CN114860819A

CN114860819A - Method, device, equipment and storage medium for constructing business intelligent system

Info

Publication number: CN114860819A
Application number: CN202210776122.4A
Authority: CN
Inventors: 吴旺石; 杨晓轩; 郝明; 匡前义; 吴华夫; 阮君华
Original assignee: Guangzhou Smart Software Co ltd
Current assignee: Guangzhou Smart Software Co ltd
Priority date: 2022-07-04
Filing date: 2022-07-04
Publication date: 2022-08-05

Abstract

The embodiment of the specification provides a construction method, a construction device, a construction equipment and a storage medium of a business intelligence system. The method comprises the following steps: acquiring a service demand report comprising a plurality of report items and attribute data of the report items; generating an initial topic model comprising a fact table and a dimension table with an incidence relation based on the report items and the attribute data of the report items; and extracting the business data corresponding to the fact table and the dimension table from a business database so as to synchronize the business data into the initial topic model to form the business intelligent system. The initial theme model is determined through the report items of the business requirement report, and the business data is extracted based on the initial theme model to form the business intelligent system, so that the conformity of the business intelligent system and the user requirements can be improved to a certain extent.

Description

Method, device, equipment and storage medium for constructing business intelligent system

Technical Field

The embodiments in this specification relate to the field of computer data processing, and in particular, to a method, an apparatus, a device, and a storage medium for constructing a business intelligence system.

Background

Business Intelligence, also known as Business Intelligence, is Business Intelligence in english, abbreviated as BI. Business intelligence is generally understood as a tool that translates data existing in an enterprise into knowledge, helping the enterprise make informed business decisions. The data includes orders, inventory, transaction accounts, customer and supplier data from the business and competitors of the enterprise, and various data from other external environments of the enterprise. Business intelligent BI systems generally consist of Data Warehouse (DW), On-Line Analytical Processing (OLAP, also known as multidimensional analysis), user queries and Reports (Query & Reports), and the like. The key of business intelligence is to extract useful data from many data from different enterprise operating systems and clean the data to ensure the correctness of the data, then merge the useful data into an enterprise-level data warehouse through Extraction (Extraction), Transformation (Transformation) and loading (Load), namely ETL (extract Load) processes, so as to obtain a global view of the enterprise data, analyze and process the global view on the basis by using proper query and analysis tools, data mining tools, OLAP tools and the like, at this time, information becomes the knowledge for assisting decision making, and finally, the knowledge is presented to a manager to provide support for the decision making process of the manager.

At present, the traditional business intelligence system based on data warehouse route is constructed by firstly using an ETL tool to extract business data from a business database to a source layer and then constructing a corresponding topic model. And after the theme model is constructed, forming a data warehouse, developing a report tool based on the data warehouse, and finally constructing and finishing the business intelligent system.

A business intelligent system is constructed based on all business data, and the business intelligent system can contain data with relatively low user demand degree to a certain extent, so that the technical problem that the fit degree between the business intelligent system and a user is not high is caused.

Disclosure of Invention

Embodiments in the present specification provide a method, an apparatus, a device and a storage medium for constructing a business intelligence system, so as to improve the degree of engagement of the business intelligence system with user requirements to some extent.

One embodiment of the present specification provides a method of constructing a business intelligence system, comprising: acquiring a service demand report comprising a plurality of report items and attribute data of the report items; generating an initial topic model comprising a fact table and a dimension table with an incidence relation based on the report items and the attribute data of the report items; and extracting the business data corresponding to the fact table and the dimension table from a business database so as to synchronize the business data to the initial theme model to form the business intelligent system.

One embodiment of the present specification provides a construction apparatus of a business intelligence system, including: the report acquisition module is used for acquiring a service demand report comprising a plurality of report items and attribute data of the report items; the model generation module is used for generating an initial theme model comprising a fact table and a dimension table with an incidence relation based on the report item and the attribute data of the report item; and the data extraction module is used for extracting the business data corresponding to the fact table and the dimension table from a business database so as to synchronize the business data into the initial theme model to form the business intelligent system.

In the embodiments provided in this specification, the initial topic model is determined by the report items of the business requirement report, and the business intelligent system is formed by extracting the business data based on the initial topic model, so that the engagement degree between the business intelligent system and the user requirement can be improved to a certain extent.

Drawings

Fig. 1 is a schematic architecture diagram of a business intelligence system building system provided in one embodiment of the present specification.

FIG. 2 is a schematic diagram of a business intelligence system build method provided in one embodiment of the present description.

FIG. 3 is a schematic diagram of an interface for a configuration file for a report entry provided in one embodiment of the present description.

FIG. 4a is a schematic diagram of an interface to a configuration file of a fact table provided in one embodiment of the present description.

Fig. 4b is a schematic diagram of an interface of a configuration file of a dimension table according to an embodiment of the present specification.

Fig. 5 is a schematic diagram of an interface of a configuration file of an association relationship between a fact table and a dimension table according to an embodiment of the present specification.

Fig. 6 is a schematic diagram illustrating a flow of a method for constructing a business intelligence system according to an embodiment of the present disclosure.

Fig. 7 is a schematic diagram of a building apparatus of a business intelligence system provided in one embodiment of the present description.

FIG. 8 is a schematic diagram of a computer device provided in one embodiment of the present description.

Detailed Description

SUMMARY

In the related art, the business intelligence system needs to build the theme model after extracting the business data value to the source layer. After the topic model is built, the reporting tool is further developed. And the business intelligent system can be formed and completed only after the report tool is developed and completed. However, the process of extracting business data from the business database and the process of developing a reporting tool often take a long time, which results in a long time for the construction process of the whole business intelligence system.

Therefore, there is a need to provide a method for constructing a business intelligence system, which can generate an initial topic model through a business report, extract corresponding business data according to the initial topic model, and simultaneously perform business report development to solve the technical problem that it takes a long time to construct a business intelligence system.

Example of a scene

Referring to fig. 1 and fig. 2, an example of an application scenario of a method for constructing a business intelligence system is provided in this specification.

The user can collect the business demand report meeting the demand according to the business demand and upload the report to the construction system of the business intelligent system. Specifically, the business requirement report may be a report capable of displaying sales data. The construction system of the business intelligent system can extract the report items of the business demand report. According to the name of the entry, the building system of the business intelligence system can generate a configuration file of the attribute data of the entry and provide a user entry configuration page. The user may download a configuration file for the attribute data in a report item configuration interface. And then, in the configuration file, according to a plurality of attributes corresponding to each report item, sequentially determining the values of the attributes of the report items.

Referring to fig. 3, a user may configure information such as a service attribute of each entry, a category of the entry, whether to put in storage, and a remark through a configuration control. Then, the construction system of the business intelligence system can screen the report items according to the report item attributes, and extract the report items for forming the fact table and the dimension table.

Next, the build system of the business intelligence system may provide the user with a configuration file for the fact table with respect to entries that form the fact table. Referring to fig. 4a, in the configuration interface of the configuration file of the fact table, the construction system of the business intelligence system can automatically generate part of the information to form the configuration file. The user may make certain modifications based on the configuration interface he generates. Accordingly, the build system of the business intelligence system can provide the user with a configuration file for the dimension table for the entry to form the dimension table, and the configuration interface for the configuration file for the dimension table can be seen in FIG. 4 b.

After determining that the fact table and the dimension table are completed, the construction system of the business intelligence system can generate a configuration file of the association relationship between the fact table and the dimension table for determining the association relationship between the fact table and the dimension table. Specifically, please refer to fig. 5 for an interface of the configuration file of the association relationship. Wherein, each column can correspond to the information of the dimension table, and each row can correspond to the information of the fact table. The user can input the identifier "√" in the table corresponding to the main key of the dimension table and the main key of the fact table, which indicates that the fact table and the dimension table have an association relationship, and can complete the configuration of the configuration file of the association relationship. The building system of the business intelligence system, upon receiving the configuration of the configuration file of the association relationship, may form the initial topic model and may generate some virtual data through a stochastic algorithm. Then, the construction system of the business intelligent system can also extract the business data corresponding to the fact table and the dimension table of the initial topic model from the business system through the ETL tool and synchronize the business data to the initial topic model. During the process of extracting business data in the business database through the ETL tool, developers can also develop report applications through the structure of the initial topic model and part of virtual data, so as to shorten the construction period of the business intelligence system. Specifically, the developer may analyze and process the virtual data based on the initial topic model using a suitable query and analysis tool, data mining tool, OLAP tool, etc. to provide a decision-making-assisted analysis interface for the user.

System architecture

Referring to fig. 1, the present specification provides a system for constructing a business intelligence system. The building system of the business intelligence system can comprise a client and a server. The client may be configured to receive configuration information of a user to determine fact tables, dimension tables, and associations between the fact tables and the dimension tables of the topic model included in the business intelligence system. The server may be used to create the business intelligence system. In some embodiments, the build system of the business intelligence system can further include a plurality of servers deployed with the business database. Business data can be extracted from the business database and synchronized to the topic model.

The client may be an electronic device with network access capabilities. Specifically, for example, the client may be a desktop computer, a tablet computer, a notebook computer, a smart phone, a digital assistant, a smart wearable device, a shopping guide terminal, a television, a smart speaker, a microphone, and the like. Wherein, wearable equipment of intelligence includes but not limited to intelligent bracelet, intelligent wrist-watch, intelligent glasses, intelligent helmet, intelligent necklace etc.. Alternatively, the client may be software capable of running in the electronic device. The server may be an electronic device having a certain arithmetic processing capability. Which may have a network communication module, a processor, memory, etc. Of course, the server may also refer to software running in the electronic device. The server may also be a distributed server, which may be a system with multiple processors, memory, network communication modules, etc. operating in coordination. Alternatively, the server may also be a server cluster formed by several servers. Or, with the development of scientific technology, the server can also be a new technical means capable of realizing the corresponding functions of the specification implementation mode. For example, it may be a new form of "server" implemented based on quantum computing.

Example methods

Referring to fig. 6, one embodiment of the present disclosure provides a method for constructing a business intelligence system. The construction method of the business intelligence system can be applied to a server. The method of constructing the business intelligence system may include the following steps.

Step S110: the method comprises the steps of obtaining a service demand report including a plurality of report items and attribute data of the report items.

In some cases, a business intelligence system is constructed by extracting business data from a business database to a source layer, and the construction may be performed after all the business data are extracted to the source layer. This makes the construction process of a business intelligence system take a long time. In addition, for some users, the analysis is not required to be performed on all data in the service database. Therefore, extracting all business data to the posting layer and building the topic model on the basis of the business data may increase the building time of the business intelligence system. Therefore, the initial topic model can be constructed by acquiring the business requirement report so as to further construct the business intelligent system. And moreover, the business intelligent system is constructed through the report items of the business demand report, and the engagement degree of the business intelligent system and the user demand can also be improved to a certain extent.

In this embodiment, the business requirement report may represent a requirement report meeting the business requirement of the user. The business requirement report may include a plurality of report items. The entry may be used to signal the service data. Specifically, for example, the business requirement report may be created by an EXCEL form. Each field in the EXCEL form in which the service data is recorded may be used as the entry. Of course, the business demand report may also be a business report stored in a database, and a field in the database, in which the business data corresponding to the business report is stored, may be used as a report entry of the business report.

Specifically, for example, the business requirement report may be a sales record table. The sales record table may include information such as name of the clerk, sales amount, sales volume, and growth on par. The name of the salesman, the sales amount, the sales volume and the comparable growth amount can be used as the entry.

In this embodiment, the entry may have corresponding attribute data indicating an attribute of the entry. The attribute data of the entry may be used to represent at least one entry. The attributes of the entry may be used to determine the entry that can constitute the initial topic model. Specifically, the attributes of the entry may include, but are not limited to, a name of the entry, a service attribute, a category of the entry, whether to put in storage, a remark, and the like. The service attribute corresponding to the entry may be set according to the service requirement. The field category may be used to indicate whether the data of the entry record is metric data or dimensional data. Whether to binning may indicate whether the initial topic model may be used to build.

The attribute data of the entry may be obtained according to user configuration. In some embodiments, the attribute data may also be generated by the server by analyzing the entry. Specifically, the fact table or the dimension table to which the entry belongs can be determined by analyzing the name of the entry through a natural language processing technology. Specifically, for example, for the entry items with names "sales amount" and "sales volume", the similarity between the names can be judged through word vector, named entity recognition, and other techniques to determine whether the entry item belongs to a fact table or a dimension table. Of course, the fact table and the dimension table to which the entry belongs may be determined by searching in a pre-configured dictionary.

In some embodiments, by analyzing the data recorded in the report entry in the service demand report, it can be determined that the field corresponding to the report entry belongs to the fact table or the dimension table. Specifically, for example, for a entry named "sales amount", which may include a plurality of numerical data, the number of the numerical data may be different from each other, the same number of the numerical data is smaller, or a larger number of the numerical data is included, and it may be inferred that the field corresponding to the entry belongs to the fact table. Of course, the statistical analysis can also be performed by reporting the item name. In some embodiments, the entry recording the atomic index may be determined by analyzing the relationship between data corresponding to entries of the fact table, i.e., other entries recording non-atomic indices may be determined by the determination of the entry. Specifically, for example, the proportional increase amount of sales can be calculated based on the sales and the corresponding date. For the case that some report items take a limited number of character string data, it can be inferred that the fields corresponding to the report items belong to the dimension table.

In this embodiment, the method for obtaining a business requirement report including a plurality of report items may be a construction system that receives a business requirement report provided by a user and imports the business requirement report into a business intelligent system. Specifically, an acquisition page of the business requirement report can be provided. The acquisition page comprises a control for uploading the business requirement report. And under the condition that the control is triggered, importing a business requirement report. A build system of a business intelligence system can identify entry items of the business demand report and determine attribute data for the entry items. Of course, the method for obtaining the service requirement report including the plurality of report items may also be a configuration interface provided for the user service requirement report, and the user may configure the service requirement report in the page. The service requirement report configured by the user may not include data of a specific corresponding report item.

Step S120: and generating an initial theme model comprising a fact table and a dimension table with incidence relations based on the report items and the attribute data of the report items.

In some cases, an initial topic model may be generated based on attribute data of the entry. On the basis, corresponding business data can be extracted from a business database and synchronized into the initial topic model to generate a target topic model, so that the business intelligent system is finally constructed.

In this embodiment, the fact table may include an index field formed by a report entry for recording data representing a business event; the dimension table includes dimension fields formed from entry sheets that describe characteristics of data recorded by the fact table. The fact table may be a central table in a data warehouse structure with metrics and keys that link the fact and dimension tables. A dimension table is a collection of dimension attributes that can represent information for a particular dimension of data.

In some embodiments, the attribute data of the entry may include an association between the entry and the entry. The association relationship may include that a plurality of entry items belong to a fact table or that a plurality of entry items belong to a dimension table. Of course, the association relationship may also include an association relationship between a plurality of entries belonging to a fact table and corresponding entries belonging to a dimension table.

Specifically, for example, the entry items indicating sales and sales volumes may belong to the same fact table. Entry items representing company name and company address may also belong to a dimension table. In addition, a fact table formed from entry items representing sales and sales amounts may have an association relationship with a dimension table formed from a company name and a company address. Accordingly, in the initial topic model, a dimension table formed by representing company names and company addresses may be named a company dimension table. The company dimension table may include a company dimension primary key. A fact table formed of entry sheets representing sales and sales amounts may be named a sales fact table. In the sales fact table, a sales fact primary key may be included. The sales fact primary key and the company dimension primary key may have an associative relationship therebetween. For example, the associative relationship may be a foreign key relationship.

The initial topic model may include a plurality of dimension tables and a plurality of fact tables. The plurality of dimension tables and the plurality of fact tables may have an associative relationship therebetween. The structure of the initial topic model can have a variety of structures. Specifically, a star model, a snowflake model, a constellation model, and the like may be included. Specifically, the initial topic model may only include field identifications of the fact table and the dimension table, and may not include corresponding business data. Of course, in some cases, the initial topic model may also include partial data. Wherein, the data can be the data contained in the business report. Of course, the data may also be virtual data generated according to an algorithm. Wherein the virtual data may have no real meaning.

After the initial theme model is built according to the business demand report, business data can be extracted from the business database, support is provided for the business demand report, development of the business demand report is achieved while business data is extracted, and time for building a business intelligent system is reduced to a certain extent.

The method for generating the initial topic model including the fact table and the dimension table with the association relationship based on the entry and the attribute data of the entry may be that the fact table and the dimension table are respectively constructed based on the attribute data of the entry. Specifically, the report items may be first screened to obtain a report item capable of recording the atomic index. And then generating a plurality of fact tables and dimension tables according to the incidence relation among the report items. Wherein the fact table may include a plurality of indicator fields. The indicator field may correspond to a corresponding entry. The dimension table may include a plurality of dimension fields, the dimension fields corresponding to entry items. Then, according to the association relationship between the fact table and the dimension table, the primary keys in the mutually associated fact table and the primary keys in the dimension table can be associated to generate the initial theme model.

Step S130: and extracting the business data corresponding to the fact table and the dimension table from a business database so as to synchronize the business data into the initial topic model to form the business intelligent system.

In some cases, after the initial topic model is built, corresponding data can be extracted from the business database according to fields included in the initial topic model to form a target topic model. In addition, in the process of extracting data, a corresponding report tool can be developed according to the structure of the initial theme model, so that the report tool and the extracted data can be developed in the same time period, and the time for constructing the business intelligent system is saved.

The service database may be a database in which service data is recorded. Wherein the service database may be a plurality of databases distributed on different servers. Wherein the type of the database may be different. Specifically, the database may be a relational database such as Oracle and MySQL, or a non-relational database such as MongoDB. In addition, the data storage criteria may be different in different databases.

The method for extracting the business data corresponding to the fact table and the dimension table from the business database can be that the data is extracted into a business intelligent system by an ETL data extraction tool. Specifically, the ETL data extraction tool may extract, clean, and convert the data of the business system and load the data into a posting layer included in the business intelligence system. Then, according to the fact table and the fields of the dimension table included in the initial topic model, the business data is extracted from the posting layer to the initial topic model, and the topic model is obtained. Specifically, after the data of the fact table and the dimension table are extracted, a theme model layer of the commercial intelligent system can be constructed. In some embodiments, during the data extraction period, a developer may complete the development of a business reporting tool, the reporting tool may be accessed into a topic model, the business intelligence system may be formed, and the construction time of the business intelligence system may be reduced to some extent, so as to provide construction efficiency.

In some embodiments, the step of obtaining a business requirement report including a plurality of report items and attribute data of the report items includes: receiving the business demand report form comprising a plurality of report forms; providing a report item configuration page corresponding to the report item; the report item configuration page is used for determining attribute data of the report item; and receiving configuration information of the entry configuration page to determine attribute data of the entry.

In some cases, the determination of the initial topic model has a greater impact on the performance of the business intelligence system. Therefore, the fact table, dimension table and their association of the initial topic model have a large impact on the performance of the business intelligence system. User confirmation information may also be required to avoid inference errors to some extent during the automatic generation of fact and dimension tables by the server. Therefore, the report item configuration page of the report item can be provided for the user, so that the attribute data of the report item can be determined more accurately. In addition, in this embodiment, the user may only need to configure at least part of the attribute data of the report item, and the user does not need to directly configure the fact table and the dimension table, which may reduce the technical threshold of the configurator to a certain extent.

The entry configuration page may be used to provide a user with attribute data for determining an entry. Specifically, the entry configuration page may be a web page. A plurality of controls arranged in a matrix may be provided in the web page. Wherein each control can be used to configure an attribute of a report entry. Specifically, the web page may be displayed with a table. Each column of the table may represent an attribute. Each row may represent a report entry. Each form unit may have a pull-down option control for configuring the attributes of the entry. For example, an attribute of an entry may be an entry category. The categories of entry may include dimensions and metrics. By pulling down the option control, the category of the corresponding entry item can be selected. Receiving configuration information of the entry configuration page, which may be receiving operation information of the web page by a user, to determine attribute data of the entry.

In some embodiments, the entry configuration page may also include a download control and/or an import control. Specifically, the download control may provide a configuration file for the user. The configuration file may be an EXCEL file or a WORD file. Correspondingly, the method for receiving the configuration information of the report item configuration page to determine the attribute data of the report item may be that after the user configures the attribute data of the report item in the configuration file, the attribute data of the report item is imported into the construction system of the business intelligent system through the import control to determine the attribute data of the report item.

In some embodiments, the step of generating an initial topic model including associated fact and dimension tables based on the entry and attribute data for the entry includes: determining at least one fact table and a report table for generating the fact table, and at least one dimension table and a report table for generating the dimension table according to the attribute data of the report table; providing a relation configuration page for configuring the incidence relation of the fact table and the dimension table; and receiving configuration information of the relationship configuration page to obtain an association relationship between the fact table and the dimension table so as to form the initial theme model.

In some cases, generating an initial topic model that includes associated fact and dimension tables may include determining the fact and dimension tables and the associations between them before building the initial topic model. The method for determining the association relationship between the fact table and the dimension table can avoid the performance reduction of the initial topic model caused by the automatic generation of the server to a certain extent through the configuration relationship of the user.

The method for determining at least one fact table and the entry table used for generating the fact table according to the attribute data of the entry table, and at least one dimension table and the entry table used for generating the dimension table may be to determine the category corresponding to the entry table according to the attribute representing the entry table category in the attribute data. For example, a entry having a entry category of "pointer" may be determined as the entry used to generate the fact table. In addition, a report item whose report item category is "dimension" may be determined as a report item for generating the dimension table. For a entry of the category "targets," the fact table to which the entry belongs may be determined. Specifically, the fact table may be determined according to the attribute configured in the attribute data to represent the fact table. Of course, the entry may also be divided into multiple groups by a clustering method according to multiple attributes of the entry. Wherein, each group of entry may belong to the same fact table. In this process, the report items may also be screened. For example, duplicate entry terms may be removed. The removal data can be the report item obtained by calculating the data of other report items. For entry items with a category of "dimension," the fact table may be determined according to attributes configured in the attribute data that represent the dimension table. Of course, the report item belonging to a dimension table may also be analyzed according to a plurality of attributes of the report item to generate the dimension table.

In some embodiments, after the entry items are divided into entry items belonging to the fact table and entry items belonging to the dimension table, a configuration interface for configuring the fact table and the dimension table may also be provided for the user. For example, the name of the fact table or dimension table to which the configuration entry belongs may be used. Correspondingly, the construction system of the business intelligent system can generate a corresponding fact table or dimension table according to the entry corresponding to the same fact table or dimension table name.

The method for providing the relationship configuration page for configuring the association relationship between the fact table and the dimension table may be to provide a configuration file. The configuration file may be a file that supports multiple formats. For example, the format may be WOED or EXCEL. In particular, the configuration file may provide a configuration table. Each column of the table may correspond to a dimension table, and each row of the table may correspond to a fact table. The user can input a corresponding confirmation mark in the form, such as hooking can be performed. The fact table and the dimension table corresponding to the table with the determined identification may have an association relationship. Of course, the method for providing the relationship configuration page for configuring the association relationship between the fact table and the dimension table may also be to provide a configuration page of a web page, a user may perform an operation on the configuration page, and the building system of the business intelligence system may determine the association relationship between the fact table and the dimension table after receiving the operation. Specifically, a table may also be provided in the web page, each column of the table may correspond to a dimension table, each row of the table may correspond to a fact table, and the association relationship between the fact table and the dimension table is determined by receiving a web page operation of a user.

The method for receiving the configuration information of the relationship configuration page to obtain the association relationship between the fact table and the dimension table to form the initial topic model may be that after receiving the configuration information, the construction system of the business intelligent system may search and determine the identification of the fact table and the dimension table corresponding to the identification to determine the fact table and the dimension table having the association relationship. The fact table may be constructed by determining the fact table and generating the fact table report entries. Each entry may correspond to an index field in the fact table. Additionally, a fact table primary key may also be built into the fact table. Correspondingly, after the dimension table and the report items used for generating the dimension table are determined, the dimension table can be constructed. Each entry may correspond to a dimension field in the dimension table. The dimension table may also include a dimension table main key. According to the relationship, the fact table with the association relationship and the main key of the dimension table can be associated, so that the initial theme model can be generated.

In some embodiments, the step of generating an initial topic model including associated fact and dimension tables based on the entry and attribute data for the entry includes: determining a report item for recording atomic index data in the report items included in the service demand report as an index item; the atomic index data can be used for calculating non-atomic index data recorded by the report item; determining at least one fact table including an index field based on the index item; wherein the metric field is formed from the metric item; an initial topic model is generated that includes associated fact tables and dimension tables in accordance with the fact tables and attribute data of the entry.

In some cases, the entry item recorded with the index data included in the business demand report may be redundant. To ensure performance of the initial topic model, some unnecessary entry items may be culled to generate a fact table.

The atomic index data may be reference data recorded in a report entry and available for statistical analysis. Based on the reference data, the data recorded by other report items can be calculated. Specifically, for example, the sales increase rate may be calculated from sales data at different times. Wherein the sales data can be used as the reference data. The sales increase rate can be calculated from the sales data. Correspondingly, the entry for recording the atomic index data may be used as an index entry. In some cases, partial data may be mutually converted without participation of other data, and one of the data may be used as reference data. For example, the size of the item is represented by two entry items, respectively. If the unit of one report entry is centimeter and the unit of one report entry is meter, only one of the report entries can be reserved. The fact table can be determined through the index item, and the initial theme model can be constructed according to the incidence relation between the fact table and the dimension table.

The method for determining the report item for recording the atomic index data in the report items included in the service demand report may be based on attribute data corresponding to the report item. Specifically, the attribute of the entry item may include an attribute representing the pointer item. According to the attribute data, an index item can be screened out from the report items. Further, a fact table may be determined according to the index item, thereby generating an initial topic model.

In some embodiments, a report item for recording atomic index data is determined in the report items included in the business demand report, and the method for serving as an index item may also sequentially calculate the association relationship between the data of the report items through a computer. For example, for the report items recorded with sales per day and the report items recorded with growth rate per day, the construction system of the business intelligence system may find the corresponding relationship between the report items and the sales by statistics, and then may determine one of the report items as the index item.

In some embodiments, the step of generating an initial topic model including associated fact and dimension tables based on the entry and attribute data for the entry includes: determining a report item used for describing the characteristics of the data recorded by the fact table from report items included in the business demand report as a dimension item; merging the dimension items which represent the same dimension information in the dimension items to obtain a target dimension item; determining at least one dimension table including dimension fields formed according to the target dimension item based on the target dimension item; an initial topic model is generated that includes associated fact tables and dimension tables in accordance with the dimension tables and attribute data of the entry.

In some cases, the entry items recorded with dimensional data included in the business demand report may also be redundant. Correspondingly, some repeated entry items can be combined to generate a dimension table, so that the performance of the initial topic model is improved to a certain extent.

Determining a report item used for describing characteristics of data recorded by the fact table from report items included in the business demand report, wherein the report item can be used as a dimension item according to attribute data corresponding to the report item. The dimension item may be recorded with data representing dimension information. Specifically, for example, if the entry item category of the entry item named "company name" is a dimension, it can be confirmed as a dimension item. Of course, the method for confirming the entry as the dimension entry may also be automatically identified according to the computer.

The method for combining the dimension items representing the same dimension information in the dimension items to obtain the target dimension item can be that one report item of a plurality of report items representing the same dimension information is selected as the dimension item to participate in the construction of the initial topic model. Of course, combining the dimension items representing the same dimension information in the dimension items, or after integrating the information of a plurality of dimension items, generating a target dimension item capable of better representing the dimension information. Specifically, for example, the dimension items may include dimension items named "transmission date", "generation date", and "sales date". The dimension items may come from different business reports but all indicate date information. Therefore, the dimension items can be merged. For example, a target dimension item named "date" may be generated. The granularity of the target dimension item can be the same as the dimension item with the smallest granularity in the dimension items before merging.

After the target dimension table is determined, a corresponding dimension table can be constructed according to the attribute data. Further, the initial topic model can be formed according to the association relationship between the dimension table and the implementation table.

In some embodiments, the method of constructing a business intelligence system may further comprise: and generating virtual data corresponding to the fact table and the dimension table of the initial model according to the initial theme model, and developing a report tool for displaying the business data according to the initial theme model with the virtual data.

In some cases, the business requirement report may not have corresponding data, or only have a portion of the data. Therefore, the fields included in the fact table and the dimension table in the initial topic model generated based on the business requirement report have no corresponding data or may lack part of the data. In order to not increase the difficulty of report tool developers to a certain extent and to be compatible with more tools, an initial theme model of the virtual data storage can be generated.

The virtual data may be data that does not correspond to a real service. Specifically, the virtual data may be data generated based on an algorithm and having no practical meaning. For example, it may be generated by a random algorithm. Alternatively, the virtual data may be data calculated based on a small portion of the data. In some embodiments, the virtual data may also be historical business data, i.e., a portion of the historical data is extracted to fill the initial topic model. Through the virtual data, the development of a report tool can be supported. For example, the virtual data may be used in a test reporting tool. In some embodiments, a reporting tool may also be developed based directly on the initial topic model without using the virtual data.

In some embodiments, the method of constructing a business intelligence system may further comprise: generating a virtual wide table according to the incidence relation between the fact table and the dimension table included in the initial theme model; wherein the virtual wide table comprises at least one group of associated fact tables and dimension tables comprising an index field and a dimension field.

In some cases, iteratively searching through associations to search for data may result in a reduced rate of data reads. Therefore, performance can be improved by generating a wide table.

The virtual wide table may represent a wide table through the initial topic model. The virtual broad table may include no data or only a portion of the data that the topic model has. Wherein the partial data included in the topic model may be the virtual data. The virtual wide table can be obtained by combining the fact table and the dimension table. Specifically, the index field and the dimension field in the fact table and the dimension table having the association relationship may have a corresponding relationship, respectively. By merging based on the primary key, the virtual wide table can be formed to improve the efficiency of data reading and writing to a certain extent. In some embodiments, the fields of the virtual wide table may have some field redundancy.

Example apparatus, electronic device, storage medium, and software

Referring to fig. 7, an embodiment of the present disclosure further provides a device for constructing a business intelligence system. The building device of the business intelligent system can comprise a report acquisition module, a model generation module and a data extraction module.

The report acquisition module is used for acquiring a service demand report comprising a plurality of report items and attribute data of the report items.

And the model generation module is used for generating an initial theme model comprising a fact table and a dimension table with an incidence relation based on the report item and the attribute data of the report item.

And the data extraction module is used for extracting the business data corresponding to the fact table and the dimension table from a business database so as to synchronize the business data into the initial theme model to form the business intelligent system.

The specific functions and effects achieved by the construction device of the business intelligence system can be explained by referring to other embodiments in this specification, and are not described herein again. The various modules in the building means of the business intelligence system can be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

Referring to fig. 8, an embodiment of the present specification provides an electronic device, which may include: a processor; a memory for storing the processor-executable instructions; the processor is configured to execute the method in the foregoing embodiments.

The present specification also provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a computer, causes the computer to execute the method for constructing a business intelligence system in any one of the above embodiments.

The present specification also provides a computer program product containing instructions, and the instructions can be executed by a computer, so that the computer can execute the construction method of the business intelligence system in any one of the above embodiments.

It should be understood that the specific examples are included merely for purposes of illustrating the embodiments of the disclosure and are not intended to limit the scope of the disclosure.

It should be understood that, in the various embodiments of the present specification, the sequence numbers of the processes do not mean the execution sequence, and the execution sequence of the processes should be determined by the functions and the inherent logic, and should not limit the implementation process of the embodiments of the present specification.

It is to be understood that the various embodiments described in the present specification may be implemented individually or in combination, and the embodiments in the present specification are not limited thereto.

Unless otherwise defined, all technical and scientific terms used in the embodiments of the present specification have the same meaning as commonly understood by one of ordinary skill in the art to which this specification belongs. The terminology used in the description is for the purpose of describing particular embodiments only and is not intended to limit the scope of the description. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. As used in the specification embodiments and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It is understood that the processor of the embodiments of the present description may be an integrated circuit chip having signal processing capability. In implementation, the steps of the above method embodiments may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The processor may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component. The various methods, steps, and logic blocks disclosed in the embodiments of the present specification may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present specification may be embodied directly in a hardware decoding processor, or in a combination of hardware and software modules in the decoding processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, etc. as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

It will be appreciated that the memory in the implementations of the specification can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EEPROM (EEPROM), or a flash memory. The volatile memory may be Random Access Memory (RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present specification.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in this specification, it should be understood that the disclosed system, apparatus, and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is merely a logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

In addition, functional units in the embodiments of the present specification may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present specification may be substantially or partially embodied in the form of a software product stored in a storage medium, and include several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the methods described in the embodiments of the present specification. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above description is only for the specific embodiments of the present disclosure, but the scope of the present disclosure is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope disclosed in the present disclosure, and all the changes or substitutions should be covered within the scope of the present disclosure. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method of constructing a business intelligence system, comprising:

acquiring a service demand report comprising a plurality of report items and attribute data of the report items;

generating an initial topic model comprising a fact table and a dimension table with an incidence relation based on the report items and the attribute data of the report items;

and extracting the business data corresponding to the fact table and the dimension table from a business database so as to synchronize the business data into the initial topic model to form the business intelligent system.

2. The method of claim 1, wherein the step of obtaining a business requirement report including a plurality of report items and attribute data of the report items comprises:

receiving the business demand report form comprising a plurality of report forms;

providing a report item configuration page corresponding to the report item; the report item configuration page is used for determining attribute data of the report item;

and receiving configuration information of the entry configuration page to determine attribute data of the entry.

3. The method of claim 1, wherein generating an initial topic model including associated fact and dimension tables based on the entry and attribute data for the entry comprises:

determining at least one fact table and a report table for generating the fact table, and at least one dimension table and a report table for generating the dimension table according to the attribute data of the report table;

providing a relation configuration page for configuring the incidence relation of the fact table and the dimension table;

and receiving configuration information of the relationship configuration page to obtain an association relationship between the fact table and the dimension table so as to form the initial theme model.

4. The method of claim 1, wherein generating an initial topic model including associated fact and dimension tables based on the entry and attribute data for the entry comprises:

determining a report item for recording atomic index data in the report items included in the service demand report as an index item; the atomic index data can be used for calculating non-atomic index data recorded by the report item;

determining at least one fact table including an index field based on the index item; wherein the metric field is formed from the metric item;

an initial topic model is generated that includes associated fact tables and dimension tables in accordance with the fact tables and attribute data of the entry.

5. The method of claim 1, wherein generating an initial topic model including associated fact and dimension tables based on the entry and attribute data for the entry comprises:

determining a report item used for describing the characteristics of the data recorded by the fact table from report items included in the business demand report as a dimension item;

merging the dimension items which represent the same dimension information in the dimension items to obtain a target dimension item;

determining at least one dimension table comprising dimension fields based on the target dimension item; wherein the dimension field is formed from the target dimension item;

an initial topic model is generated that includes associated fact tables and dimension tables in accordance with the dimension tables and attribute data of the entry.

6. The method of claim 1, further comprising:

and generating virtual data corresponding to the fact table and the dimension table of the initial theme model according to the initial theme model, and developing a report tool for displaying business data based on the initial theme model comprising the virtual data.

7. The method of claim 1, further comprising:

generating a virtual wide table according to the incidence relation between the fact table and the dimension table included in the initial theme model; wherein the virtual wide table comprises at least one group of associated fact table and dimension table comprising index field and dimension field.

8. An apparatus for constructing a business intelligence system, comprising:

the report acquisition module is used for acquiring a service demand report comprising a plurality of report items and attribute data of the report items;

the model generation module is used for generating an initial theme model comprising a fact table and a dimension table with an incidence relation based on the report item and the attribute data of the report item;

and the data extraction module is used for extracting the business data corresponding to the fact table and the dimension table from a business database so as to synchronize the business data to the initial theme model to form the business intelligent system.

9. A computer device comprising a memory storing a computer program and a processor implementing the method of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method of any one of claims 1 to 7.