KR20190069106A - Method, apparatus and computer-readable medium of data analysis combine with data groups - Google Patents

Abstract

The present invention relates to a method and an apparatus for analyzing data through a combination of data groups. The method of the present invention which comprises: a step of receiving two or more data groups which are to be analyzed through an external network from two or more independent databases, as to-be-combined data received by a user terminal; a medium data selecting step of extracting sub-data commonly included in received data groups, and selecting at least one medium data which is a combination standard of the data groups; and a result deriving step of analyzing correlation between the data groups with respect to the selected medium data, and deriving to-be-derived result data in accordance with the analyzed correlation. The apparatus of the present invention comprises: a data receiving unit for receiving two or more data groups which are to be analyzed through an external network from two or more independent databases, as to-be-combined data received by a user terminal; a medium data selecting unit for extracting sub-data commonly included in received data groups, and selecting at least one medium data which is a combination standard of the data groups; a result deriving unit of analyzing correlation between the data groups with respect to the selected medium data, and deriving to-be-derived result data in accordance with the analyzed correlation.

Description

[0001] METHOD, APPARATUS AND COMPUTER-READABLE MEDIUM OF DATA ANALYSIS COMBINE WITH DATA GROUPS [0002]

More particularly, the present invention relates to a technique for combining two or more groups of data by utilizing intermediate data without separately editing and transforming data and deriving a result through data analysis .

Recently, due to the development of computers and networks, a large amount of data has been stored and stored in the cloud. Accordingly, a data analysis technique has been disclosed that efficiently analyzes the stored and archived data and provides analysis results to the user.

Meanwhile, Korean Patent Laid-Open No. 10-2016-0100752 (a system and method for efficiently processing and analyzing big data using a column-index data format) arranges data in column units in order to process big data, Generates an index for each dictionary in accordance with the order of the data blocks by classifying the data blocks into at least one or more data blocks according to the size of sorted data, generates IDs for each column in the order of the big data, and performs data processing And the like.

However, in the above-described data analysis method according to the prior art, it is very difficult to determine, based on a certain criterion, whether the data in which the difference exist is small, when the data format or the format overlap is small, It is almost impossible to derive the result. Even when the data are combined, there has been a problem that the time and cost are extremely consumed because new data has to be created in the same format or format by combining data one by one.

In addition, the above-described prior art analyzes only the separated data without performing data combining, and results obtained through data analysis are different for each secured data, and low reliability of the result is also pointed out as a problem .

Accordingly, the present invention can quickly and easily derive results through data analysis by easily combining data groups having completely different data format formats and deriving a correlation between data, without requiring modification and editing of data, regardless of the degree of differentiation of data. And to provide a technology that can be derived from the data.

According to another aspect of the present invention, there is provided a method for analyzing data through a combination of a data group including at least one processor and at least one memory storing instructions executable by the processor, A data receiving step of receiving two or more data groups to be analyzed from two or more databases through an external network; An intermediate data selecting step of extracting sub data commonly included in the received data groups and selecting at least one intermediate data that is a combination criterion of data groups; And analyzing the correlation between the data groups based on the selected mediation data and deriving the result data to be derived according to the analyzed correlation degree.

Meanwhile, a data analysis apparatus for combining data groups includes a data receiving unit for receiving two or more data groups to be analyzed from two or more databases independent of each other through an external network, as data to be combined received by a user terminal; An intermediate data selecting unit for extracting sub data that are commonly included in the received data groups and selecting at least one intermediate data that is a combination criterion of the data groups; And a result extracting unit for analyzing a correlation between data groups on the basis of the selected intermediate data and deriving result data to be derived according to the analyzed correlation.

According to an embodiment of the present invention, data groups having different data formats and formats can be easily combined through intermediate data and correlations between data can be derived without further data modification and editing, There is an effect that can be derived.

Also, according to the embodiment of the present invention, two or more data groups can be analyzed using only one piece of mediation data on one analysis basis, so that there is no limitation on the kinds of data that can be analyzed, and the versatility of data analysis is widened .

Also, according to an embodiment of the present invention, the accuracy of data analysis is improved by combining and analyzing data groups utilizing mediating data obtained from two or more data groups rather than using only independent data, Is improved.

1 is a flow diagram of a method for analyzing data through combining data groups according to an embodiment of the present invention.
FIG. 2 is a block diagram of a data analysis apparatus according to an exemplary embodiment of the present invention. FIG.
3 is an embodiment of data to be combined received at a user terminal according to an embodiment of the present invention;
4 is an embodiment of sub data constituting a data group received by a user terminal in an embodiment of the present invention;
5 illustrates an embodiment in which mediated data is selected from received data according to an embodiment of the present invention.
6 illustrates an embodiment of result data provided in accordance with an embodiment of the present invention.
FIG. 7 is a block diagram for explaining an internal configuration of a computing device according to an embodiment of the present invention; FIG.

In the following, various embodiments and / or aspects are now described with reference to the drawings. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more aspects. However, it will also be appreciated by those of ordinary skill in the art that such aspect (s) may be practiced without these specific details. The following description and the annexed drawings set forth in detail certain illustrative aspects of one or more aspects. It is to be understood, however, that such aspects are illustrative and that some of the various ways of practicing various aspects of the principles of various aspects may be utilized, and that the description set forth is intended to include all such aspects and their equivalents.

As used herein, the terms "an embodiment," "an embodiment," " an embodiment, "" an embodiment ", etc. are intended to indicate that any aspect or design described is better or worse than other aspects or designs. .

It is also to be understood that the term " comprises "and / or" comprising " means that the feature and / or component is present, but does not exclude the presence or addition of one or more other features, components and / It should be understood that it does not.

Also, terms including ordinal numbers such as first, second, etc. may be used to describe various elements, but the elements are not limited to these terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Furthermore, in the embodiments of the present invention, all terms used herein, including technical or scientific terms, unless otherwise defined, are to be understood as being generically understood by one of ordinary skill in the art to which this invention belongs It has the same meaning. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and, unless explicitly defined in the embodiments of the present invention, are intended to mean ideal or overly formal .

The present invention relates to a method of analyzing data by combining data groups, and it relates to a method of analyzing data by combining data groups having completely different data format formats and deriving a correlation between data, There is a purpose in providing the technology that can be.

FIG. 1 is a flowchart illustrating a method of analyzing data by combining data groups according to an exemplary embodiment of the present invention. Referring to FIG.

First, a data receiving step (S1) of receiving two or more data groups to be analyzed through an external network from two or more databases independent of each other may be performed as the data to be combined received by the user terminal.

Meanwhile, the user terminal used in the present invention may include at least a wire / wireless telephone, a tablet PC, a laptop, a personal computer, a smart phone, A personal digital assistant (PDA), and a mobile communication terminal, and may receive data groups from a database connected through an external network, and may perform data analysis through combining data groups of the present invention Any user terminal can be used without limitation.

The database may be understood as a space in which two or more data groups received by two or more independent databases connected to the external network are stored in the database. At least two data groups selected according to the selection input of the user terminal may be stored in the server As will be understood by those skilled in the art.

Meanwhile, the combination target data received by the user terminal in the above step S1 means two or more data groups that the user wants to combine. For example, if the data that the user wants to combine is data of the A public institution and the B financial institution It can be understood that the data group is received from each of the databases of the A public entity and the B financial institution described above.

After performing step S1, an intermediate data selection step S2 for extracting sub data included in the received data groups and selecting at least one intermediate data as a combination criterion of the data groups is performed.

In the meantime, the above-described sub data will be understood as a concept including content information or attribute information constituting each data group. In the embodiment of the present invention, As the intermediate data, at least one sub data which is expected to have a high impact value on the result data among the sub data included in the common data.

In other words, the above-described intermediate data constitutes a data group, and based on the attribute information of the result data to be derived, out of the sub data that are commonly included in two or more data groups, The data can be automatically calculated.

Meanwhile, in another embodiment of the present invention, in the step S2, the sub data included in the data groups received from two or more databases may be extracted and provided to the user terminal. At this time, And selecting at least one sub-data selected by the input means of the user terminal as the mediating data.

That is, as described above, in the present invention, the sub data that is expected to have a high impact value on the result data among the sub data that are commonly included in the data groups may be automatically extracted and selected as the mediation data. However, The user may directly select the intermediate data through the input means of the user terminal among the sub data included in the intermediate data.

In other words, according to the embodiments described above, it is possible to analyze two or more groups of data by using only one piece of mediation data as one analysis standard, so that there is no limitation on the kinds of data that can be analyzed, .

Meanwhile, in step S2, the mediating data selected among the data groups is weighted to the mediating data which is expected to have the highest correlation with the result data to be derived, and the result data is predicted can do.

That is, in one embodiment, a weight can be given to the mediata data expected to have the greatest influence on the result data to be derived, that is, expected to have a high degree of correlation. In this case, A weight may be applied or a weight set by the user through input means of the user terminal may be applied.

After performing step S2, the correlation between the data groups is analyzed on the basis of the mediation data selected by the execution of step S2, and the result derivation step S3 (step S3) of deriving the result data to be derived according to the analyzed correlation degree ) Is performed.

In the step S3 described above, for example, there is data on gender, region, month, and year on the database, and mediating data commonly included in the first data group and the second data group to be combined are gender, Assuming the year and month, the result data can be derived through the following process.

That is, for example, the first data group and the second data group described above can be calculated as gender, region, and year, which are mediating data, and sales of each mediated data can be calculated. Based on the sales data, 1 data group and the second data group, and a correlation analysis of the sales trend.

That is, in analyzing two or more data groups, the present invention can combine two or more data by using mediating data and compare and analyze the two or more data groups. Accordingly, without data editing and editing, The data can be easily combined through the intermediate data and the correlation between the data can be derived so that the result of analyzing data of two or more data groups received from two or more independent databases can be quickly and easily obtained You can expect.

In another embodiment of the present invention, a report providing step (not shown) may be further included in which the generated result data is generated as a report file of a predetermined format and provided to the user terminal after performing step S3.

A report file of a predetermined format (e.g., Excel) generated in the above-described report providing step generates an analysis report based on the result data derived by performing the above-described steps S1 to S3. At this time, In generating the report file, a report file including the prediction model generated from the result data according to the request input of the user terminal may be generated and provided to the user terminal.

On the other hand, the prediction model described above is a prediction model including at least one of a data table, a graph, and a diagram that can be generated using result data. The resultant data is visualized and provided to the user terminal, Thereby making it easier to grasp the prediction result.

Generally, according to an embodiment of the present invention, data groups having different data formats and formats can be easily combined through intermediate data and the correlation between data can be derived without additional data modification and editing, And can be easily derived.

Also, according to the embodiment of the present invention, two or more data groups can be analyzed using only one piece of mediation data on one analysis basis, so that there is no limitation on the kinds of data that can be analyzed, and the versatility of data analysis is widened .

Also, according to an embodiment of the present invention, the accuracy of data analysis is improved by combining and analyzing data groups utilizing mediating data obtained from two or more data groups rather than using only independent data, Is improved.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.

FIG. 2 is a configuration diagram of a data analysis apparatus through a combination of data groups according to an embodiment of the present invention.

In the following description, the description of the unnecessary embodiments that overlap with the description of FIG. 1 will be omitted.

As shown in FIG. 2, the apparatus for analyzing data through combination of data groups according to the present invention can be configured to include a server 10, a user terminal 20, and a database 30.

At this time, the server 10 may include a data receiving unit 11, an intermediate data selecting unit 12, a result deriving unit 13, a user terminal 20, and a database 30.

The data receiving unit 11 receives two or more data groups to be analyzed from two or more databases 30 independent of each other through the external network as data to be combined received by the user terminal 20. [

That is, in one embodiment, when the data to be combined by the user is a data group included in the A public institution and the B financial institution, the data to be combined from the database 30 of the A public institution and the B financial institution described above It can be understood that it performs the function of receiving the data group.

As a result, it can be understood that the data receiving unit 11 performs all the functions performed in the data receiving step of FIG.

On the other hand, the intermediate data selecting unit 12 extracts the sub data commonly included in the received data groups and selects at least one intermediate data that is a combination criterion of the data groups.

In other words, the above-described intermediate data selecting unit 12 includes content information or attribute information constituting each data group, and it is assumed that the influence value is high in the result data among the sub data that are commonly included among the data groups It will be understood that it performs the function of selecting at least one sub-data as mediating data.

On the other hand, the intermediate data selected by the intermediate data selecting unit 12 may be a function of automatically selecting the sub data expected to have a high impact value on the result data in the program, The input interface may be provided to allow the subdata selected by the user among the subdata included in common to be selected as the intermediate data.

In other words, the above-described intermediate data selecting unit 12 can be understood to perform all the functions performed in the intermediate data selecting step of FIG. 1 described above. It is also possible to analyze two or more data groups by using only the intermediate data, Thus, there is no limitation on the kinds of data that can be analyzed, and the effect of broadening the versatility of data analysis can be expected.

The result derivation unit 13 analyzes the correlation between the data groups on the basis of the selected intermediate data, and derives the result data to be derived according to the analyzed correlation.

In other words, the above-described result derivation unit 13 can be understood to perform all the functions performed in the result derivation step of FIG. 1. In analyzing two or more data groups, So that the data groups having different data formats and formats can be easily combined through the intermediary data and the correlation between the data can be derived without any additional data modification and editing, It is possible to expect an effect that it can be easily derived.

Meanwhile, the user terminal 20 may be connected to at least one of a wire / wireless telephone, a tablet PC, a laptop, a personal computer, a smartphone, a personal digital assistant A personal digital assistant (PDA), and a mobile communication terminal, and receives data groups from a database 30 connected through an external network, and performs data analysis through combining data groups of the present invention The user terminal 20 can be used without limitation.

The database 30 may be understood as a space in which two or more data groups received by the user terminal 20 are stored in two or more independent databases 30 connected to the external network, And load at least two data groups selected according to the selection input to the server 10. [

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.

3 is an embodiment of data to be combined received at a user terminal according to an embodiment of the present invention.

In the following description, the description of the unnecessary embodiment which is the same as the description of FIG. 1 and FIG. 2 described above will be omitted.

In FIG. 3, reference numeral 100 denotes an embodiment of a list of data groups received at the user terminal.

In the present invention, the data groups shown at 100 may be data groups received from two or more independent databases.

In other words, assuming that the A data group and the E data group, which is the data group thereof, are combined and analyzed, the A data group may have the nature of a population, and the comparison between the A data group and the E data group is a weight , Correlation and benchmark comparisons can be applied.

In one embodiment, when the mediated data selected through the common sub data of the A data group and the E data group is gender, region, and year, and the result data to be derived is sales, the A data group is divided into sex, The data is grouped into E data group, which is the data group of the company, and it can be compared with the A data group (for example, market share) and the correlation analysis can be made through the sales change trend .

Meanwhile, as another embodiment for further facilitating understanding, the A data group may be regarded as a benchmark index such as KOSPI 200, and the E data group, which is its own data, may be considered as stock price information for a specific item.

That is, according to the present invention, as means for comparing two or more data groups received from different databases, sub-data having a high degree of correlation with result data to be derived, among sub-data commonly included in each data group, According to one embodiment of the present invention, as a technique designed to select data, combine the above-described data groups using the selected mediating data, and to perform comparative analysis, the data format and the format It is possible to quickly and easily derive the results through data analysis by easily combining data groups through intermediate data and deriving the correlation between data, and analyzing two or more groups of data by one analysis standard using only intermediate data Of data that can be analyzed It is not limited to be the flow has the effect that the versatility of the data analysis, broadened.

Also, instead of using only independent data, it is possible to improve the accuracy of data analysis by combining and analyzing data groups by utilizing mediating data obtained from two or more data groups, thereby improving the reliability of analysis results .

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.

4 is an example of sub data constituting a data group received at a user terminal in an embodiment of the present invention.

In the following description, the description of the unnecessary embodiment which is the same as the description of the above-described FIG. 1 to FIG. 3 will be omitted.

As described above, according to the present invention, data analysis is performed by receiving two or more data groups to be analyzed from two or more independent databases through an external network, and deriving result data using the mediated data.

Meanwhile, the data group received by the user terminal includes at least one sub-data, for example, as shown in 200 of FIG.

That is, assuming that there is an A data group and a B data group, for example, the A data group may include sub data composed of age group, sex, income and area as sub data, Data, age, and sex.

According to the above-described embodiment, the sub data common between the A data group and the B data group is derived by age group and sex, and the derived age group and sex can be used as intermediate data.

In other words, the intermediate data in the present invention can be understood as a concept including content information of sub data or attribute information of the data itself, and in another embodiment of the present invention, the intermediate data includes all It can be understood that subdata can be included.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.

FIG. 5 illustrates an embodiment in which mediating data is selected from received data according to an embodiment of the present invention.

In the following description, the description of the unnecessary embodiment which is the same as the description of FIG. 1 to FIG. 4 described above will be omitted.

In the present invention, as described above, there is an embodiment in which at least one sub-data, which is expected to have a high influence value, is selected as the mediating data among the sub-data commonly included in the data groups .

5, reference numeral 300 denotes an embodiment for automatically selecting mediating data, wherein sub-data commonly included in two or more data groups is selected based on gender, region, age range, etc. It is possible to automatically select the region and the age range as the sub data which is expected to have a high impact value on the result data and it can be understood that the data analysis can be performed based on the selected mediation data.

That is, according to the present invention, it is possible to easily derive the expected result data and the analysis result based on the automatically selected mediating data, and it is also possible to separately generate or edit separate data necessary for analyzing the separated data as one data And the conversion process are omitted, thereby minimizing the time and cost required for data analysis.

Meanwhile, FIG. 5 illustrates an embodiment in which intermediate data is selected according to a selection input of a user terminal. For example, when the common sub data is sex, region and age, It is possible to understand that data analysis through data combination is performed by selecting sub data expected to have a high impact value through the input means of the user terminal and selecting one or more selected sub data as mediating data.

On the other hand, in the embodiments mentioned in FIG. 5, it is possible to assign a weight to the mediating data expected to have the greatest influence on the result data to be derived, that is, The predetermined weight may be applied according to the rank, or the weight set by the user through the input means of the user terminal may be applied.

As a result, according to the above-described embodiments of the present invention, it is possible to easily combine and analyze each data group using mediated data without using only independent data, thereby greatly improving the accuracy of data analysis. The reliability is improved.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.

Figure 6 is an example of result data provided in accordance with an embodiment of the present invention.

In the following description, the description of unnecessary embodiments which overlap with the description of the above-described Figs. 1 to 5 will be omitted.

According to an embodiment of the present invention, correlation between data groups is analyzed on the basis of the selected intermediate data, and result data to be derived can be obtained according to the analyzed correlation.

For example, the public statistical data received from the database of the public institution is used as the first data, the customer's transaction data received from the database of the financial institution is collected as the second data, Assuming that the mediator data selected from the data and the second data are regions and age groups, by combining and analyzing the data based on the selected mediator data, region and age range, It is possible to automatically analyze the financial transaction product that is likely to be activated and obtain the resultant data.

According to another embodiment of the present invention, an analysis report can be generated based on the obtained result data. At this time, the report file includes a report file including a prediction model generated from the result data according to a request input of the user terminal Can be generated and provided to the user terminal.

The prediction model described above can be understood as a prediction model including at least one of a data table, a graph and a diagram that can be generated using result data, and provides result data to the user terminal by visualizing the result data, It can be seen that the resulting data is a graphical representation.

That is, the present invention has the effect of visualizing the obtained result data and providing it to the user terminal so that the analyzed result can be easily grasped, and the data groups having different data formats and formats can be easily identified The data can be easily combined and the correlation between the data can be derived so that the result of the data analysis can be quickly and easily derived.

Also, according to the embodiment of the present invention, two or more data groups can be analyzed using only one piece of mediation data on one analysis basis, so that there is no limitation on the kinds of data that can be analyzed, and the versatility of data analysis is widened .

Also, according to an embodiment of the present invention, the accuracy of data analysis is improved by combining and analyzing data groups utilizing mediating data obtained from two or more data groups rather than using only independent data, Is improved.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.

7 is a block diagram illustrating an internal configuration of a computing device according to an embodiment of the present invention.

7, computing device 11000 includes at least one processor 11100, a memory 11200, a peripheral interface 11300, an input / output subsystem An I / O subsystem) 11400, a power circuit 11500, and a communication circuit 11600. At this time, the computing device 11000 may correspond to the user terminal (A) connected to the tactile interface device or the above-described computing device (B).

Memory 11200 can include, for example, a high-speed random access memory, a magnetic disk, SRAM, DRAM, ROM, flash memory or non-volatile memory. have. The memory 11200 may include software modules, a set of instructions, or various other data required for operation of the computing device 11000.

At this point, accessing memory 11200 from other components, such as processor 11100 or peripheral device interface 11300, may be controlled by processor 11100.

Peripheral device interface 11300 may couple the input and / or output peripheral devices of computing device 11000 to processor 11100 and memory 11200. The processor 11100 may execute a variety of functions and process data for the computing device 11000 by executing a software module or set of instructions stored in the memory 11200.

The input / output subsystem 11400 may couple various input / output peripherals to the peripheral interface 11300. For example, input / output subsystem 11400 may include a controller for coupling a peripheral, such as a monitor, keyboard, mouse, printer, or a touch screen or sensor, as needed, to peripheral interface 11300. According to another aspect, the input / output peripheral devices may be coupled to the peripheral device interface 11300 without going through the input / output subsystem 11400.

Power circuitry 11500 may provide power to all or a portion of the components of the terminal. For example, the power circuit 11500 may include one or more power supplies, such as a power management system, a battery or alternating current (AC), a charging system, a power failure detection circuit, a power converter or inverter, And may include any other components for creation, management, distribution.

Communication circuitry 11600 may enable communication with other computing devices using at least one external port.

Or as described above, communication circuitry 11600 may, if necessary, enable communications with other computing devices by sending and receiving RF signals, also known as electromagnetic signals, including RF circuitry.

7 is merely an example of the computing device 11000, and the computing device 11000 may have the additional components omitted in FIG. 7, or further components not shown in FIG. 7, Lt; RTI ID = 0.0 > components. ≪ / RTI > For example, in addition to the components illustrated in FIG. 7, a computing device for a mobile communication terminal may further include a touch screen or a sensor, and may be connected to a communication circuit 1160 through various communication methods (WiFi, 3G, LTE , Bluetooth, NFC, Zigbee, etc.). The components that may be included in computing device 11000 may be implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing or application specific integrated circuits.

The methods according to embodiments of the present invention may be implemented in the form of a program instruction that can be executed through various computing devices and recorded in a computer-readable medium. In particular, the program according to the present embodiment can be configured as a PC-based program or an application dedicated to a mobile terminal. An application to which the present invention is applied can be installed in a user terminal through a file provided by a file distribution system. For example, the file distribution system may include a file transfer unit (not shown) for transferring the file according to a request from the user terminal.

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA) A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device , Or may be permanently or temporarily embodied in a transmitted signal wave. The software may be distributed over a networked computing device and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced. Therefore, other implementations, other embodiments and equivalents to the claims are within the scope of the following claims.

Claims (10)

A method for analyzing data through a combination of data groups comprising one or more processors and one or more memories for storing instructions executable by the processor,
A data receiving step of receiving two or more data groups to be analyzed through an external network from two or more databases independent of each other as the data to be combined received by the user terminal;
An intermediate data selecting step of extracting sub data that are commonly included in the received data groups and selecting at least one intermediate data as a combining criterion of the data groups; And
And analyzing the correlation between the data groups on the basis of the selected median data and deriving result data to be derived according to the analyzed correlation. A method of analyzing data through combination.
The method according to claim 1,
Wherein the mediating data selection step comprises:
Wherein at least one sub-data, which is expected to have a high influence value, is selected as intermediate data among the sub-data commonly included in the data groups.
The method according to claim 1,
Wherein the mediating data selection step comprises:
Extracts the sub data that are commonly included in the data groups and provides the sub data to the user terminal,
Wherein at least one sub-data selected by the input means of the user terminal among the provided sub-data is selected as intermediate data.
The method according to claim 1,
The intermediate data includes:
Wherein weighting is given to intermediate data expected to have the highest correlation with the result data to be derived.
The method according to claim 1,
After performing the result derivation step,
And generating a report file having a predetermined format and providing the generated result data to the user terminal. The data analysis method according to claim 1, further comprising:
6. The method of claim 5,
The report generation step includes:
When receiving the mail transmission input to the report file from the input means of the user terminal, transmits the report file to the mail address included in the mail transmission input.
6. The method of claim 5,
The report generation step includes:
Generating a report file including a prediction model generated from the result data according to a request input of the user terminal and providing the generated report file to the user terminal when generating the report file; Way.
8. The method of claim 7,
The prediction model may include:
And a predictive model including at least one of a data table, a graph, and a diagram that can be generated using the resultant data.
An apparatus for analyzing data through a combination of data groups comprising one or more processors and one or more memories for storing instructions executable by the processor,
A data receiving unit for receiving two or more data groups to be analyzed from two or more databases independent of each other via an external network as data to be combined received by a user terminal;
An intermediate data selecting unit for extracting sub data that are commonly included in the received data groups and selecting at least one intermediate data as a combining criterion of the data groups; And
And a result extracting unit for analyzing a correlation between the data groups on the basis of the mediated data and deriving result data to be derived according to the analyzed correlation. A device for analyzing data through combination.
22. A computer-readable medium,
The computer-readable medium storing instructions that cause a computing device to perform the steps of:
A data receiving step of receiving two or more data groups to be analyzed through an external network from two or more databases independent of each other as the data to be combined received by the user terminal;
An intermediate data selecting step of extracting sub data that are commonly included in the received data groups and selecting at least one intermediate data as a combining criterion of the data groups; And
And analyzing the degree of correlation between the data groups based on the selected median data and deriving result data to be derived according to the analyzed degree of correlation. Available media.

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