing procedure or the control procedure shown in the document or the drawing can be arbitrarily changed unless otherwise specified.

  As described above, the present invention is useful for performing analysis by selecting analysis target data in a free combination in data analysis using a multidimensional database, and performing data selection simply and quickly. It is suitable for constructing a management device, management method, and management program for a multidimensional database having higher utility value than before.

It is a block diagram which illustrates functionally conceptually the structure of the whole system containing the multidimensional database management apparatus concerning Embodiment 1 of this invention. 1 is a block diagram illustrating a functional concept of a configuration of a multidimensional database management device according to Embodiment 1. FIG. It is a figure which shows notionally the data structure example of MDB. It is a figure which shows the example of comprehensive item information. It is a figure which shows the example of recommendation information. It is a figure which shows the example of no recommendation information. It is a block diagram which illustrates the structure of a client apparatus functionally. It is a flowchart of the whole data analysis process. It is a flowchart of the selection process of analysis object data. It is a figure which shows the example of a selection screen of the data of an analysis classification axis | shaft. It is a figure which shows the example of a selection screen of the data of an analysis classification axis | shaft. It is a figure which shows the example of a selection screen of the data of a chemical | medical agent axis | shaft. It is a figure which shows the example of a selection screen of the data of a regional axis. It is a flowchart of the calculation output process of analysis object data. It is a figure which shows the example of an output screen of a use performance analysis. It is a figure which shows the example of an output screen of expiration loss analysis. It is a block diagram which illustrates functionally the structure of the multidimensional database management apparatus which concerns on Embodiment 2. FIG. It is a figure which shows notionally the data structure example of MDB. It is a figure which shows notionally the data structure example of prescription history DB. It is a flowchart of the selection process of analysis object data. It is a figure which shows the example of a selection screen of the data of a patient axis. It is a figure which shows the example of a selection screen of the data of a chemical | medical agent axis | shaft. It is a figure which shows the example of a registration screen.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1,100 Multidimensional database management apparatus 2 Client apparatus 3 Network 11, 21, 101 Input / output control part 12, 24, 102 External storage part 12a, 102a RDB
12b, 102b MDB
12c Reference information 13, 25, 103 Main storage unit 14, 104 Medium reading unit 14a, 104a Recording medium 15, 26, 105 Control unit 15a, 105a MDB basic management unit 15b, 105b Analysis target data extraction unit 15c Reference information update unit 15d , 105e Analysis calculation unit 105c Reference information generation unit 105d Prescription history information update unit 16, 27, 106 Bus 22 Input device 23 Output device 26a Web browser 26b MDB operation unit

Claims (30)

A multi-dimensional database management apparatus for performing processing on a multi-dimensional database configured by multi-dimensionalizing hierarchical data,
Multidimensional database storage means for storing the multidimensional database;
Selection for accepting input of selection information for specifying, as analysis target data, a plurality of data belonging to the same hierarchy and / or different hierarchies from among the data belonging to at least one of the multi-dimensions Information input means;
After the selection information is received by the selection information input means, the multidimensional database in which the plurality of pieces of analysis target data specified by the received selection information are stored in the multidimensional database storage means Analysis target data extraction means for extracting from among,
Data output means for outputting the plurality of analysis target data extracted by the analysis target data extraction means in a predetermined format;
A multidimensional database management apparatus comprising: Reference information storage means for storing reference information for reference when simultaneously selecting a plurality of data belonging to the same hierarchy and / or different hierarchies;
Reference information output means for presenting the reference information stored in the reference information storage means to the user when receiving the selection information input by the selection information input means;
The multidimensional database management device according to claim 1, comprising: Reference information input means for receiving input of the reference information;
After the reference information is received by the reference information input means, based on the received reference information, reference information update means for updating the reference information stored in the reference information storage means,
The multidimensional database management device according to claim 2, comprising: Reference information generating means for generating the reference information based on the multidimensional database stored in the multidimensional database storage means;
The multidimensional database management device according to claim 1, comprising: The reference information includes comprehensive item information relating to a comprehensive item for comprehensively selecting a plurality of data belonging to the same layer and / or different layers;
The multidimensional database management apparatus according to any one of claims 2 to 4, wherein The reference information includes recommendation information regarding data recommended to be selected as a plurality of data belonging to the same hierarchy and / or different hierarchy,
The multidimensional database management apparatus according to any one of claims 2 to 5, wherein The reference information includes non-recommended information regarding data that is not recommended to be selected as a plurality of data belonging to the same hierarchy and / or different hierarchies;
The multidimensional database management device according to any one of claims 2 to 6, wherein After the selection information is received by the selection information input unit, an analysis calculation unit that performs a predetermined calculation on the plurality of analysis target data specified by the received selection information;
The multidimensional database management apparatus according to any one of claims 1 to 7, further comprising: The analysis calculation means performs subtraction for subtracting the analysis target data belonging to the lower hierarchy from the analysis target data belonging to the upper hierarchy among the plurality of analysis target data,
The multidimensional database management device according to claim 8. The data includes purchase amount, effective use amount, use loss amount, and inventory target amount for a specific product,
The analysis calculation means calculates the actual inventory amount by subtracting the effective usage amount and the usage loss amount from the purchase amount,
The data output means displays the actual inventory quantity and the target inventory quantity;
The multidimensional database management apparatus according to claim 8 or 9, characterized in that: A multi-dimensional database management method for performing processing on a multi-dimensional database configured by multi-dimensionalizing hierarchical data,
Selection for accepting input of selection information for specifying, as analysis target data, a plurality of data belonging to the same hierarchy and / or different hierarchies from among the data belonging to at least one of the multi-dimensions An information input step;
After the selection information is received in the selection information input step, the plurality of analysis target data specified by the received selection information are extracted from the multidimensional database stored in a predetermined storage unit Analysis target data extraction step,
A data output step for outputting the plurality of analysis target data extracted in the analysis target data extraction step in a predetermined format;
A multidimensional database management method comprising: Reference information that is stored in a predetermined storage means when receiving input of the selection information in the selection information input step and serves as a reference when simultaneously selecting a plurality of data belonging to the same hierarchy and / or different hierarchies A reference information output step for presenting to the user,
The multidimensional database management method according to claim 11, further comprising: A reference information input step for receiving input of the reference information;
After the reference information is received in the reference information input step, based on the received reference information, a reference information update step of updating the reference information stored in the predetermined storage unit;
The multidimensional database management method according to claim 12, further comprising: A reference information generating step for generating the reference information based on the multidimensional database;
The multidimensional database management method according to claim 11, further comprising: The reference information includes comprehensive item information relating to a comprehensive item for comprehensively selecting a plurality of data belonging to the same layer and / or different layers;
The multidimensional database management method according to any one of claims 12 to 14, wherein: The reference information includes recommendation information regarding data recommended to be selected as a plurality of data belonging to the same hierarchy and / or different hierarchy,
The multidimensional database management method according to any one of claims 12 to 15, wherein: The reference information includes non-recommended information regarding data that is not recommended to be selected as a plurality of data belonging to the same hierarchy and / or different hierarchies;
The multidimensional database management method according to any one of claims 12 to 16, wherein: After the selection information is received in the selection information input step, an analysis calculation step for performing a predetermined calculation on the plurality of analysis target data specified by the received selection information;
The multidimensional database management method according to any one of claims 11 to 17, further comprising: Performing the subtraction for subtracting the analysis target data belonging to the lower hierarchy from the analysis target data belonging to the upper hierarchy among the plurality of analysis target data in the analysis calculation step;
The multidimensional database management method according to claim 18. The data includes purchase amount, effective use amount, use loss amount, and inventory target amount for a specific product,
In the analysis calculation step, by subtracting the effective usage amount and the usage loss amount from the purchase amount, an actual inventory amount is calculated,
In the data output step, displaying the actual inventory quantity and the target inventory quantity;
The multidimensional database management method according to claim 18 or 19, characterized in that: A multi-dimensional database management program for causing a computer to execute a method for processing a multi-dimensional database configured by multi-dimensionalizing hierarchized data, the method comprising:
Selection for accepting input of selection information for specifying, as analysis target data, a plurality of data belonging to the same hierarchy and / or different hierarchies from among the data belonging to at least one of the multi-dimensions An information input step;
After the selection information is received in the selection information input step, the plurality of analysis target data specified by the received selection information are extracted from the multidimensional database stored in a predetermined storage unit Analysis target data extraction step,
A data output step for outputting the plurality of analysis target data extracted in the analysis target data extraction step in a predetermined format;
A multidimensional database management program characterized by including: The method
A reference information output step of presenting the reference information stored in a predetermined storage means to the user when receiving the input of the selection information in the selection information input step;
The multidimensional database management program according to claim 21, further comprising: The method
A reference information input step for receiving input of the reference information;
After the reference information is received in the reference information input step, a reference information update step of updating the reference information stored in the predetermined storage unit;
The multidimensional database management program according to claim 22, comprising: The method
A reference information generating step for generating the reference information based on the multidimensional database;
The multidimensional database management program according to claim 21, further comprising: The reference information includes comprehensive item information relating to a comprehensive item for comprehensively selecting a plurality of data belonging to the same layer and / or different layers;
The multidimensional database management program according to any one of claims 22 to 24. The reference information includes recommendation information regarding data recommended to be selected as a plurality of data belonging to the same hierarchy and / or different hierarchy,
The multidimensional database management program according to any one of claims 22 to 25, wherein: The reference information includes non-recommended information regarding data that is not recommended to be selected as a plurality of data belonging to the same hierarchy and / or different hierarchies;
The multidimensional database management program according to any one of claims 22 to 26, wherein: The method
After the selection information is received in the selection information input step, an analysis calculation step for performing a predetermined calculation on the plurality of analysis target data specified by the received selection information,
The multidimensional database management program according to any one of claims 21 to 27, characterized by comprising: Performing the subtraction for subtracting the analysis target data belonging to the lower hierarchy from the analysis target data belonging to the upper hierarchy among the plurality of analysis target data in the analysis calculation step;
29. The multidimensional database management program according to claim 28. The data includes purchase amount, effective use amount, use loss amount, and inventory target amount for a specific product,
In the analysis calculation step, by subtracting the effective usage amount and the usage loss amount from the purchase amount, an actual inventory amount is calculated,
In the data output step, displaying the actual inventory quantity and the target inventory quantity;
30. The multidimensional database management program according to claim 28 or 29.

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