Data integration method and data integration system

Abstract

To allows a user to select data to be integrated on the basis of a clear selection reference.SOLUTION: A data integration method includes: receiving input of data set search conditions including a KPI and matching data items designating data items to be matched when executing matching processing; extracting as a data set the data items having relevance with the KPI from among the data including the data items corresponding to the matching data items; and then acquiring matching processing method identifiers and processing man-hours corresponding to attribute identifiers of the data items corresponding to the matching data items to display them along with a list of the data items of the data set on a display screen.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present invention relates to a data integration method and a data integration system. [Background technology]

[0002] Conventionally, there has been a data integration technology that generates data having data items that match the needs of a user by extracting data items from different data and integrating them into one data. For example, Patent Document 1 discloses a technology that combines two or more tables, which are data composed of multiple data items, and associates the tables using the data items of the defined primary key and foreign key.

[0003] In addition, when associating data items, a matching process is performed on key data items. For example, Patent Document 2 discloses a technology in which a character string is divided into phrases, and multiple character strings are matched to determine and record the quality of the match. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2023 / 275945 [Patent Document 2] JP 2017-97719 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the conventional technologies of Patent Documents 1 and 2 described above, no consideration was given to information that could be used as selection criteria for data to be integrated, such as the matching process method, labor hours, quality of data to be matched, etc. For this reason, when selecting data to be integrated, users could not base their selection on clear selection criteria, and the validity of the selection was unclear.

[0006] The present invention has been made in consideration of the above circumstances, and has an object to enable a user to select data to be integrated based on clear selection criteria. [Means for solving the problem]

[0007] As one aspect for solving the above problem, there is provided a data integration method executed by a data integration system that extracts a data set consisting of each data item of a plurality of data from the plurality of data, the data integration system having a processor, a memory, and a storage unit, the storage unit storing domain information that associates and manages a domain identifier that identifies a domain representing an application field of the data, the data items, and attribute identifiers that identify data attributes of the data items, a matching processing method identifier that identifies a processing method for matching the data items among the plurality of data, a required processing identifier that identifies a required processing required for the matching processing, and processing man-hours for the matching processing, and the processor storing data integration information that associates and manages a KPI (Key Performance Indicator), the data matching method information and the matching processing method identifier and the processing time corresponding to the attribute identifier acquired by referring to the domain information; and displaying on a display screen the processing method and the processing time corresponding to the matching processing method identifier, together with a list of data items of the data set including the specified data item. Effect of the Invention

[0008] The present invention allows the user to select the data to be integrated based on explicit selection criteria. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing the configuration of a data management system according to an embodiment. [Diagram 2] FIG. 2 is a diagram showing the configuration of a business data management server according to the embodiment. [Diagram 3] FIG. 4 is a diagram showing the arrangement of a business data table according to the embodiment. [Figure 4] FIG. 2 is a diagram showing the configuration of an integrated data management server according to the embodiment. [Diagram 5] 3A and 3B are diagrams showing configurations of various data stored in an integrated data management server according to the embodiment. [Figure 6] FIG. 2 is a sequence diagram showing the overall processing in the data management system according to the embodiment. [Figure 7] 11 is a flowchart showing details of a dataset search process according to the embodiment. [Figure 8] 10 is a flowchart showing details of a reliability calculation process according to the embodiment. [Figure 9] 11 is a flowchart showing details of a data set extraction process according to the embodiment. [Figure 10] FIG. 4 is a diagram showing the configuration of a dataset search condition input screen according to the embodiment. [Figure 11] FIG. 13 is a diagram showing a dataset search result output screen according to the embodiment. [Figure 12] FIG. 13 is a diagram showing the configuration of a data matching process parameter input screen according to the embodiment. [Figure 13] FIG. 13 is a diagram showing the arrangement of a dataset extraction result output screen (automatic or semi-automatic) according to the embodiment. [Figure 14] FIG. 13 is a diagram showing the arrangement of a dataset extraction result output screen (manual) according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Note that the embodiments described below do not limit the invention according to the claims, and not all of the elements and combinations thereof described in the embodiments are necessarily essential to the solution of the invention.

[0011] In the following description, a program realizing each processing function unit is executed by a processor to perform a predetermined process using a storage resource (e.g., a RAM (Random Access Memory)) and / or a communication interface device (e.g., a port). The processor is, for example, a CPU (Central Processing Unit). Therefore, the process executed by each processing function unit may be a process performed by a processor or a computer having the processor.

[0012] In the following description, identical or similar components are given the same reference numerals, and in the following embodiments and modified examples, the description may be omitted or only the differences may be described. In addition, when there are multiple identical or similar components, the same reference numerals may be given different subscripts. In addition, when there is no need to distinguish between these multiple components, the subscripts may be omitted. The number of each component may be singular or plural unless otherwise specified.

[0013] In the following description, various types of information will be described in table format. However, the various types of information are not limited to table format, and may be in other formats such as CSV format. In the following description, "XXX" and "XXX identifier" are essentially the same, assuming that they are converted into each other as appropriate. For example, "domain" and "domain identifier" are essentially the same, since they can be converted into each other as appropriate using dictionaries and mapping information. In the following description, information such as the names and data of data items expressed in text contained in different tables (data) is considered to be the same information when they are converted into each other using dictionaries and mapping information.

[0014] (Configuration of Data Management System S according to the Embodiment) 1 is a diagram showing the configuration of a data management system S according to an embodiment. The data management system S includes an integrated data management server 1, an integrated data management terminal 2, business data management servers 3 (3-1, ..., 3-M), and data generating devices 4 (4-11, 4-12, 4-13, ..., 4-M1, 4-M2). The integrated data management server 1, the integrated data management terminal 2, and the business data management server 3 are connected via a network N. The data generating devices 4 are connected to the business data management server 3.

[0015] The integrated data management server 1 is placed in an operation management center 100. The integrated data management server 1 is an example of a data integration system. The business data management server 3 and the data generating device 4 are placed in a plurality of bases 200 (200-1, ..., 200-M). The number of bases 200 and the number of data generating devices 4 in each base 200 are arbitrary.

[0016] The integrated data management terminal 2 is a computer having a processor such as a CPU (Central Processing Unit), a memory, a storage, a display device, and a network interface.

[0017] At each base 200, the business data management server 3 collects, stores, and manages business data generated by a data generating device 4. The data generating device 4 is, for example, a machine tool equipped with a sensor in a factory, a weather observation device in a weather observation base, or the like, but is not limited to these.

[0018] In the operation management center 100 , the integrated data management server 1 integrates, stores, and manages the business data managed by the business data management server 3 in the base 200 in response to an instruction from a user who operates the integrated data management terminal 2 .

[0019] (Configuration of business data management server 3 according to the embodiment) 2 is a diagram showing the configuration of a business data management server 3 according to an embodiment. The business data management server 3 includes a network interface 31, a control unit (CPU) 32, an external storage device (storage) 33, and an internal storage device (memory) 34. The network interface 31, the control unit 32, the external storage device 33, and the internal storage device 34 are connected via a bus 35. The external storage device 33 and the internal storage device 34 are examples of a storage unit.

[0020] The network interface 31 is a communication device through which the business data management server 3 communicates with the integrated data management server 1 via the network N.

[0021] The control unit 32 controls the entire device of the business data management server 3, and also loads programs stored in the external storage device 33 into the internal storage device 34 and executes them in cooperation with the internal storage device 34. One such program is a business data management program 341. The business data management program 341 stores and manages the business data collected from the data generating device 4 in a business data table (Data Base) 342. The business data management program 341 and the business data table 342 will be described in detail later.

[0022] (Configuration of business data table 342 according to the embodiment) Fig. 3 is a diagram showing the configuration of a business data table 342 held by the business data management server 3 according to the embodiment. The business data table 342 is data in a table format having the columns shown in Fig. 3, for example. The business data table 342 is a plurality of data items present in each business data management server 3 of each base 200.

[0023] The business data table 342 has columns of “table identifier”, “data item 1”, “data item 2”, ... “data item N1.” “N1”, which indicates the number of items in the “data item”, is arbitrary.

[0024] The "table identifier" is identification information of the corresponding table. The "data item i" (i=1, 2, ..., N1) is business data collected from the data generating device 4 in the base 200 where the business data management server 3 is located. The "table identifier" is an example of a data identifier.

[0025] (Configuration of integrated data management server 1 according to the embodiment) 4 is a diagram showing the configuration of the integrated data management server 1 according to an embodiment. The integrated data management server 1 includes a network interface 11, a control unit (CPU) 12, an external storage device (storage) 13, and an internal storage device (memory) 14. The network interface 11, the control unit 12, the external storage device 13, and the internal storage device 14 are connected via a bus 15. The external storage device 13 and the internal storage device 14 are examples of a storage unit.

[0026] The network interface 11 is a communication device through which the integrated data management server 1 communicates with the integrated data management terminal 2 and the business data management server 3 via the network N.

[0027] The control unit 12 controls the entire device of the integrated data management server 1, and also loads programs stored in the external storage device 13 into the internal storage device 14 and executes them in cooperation with the internal storage device 14. One such program is a business data integration management program 141. The business data integration management program 141 integrates business data collected from the business data management server 3 through a data matching process described below, and stores and manages the data in an integrated business data table (Data Base) 142.

[0028] The internal storage device 14 also accumulates and manages various types of information, such as a data set search history information table 143 , a data table information table 144 , a domain information table 145 , a data matching method information table 146 , and a data processing method information table 147 .

[0029] The business data integration management program 141, the integrated business data table 142, the data set search history information table 143, the data table information table 144, and the domain information table 145 will be described later in detail. The data matching method information table 146 and the data processing method information table 147 will be described later in detail.

[0030] (Configuration of various data held by integrated data management server 1 according to the embodiment) FIG. 5 is a diagram showing the configuration of various data stored in the integrated data management server 1 according to the embodiment.

[0031] (Configuration of integrated business data table 142) The integrated business data table 142 is data in a table format having columns, for example, as shown in Fig. 5. The integrated business data table 142 has columns of "domain identifier", "table identifier", "data item 1", "data item 2", ... "data item N2". "N2", which indicates the number of items in "data item", is arbitrary.

[0032] The "domain identifier" is identification information of the application field of the data stored in the corresponding table. The "table identifier" is identification information of the corresponding table. The "data item i" (i=1, 2, ..., N2) is business data collected by the integrated data management server 1 from the subordinate business data management server 3.

[0033] (Configuration of Dataset Search History Information Table 143) The data set search history information table 143 stores a search history of a business data management server 3 of a base 200 in which a "data item" used to calculate a certain KPI is managed.

[0034] 5, the dataset search history information table 143 has columns of "domain identifier", "KPI identifier", "table identifier 1", "data item 1", "table identifier 2", "data item 2", ..., "table identifier N3", "data item N3". "N3", which indicates the number of items in the "table identifier" and "data item", is arbitrary.

[0035] The "domain identifier" is identification information for the application field of the data stored in the corresponding table. The "KPI identifier" is identification information for the KPI calculated using the item value of the "data item i" (i=1, ..., N3) stored in the corresponding table. The KPI identified by the "KPI identifier" is an index value that can be calculated as appropriate using business data managed by the business data management server 3-j (j=1, ..., M) of the base 200-j (j=1, ..., M).

[0036] "Table identifier i" (i=1, ..., N3) is identification information of the table of the business data table 342 in which the item value of "data item i" (i=1, ..., N3) is stored. "Data item i" (i=1, ..., N3) is used to calculate the KPI identified by the "KPI identifier." "Data item i" (i=1, 2, ..., N3) is business data collected by the integrated data management server 1 from the subordinate business data management servers 3.

[0037] (Configuration of Data Table Information Table 144) The data table information table 144 manages information related to the reliability of data in the business data table 342 identified by the "table identifier" and managed by the business data management server 3 of each base 200. The data table information table 144 is an example of data information.

[0038] As shown in FIG. 5, the data table information table 144 has columns of "table identifier", "number of data", "reliability of number of data", "data source information", "data source reliability", "last update date and time", and "last update date and time reliability".

[0039] "Table identifier" is identification information for the table in question. "Number of data" is the number of records of data that the table in question has. "Data number reliability" is the reliability of the table in question based on the "number of data". "Data number reliability" is expressed as a higher score for classes with a larger number of records, for example, "1" for less than 10,000 records, "2" for between 10,000 and 100,000, "3" for between 100,000 and 300,000, "4" for between 400,000 and 1 million, and "5" for over 1 million.

[0040] The "data source information" indicates the information source of the corresponding table, that is, the base 200 and the business data management server 3. The "data source reliability" is expressed as a score that is higher for paid data, for example, "3" if the corresponding table is free data, and "5" if the data is paid data.

[0041] "Last update date and time" indicates the timestamp of the last update of the table in question. "Last update date and time reliability" is, for example, "1" if the "last update date and time" of the table in question is "10 years or more" and "2" if it is "3 years or more but less than 10 years." "Last update date and time reliability" is "3" if it is "1 month or more but less than 1 year," "4" if it is "less than 1 month." In this way, the more recent the last update date and time, the higher the score of "last update date and time reliability" is represented.

[0042] (Configuration of Domain Information Table 145) As shown in FIG. 5, the domain information table 145 has columns of "domain identifier," "data item," and "attribute identifier."

[0043] The "domain identifier" is identification information for the application field of the business data indicated in the "data item." The "data item" is business data managed by the business data management server 3 of the base 200. The "attribute identifier" is identification information for the data attribute of the "data item" in combination with the "domain identifier." The data attribute indicates the data type, such as numeric data, text data, or date and time data.

[0044] (Configuration of data matching method information table 146) As shown in FIG. 5, the data matching method information table 146 has columns of "matching processing method identifier", "domain identifier", "attribute identifier", "processing type", "required processing identifier", and "processing man-hours".

[0045] The "matching method identifier" is identification information for the data matching process to be performed on the data items with the corresponding "domain identifier" and "attribute identifier." Data matching methods include time matching and location matching. The "domain identifier" is identification information for the domain of the data item for which the data matching process identified by the corresponding "matching method identifier" is to be performed. The "attribute identifier" is the data type of the data item for which the data matching process identified by the corresponding "matching method identifier" is to be performed. The "attribute identifier" corresponds to the "attribute identifier" in domain information table 145.

[0046] "Processing type" indicates whether the data matching process identified by the "data matching processing method identifier" is "automatic," "semi-automatic," or "manual." "Automatic" data matching process means that the data matching process is automatically processed by a computer without human intervention. "Semi-automatic" data matching process means that the data matching process is processed by a computer without human intervention except for the control parameters being manually provided. "Manual" data matching process means that the data matching process cannot be processed by a computer and is processed only manually.

[0047] The "required processing identifier" indicates the necessary processing or pre-processing required for the data matching process identified by the corresponding "matching method identifier." Examples of necessary processing or pre-processing include data complementation such as identical value padding or linear interpolation for missing data, rounding or averaging for numerical data, matching determination processing for text data, and name mapping processing.

[0048] "Processing Man-hours" indicates the man-hours expected for the data matching process identified by the corresponding "Matching Processing Method Identifier." "Processing Man-hours" is expressed as the processing time required to process a certain number of records, for example, XX minutes / 10,000 records.

[0049] (Configuration of data processing method information table 147) 5, data processing method information table 147 has columns of "required processing identifier" and "control parameter." The "required processing identifier" corresponds to the "attribute identifier" of data matching method information table 146. The "control parameter" indicates the control parameter to be set by the user in the required process identified by the corresponding "required processing identifier."

[0050] (Dataset Search Process According to the Embodiment) Fig. 6 is a sequence diagram showing the overall processing in the data management system S according to the embodiment. Fig. 7 is a flowchart showing the details of the data set search processing according to the embodiment.

[0051] First, in step S1, the integrated data management terminal 2 accepts input of data set search conditions from the user via the data set search condition input screen G1 (FIG. 10).

[0052] Next, in step S2, the integrated data management terminal 2 transmits to the integrated data management server 1 the data set search conditions received in step S1.

[0053] Next, in step S3, the integrated data management server 1 executes a data set search process based on the data set search conditions received from the integrated data management terminal 2. Details of the data set search process will be described later with reference to FIG.

[0054] Next, in step S4, the integrated data management server 1 transmits the processing result of the data set search processing in step S3 to the integrated data management terminal 2.

[0055] Next, in step S5, the integrated data management terminal 2 outputs the data set search result received from the integrated data management server 1 to a data set search result output screen G2 (FIG. 11).

[0056] Next, in step S6, the integrated data management terminal 2 accepts input of data set extraction conditions from the user based on the data set search result output screen G2 (FIG. 11) displayed in step S5.

[0057] Next, in step S7, the integrated data management terminal 2 transmits to the integrated data management server 1 the data set extraction conditions received in step S6.

[0058] Next, in step S8, the integrated data management server 1 executes a data set extraction process based on the data set extraction conditions received from the integrated data management terminal 2. Details of the data set extraction process will be described later with reference to FIG.

[0059] Next, in step S9, the integrated data management server 1 transmits to the integrated data management terminal 2 the result of the data set extraction process in step S8.

[0060] Next, in step S10, the integrated data management terminal 2 outputs the dataset extraction result received from the integrated data management server 1 to a dataset extraction result output screen G5 (FIG. 14).

[0061] (Details of Data Set Search Process (Step S3 (FIG. 6)) according to the embodiment) FIG. 8 is a flowchart showing details of the dataset search process according to the embodiment.

[0062] First, in step S3 a, the business data integrated management program 141 of the integrated data management server 1 receives a data set search condition from the integrated data management terminal 2.

[0063] Next, in step S3b, the business data integration management program 141 determines whether there is a search history that meets the data set search conditions received in step S3a. Specifically, the business data integration management program 141 determines whether a record that includes the domain, business improvement KPI, data item, and matching data item that were specified in the data set search conditions exists in the data set search history information table 143. If the corresponding record exists in the data set search history information table 143 (step S3b YES), the business data integration management program 141 proceeds to step S3c, and if not (step S3b NO), the business data integration management program 141 proceeds to step S3d.

[0064] In step S3c, the business data integration management program 141 extracts data sets that are related to the business improvement KPIs specified in the data set search conditions and their corresponding table identifiers from the data set search history information table 143. "Related to the business improvement KPIs" means, for example, that they are used to calculate the business improvement KPIs. A data set is a collection of data items.

[0065] Meanwhile, in step S3d, the business data integration management program 141 identifies business data tables 342 ( FIG. 3 ) managed by the business data management servers 3 of each base 200 that contain the data items or matching data items specified in the data set search conditions. Then, the business data integration management program 141 extracts data sets that are related to the business improvement KPIs specified in the data set search conditions from the identified business data tables 342. When extracting data sets (data items) that are related to the business improvement KPIs, for example, a list that lists data items related to the KPI for each KPI can be used.

[0066] Next, in step S3e, the business data integration management program 141 acquires the table identifier of the business data table 342 having the data set extracted in step S3d.

[0067] The business data integration management program 141 registers the processing results of steps S3d and S3e as search history in the data set search history information table 143.

[0068] In step S3f following step S3c or S3e, the business data integration management program 141 executes a reliability calculation process for the data set extracted in step S3c or S3d. The details of the reliability calculation process will be described later with reference to FIG.

[0069] Next, in step S3g, the business data integration management program 141 refers to the domain information table 145 to obtain attribute identifiers corresponding to the matching data items included in the data set extracted in step S3c or S3d.

[0070] Next, in step S3h, the business data integration management program 141 refers to the data matching method information table 146. Then, the business data integration management program 141 acquires an applicable "matching processing method identifier" based on the domain identifier specified in the data set search condition received in step S3a and the attribute identifier acquired in step S3g. The business data integration management program 141 also acquires the "processing type," "required processing," and "processing effort" corresponding to the acquired "matching processing method identifier."

[0071] Next, in step S3i, the business data integration management program 141 outputs the "domain," "dataset (list of data items)," "matching processing method," "processing effort," "data source," "number of data," and "data reliability" as the dataset search results.

[0072] (Details of the reliability calculation process (step S3 (FIG. 7)) according to the embodiment) FIG. 8 is a flowchart showing details of the reliability calculation process according to the embodiment.

[0073] First, in step S3f1, the business data integration management program 141 acquires the number of data items, the data source, and the last update date and time of the data in the business data table 342 (FIG. 3) corresponding to each table identifier acquired in step S3c or S3e. The number of data items and the last update date and time of the data can be obtained, for example, by referring to the corresponding business data table 342. The data source can be acquired, for example, by inquiring to the business data management server 3 that manages the corresponding business data table 342.

[0074] Next, in step S3f2, the business data integration management program 141 calculates the reliability of the number of data items based on the number of data items in the business data table 342 corresponding to each table identifier acquired in step S3c or S3e.

[0075] Next, in step S3f3, the business data integration management program 141 calculates the data source reliability based on the data source of the business data table 342 corresponding to each table identifier acquired in step S3c or S3e.

[0076] Next, in step S3f4, the business data integration management program 141 calculates the reliability of the last update date and time based on the last update date and time of the data in the business data table 342 corresponding to each table identifier acquired in step S3c or S3e.

[0077] Next, in step S3f5, the business data integration management program 141 calculates data reliability by summing the data number reliability, data source reliability, and last update date and time reliability calculated in steps S3f2, S3f3, and S3f4. The business data integration management program 141 associates table identifiers with the data number, data number reliability, data source information, data source reliability, last update date and time, and last update date and time reliability acquired or calculated in the reliability calculation process, and stores them in the data table information table 144.

[0078] (Details of Data Set Extraction Process (Step S8 (FIG. 6)) according to the embodiment) FIG. 9 is a flowchart showing details of the data set extraction process according to the embodiment.

[0079] First, in step S8a, the business data integration management program 141 of the integrated data management server 1 extracts the business data table 342 (FIG. 3) and data items required to generate the data set selected based on the data set extraction conditions received in step S6 (FIG. 6).

[0080] Next, in step S8b, the business data integration management program 141 refers to the data table information table 144 (FIG. 5) and determines whether the "processing type" of the data matching processing method is "automatic" or "semi-automatic." If the "processing type" of the data matching processing method is "automatic" or "semi-automatic," the business data integration management program 141 proceeds to step S8c, and if the "processing type" is "manual," the business data integration management program 141 proceeds to step S8f.

[0081] In step S8c, the business data integration management program 141 refers to the data table information table 144 (FIG. 5) and determines whether the "processing type" of the data matching processing method is "semi-automatic." If the "processing type" of the data matching processing method is "semi-automatic," the business data integration management program 141 proceeds to step S8d, and if the "processing type" is "automatic," it skips step S8d and proceeds to step S8e.

[0082] In step S8d, the business data integration management program 141 accepts the user's setting of parameters necessary for the data matching process via the data matching process parameter input screen G3 (FIG. 12) of the integrated data management terminal 2.

[0083] In step S8e, the business data integration management program 141 performs table join between the business data table 342 to be integrated (FIG. 3) and the business data table 342 of the integration candidate, and executes data matching processing of each data item corresponding to the matching data item. The table join key used in the table join is extracted by a well-known technique. Then, the business data integration management program 141 outputs the integration result to the data set extraction result output screen G4 (FIG. 13).

[0084] The business data table 342 to be integrated is, for example, data owned by the user who executes the data set extraction process. The business data table 342 as an integration candidate is, for example, data provided by an individual, organization, or system other than the user. The integrated data (integrated business data) is data integrated by performing a matching process between the business data table 342 to be integrated and the business data table 342 as an integration candidate.

[0085] Meanwhile, in step S8f, the business data integration management program 141 outputs data items of the business data table 342 to be integrated (FIG. 3) and the business data table 342 of the integration candidate to the data set extraction result output screen G5 (FIG. 14).

[0086] (Configuration of Dataset Search Condition Input Screen G1 According to the Embodiment) FIG. 10 is a diagram showing the configuration of a dataset search condition input screen G1 according to the embodiment.

[0087] The dataset search condition input screen G1 has a domain input box G1a, a business improvement KPI input box G1b, a data item 1 input box G1c, a data item 2 input box G1d, a data item 3 input box G1e, and a data item 4 input box G1f. The data items input into the data item 1 input box G1c, the data item 2 input box G1d, the data item 3 input box G1e, and the data item 4 input box G1f are examples of specified data items designated to be included in the dataset.

[0088] The data set search condition input screen G1 also has a matching data item 1 input box G1g, a matching data item 2 input box G1h, an add data item button G1i, an add matching data item button G1j, and a search button G1k.

[0089] The domain input box G1a accepts input of the name of the domain to which the data to be integrated applies. Input into the domain input box G1a is optional. The business improvement KPI input box G1b accepts input of KPIs that realize business improvement that can be calculated using the integrated business data, for example.

[0090] The data item 1 input box G1c, the data item 2 input box G1d, the data item 3 input box G1e, and the data item 4 input box G1f accept input of data items to be selected from the data to be integrated. The data item 1 input box G1c, the data item 2 input box G1d, the data item 3 input box G1e, and the data item 4 input box G1f are similar input boxes. The number of input boxes for data items to be selected from the business data to be integrated is not limited to four.

[0091] The matching data item 1 input box G1g and the matching data item 2 input box G1h accept input of data items to be selected from the business data of the integration candidates and associated with the data to be integrated by the data matching process. The matching data item 1 input box G1g and the matching data item 2 input box G1h are similar input boxes. The number of input boxes for data items to be selected from the business data of the integration candidates is not limited to two.

[0092] The add data item button G1i is a button for adding input boxes similar to the data item 1 input box G1c, data item 2 input box G1d, data item 3 input box G1e, and data item 4 input box G1f to the dataset search condition input screen G1. The add match data item button G1j is a button for adding input boxes similar to the match data item 1 input box G1g and match data item 2 input box G1h to the dataset search condition input screen G1.

[0093] The search button G1k is a button for instructing execution of a dataset search process based on the dataset search conditions input to the dataset search condition input screen G1. When the user presses the search button G1k, step S1 (FIG. 6) is completed.

[0094] The domain entered in the domain input box G1a and the KPI name entered in the business improvement KPI input box G1b are appropriately converted into a domain identifier and a KPI identifier, respectively.

[0095] (Dataset search result output screen G2 according to the embodiment) FIG. 11 is a diagram showing the dataset search result output screen G2 according to the embodiment.

[0096] The data set search result output screen G2 has items for search conditions G2a, search results G2b, and a data extraction instruction button G2c.

[0097] The search condition G2a has the display items of "domain," "business improvement KPI," "data item," and "matching data item."

[0098] "Domain" is the domain name entered in the domain input box G1a on the dataset search condition input screen G1 (Figure 10). "Business improvement KPI" is the KPI entered in the business improvement KPI input box G1b on the dataset search condition input screen G1. "Data item" is the data item entered in data item 1G1c to data item 4G1f on the dataset search condition input screen G1. "Matching data item" is the matching data item entered in matching data items 1G1g and G1h on the dataset search condition input screen G1.

[0099] The search result G2b includes, for example, two search results G2b1 and G2b2. Note that the search results are not limited to two.

[0100] Search result G2b1 is one of the search results obtained by searching the business data of the integration candidates using the search criteria displayed in search criteria G2a. The "Data Item Name" of search result G2b1 includes the data items "Location" and "Time" in the business data of the integration candidates that correspond to the data items "Location" and "Time" specified in the "Matching Data Item" of search criteria G2a. In addition, the data items in the business data of the same integration candidates include "Weather" and "Temperature", which are related to the KPI "Building Power Consumption" specified in the "Business Improvement KPI" of search criteria G2a.

[0101] Additionally, the data items "Location" and "Time" specified in the "Match Data Item" of search condition G2a have matching methods of "Normal Matching" and "Time Matching", respectively. Since the data item "Location" has an exact match between the data item name in the business data to be integrated and the business data of the integration candidate, the matching method is "Normal Matching", which determines whether the data item values ​​match. The matching method for data item "Time" is "Time Matching".

[0102] The "processing type" is "automatic" for the data item "location" and "semi-automatic" for the data item "time." The "required processing" is "none" for the data item "location" and "missing data interpolation processing" for the data item "time."

[0103] Furthermore, the "data items" shown in search result G2b1 are the "estimated labor hours" of "XX minutes / 10,000 records" for the data matching process when integrating the business data to be integrated with the business data of the integration candidates. Also, the business data of the integration candidates that can provide the data items shown in search result G2b1 have a "data source" of "open data," a "number of data" of "10,000,000 records," and a "data reliability" of "XX."

[0104] The search result G2b2 also has the same information as the search result G2b1.

[0105] The user checks the checkboxes of the search results to be selected from these multiple search results G2b. At this time, the user may select multiple search results by checking the checkboxes of multiple search results. The checked search results become the data set extraction conditions. When the data extraction instruction button G2c is pressed, step S6 (Fig. 6) is completed, and data set extraction conditions are generated based on the checked search results and sent to the integrated data management server 1 (Fig. 1).

[0106] (Data matching processing parameter input screen G3 according to the embodiment) FIG. 12 is a diagram showing a data matching process parameter input screen G3 according to the embodiment.

[0107] The data matching process parameter input screen G3 shown in Fig. 12 is an input screen for parameters that need to be input by the user when the matching process method is "time matching." For matching processes other than "time matching," the data matching process parameter input screen G3 becomes an input screen for parameters according to the matching process method.

[0108] The data matching process parameter input screen G3 has input items for time granularity G3a and data complementation method G3b according to the matching process method of, for example, "time collation," and an OK button G3c.

[0109] For time granularity G3a, when the time granularity of the data item "time" of two business data to be matched is different, a unit for aligning the time interval of both data items "time" is input. "1 record / 1 hour" shown in FIG. 12 is an example in which the interval of the data item "time" is "1 hour". When data with an interval of the data item "time" longer than "1 hour" (for example, "2 hours") is to be set to an interval of "1 hour", the data with an interval of "2 hours" is copied and made into data with an interval of "1 hour". On the other hand, when data with an interval of the data item "time" shorter than "1 hour" (for example, "10 minutes") is to be set to an interval of "1 hour", the data with an interval of "10 minutes" is collected for each "1 hour" to calculate the average value, and this average value is made into data with an interval of "1 hour".

[0110] The data complementation method G3b indicates a method of complementing missing data, and includes "same value padding" that assigns a predetermined same value to missing data, and "linear interpolation" that linearly interpolates missing data based on the data before and after it. The data complementation method G3b is not limited to "same value padding" or "linear interpolation".

[0111] When the OK button G3c is pressed, a data matching process and a data complement process are executed according to the time granularity G3a and the data complement method input to the data complement method G3b.

[0112] (Dataset Extraction Result Output Screen (Automatic or Semi-Automatic) G4 according to the Embodiment) 13 is a diagram showing a dataset extraction result output screen (automatic or semi-automatic) G4 according to an embodiment. The dataset extraction result output screen G4 displays the dataset extraction result extracted when a search result in which "processing type" is "automatic" or "semi-automatic" is selected on the dataset search result output screen G2 and the data extraction instruction button G2c is pressed.

[0113] The dataset extraction result output screen G4 has dataset extraction conditions G4a, dataset extraction results G4b, and a file output button G4c.

[0114] The dataset extraction conditions G4a are information that combines the search conditions G2a on the dataset search result output screen G2 (FIG. 11) with a search result selected from the search result G2b (search result G2b1 (FIG. 11) in the case of FIG. 13).

[0115] The dataset extraction result G4b is data in which datasets are extracted in the integrated data management server 1 according to the dataset extraction conditions G4a and integrated automatically or semi-automatically.

[0116] When the user presses the file output button G4c, the data set extraction result G4b is registered in the integrated business data table 142 (FIG. 5).

[0117] 13 shows a case where one integration candidate business data is selected and integrated with one integration target business data, but is not limited to this, and multiple integration candidate business data may be selected and integrated with one integration target business data.

[0118] (Dataset Extraction Result Output Screen (Manual) G5 according to the embodiment) 14 is a diagram showing a dataset extraction result output screen (manual) G5 according to an embodiment. The dataset extraction result output screen G5 displays a dataset extraction result extracted when a search result including "manual" as the "processing type" is selected on the dataset search result output screen G2 and the data extraction instruction button G2c is pressed.

[0119] The dataset extraction result output screen G5 has dataset extraction conditions G5a, dataset extraction results G5b, and a file output button G5c.

[0120] The dataset extraction conditions G5a are information that combines the search conditions G2a on the dataset search result output screen G2 (FIG. 11) with a search result selected from the search result G2b (search result G2b2 (FIG. 11) in the case of FIG. 14).

[0121] The dataset extraction result G5b includes datasets G5b1 and G5b2 extracted in the integrated data management server 1 according to the dataset extraction condition G4a. Since the data item "location" of the datasets G5b1 and G5b2 has a matching type of "manual", they are not combined "automatically" or "semi-automatically", and the unintegrated business data before the matching process is executed is displayed. The user manually operates the dataset extraction result G5b to integrate the data. When the user then presses the file output button G5c, the dataset extraction result G5b manually integrated by the user is registered in the integrated business data table 142 (FIG. 5).

[0122] 14 shows a case where one integration candidate business data is selected for one integration target business data, and the business data before integration and the business data of one integration candidate are displayed side by side so that the business data can be manually integrated. However, the present invention is not limited to this, and multiple integration candidate business data may be selected for one integration target business data, and the business data before integration and the business data of multiple integration candidates may be displayed side by side so that the business data can be manually integrated.

[0123] (Effects of the embodiment) In the above embodiment, the data items of the business data to be integrated are extracted as a dataset based on the dataset search conditions, and the processing method and processing labor hours for the matching processing of the matching data items are presented to the user along with the dataset extraction results. Therefore, according to this embodiment, the data to be integrated can be selected based on these clear selection criteria, taking into account the processing method and processing labor hours.

[0124] In the above embodiment, a domain is specified in the dataset search conditions, and the dataset, processing method, and processing effort are acquired based on the dataset search conditions including the domain specification. Therefore, according to the above embodiment, by specifying a domain, it is possible to improve the validity of the extracted dataset and processing method.

[0125] In the above embodiment, data extraction conditions are generated that include the specification of a dataset selected by the user from the candidate datasets extracted based on the dataset search conditions, and a dataset is extracted based on the data extraction conditions to generate integrated data. Therefore, according to the above embodiment, the process from dataset search through selection to extraction and integration can be seamlessly performed via a GUI (Graphical User Interface), thereby improving user convenience.

[0126] In the above-described embodiment, search history information that associates KPIs with datasets extracted based on dataset search conditions that include the KPIs is managed, and when searching for a dataset, a dataset that corresponds to the same KPI is obtained from the search history information. Therefore, according to the above-described embodiment, by using the search history information, it is possible to improve the efficiency of searching datasets in some cases.

[0127] In addition, in the above-described embodiment, the reliability of the data providing the search result dataset is calculated and presented to the user, so that the user can select a dataset extracted from data with high reliability, which may improve the quality of the integrated data.

[0128] Although the embodiments of the present disclosure have been described above in detail, the present disclosure is not limited to the above-described embodiments, and various modifications can be made without departing from the spirit of the present disclosure. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present disclosure is not necessarily limited to those having all of the configurations described. In addition, it is possible to add, delete, or replace part of the configuration of the above-described embodiments with other configurations.

[0129] Furthermore, the above-mentioned configurations, functional units, processing units, etc. may be realized in part or in whole by hardware, for example, by designing them as integrated circuits. The above-mentioned configurations, functions, etc. may be realized in software by a processor interpreting and executing a program that realizes each function. Information such as the program, table, file, etc. that realizes each function can be stored in a memory, a storage device such as an HDD or SSD, or a recording medium such as an IC card, an SD card, or a DVD.

[0130] In addition, in each of the above figures, the control lines and information lines are shown as those considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the actual implementation. For example, it may be considered that almost all the components are actually connected to each other.

[0131] The above-mentioned arrangement of the functions and data of the integrated data management server 1, the integrated data management terminal 2, and the business data management server 3 is merely an example. The arrangement of the functions and data and the integration and distribution of the functions and data can be changed to an optimal form in terms of the performance of the hardware and software, processing efficiency, communication efficiency, etc. [Explanation of symbols]

[0132] 1: Integrated data management server, 2: Integrated data management terminal, 3: Business data management server, 4: Data generating device, 11: Control unit, 141: Business data integrated management program, 142: Integrated business data table, 143: Data set search history information table, 144: Data table information table, 145: Domain information table, 146: Data matching method information table, 147: Data processing method information table, 341: Business data management program, 342: Business data table.

Claims

1. A data integration method executed by a data integration system that extracts a data set consisting of each data item of a plurality of data, the method comprising: The data integration system includes a processor, a memory, and a storage unit. The storage unit is domain information for managing a domain identifier that identifies a domain representing an application field of the data, the data item, and an attribute identifier that identifies a data attribute of the data item in association with each other; storing data matching method information for managing a matching method identifier for identifying a processing method for matching the data items among the plurality of data, the attribute identifier, a necessary processing identifier for identifying a necessary processing required for the matching process, and a processing man-hour for the matching process in association with each other; The processor, Accepting input of data set search conditions including a KPI (Key Performance Indicator), a designated data item which is the data item to be included in the data set, and a matching data item which designates the data item to be matched when performing the matching process; Extracting, as the data set, the data items related to the KPI from the data including the data items corresponding to the specified data items or the matching data items; Refer to the domain information to obtain the attribute identifier corresponding to the data item corresponding to the matching data item; Refer to the data matching method information, and obtain the matching processing method identifier and the processing man-hours corresponding to the attribute identifier obtained by referring to the domain information; The processing method and the processing man-hours corresponding to the matching processing method identifier are displayed on a display device together with a list of data items of the data set including the specified data item. A data integration method comprising each process.

2. 2. The data integration method according to claim 1, the data matching method information and the data are managed in association with the domain identifier; The processor, Accepting input of the dataset search conditions including the designation of the domain; Extracting the dataset from the data that corresponds to the domain identifier of the domain specified in the dataset search conditions and includes the data item that corresponds to the matching data item; Refer to the domain information, and obtain the attribute identifier corresponding to a combination of the domain identifier of the domain specified in the data set search condition and the data item corresponding to the data set; The data matching method information is referenced, and the matching processing method identifier and the processing man-hours corresponding to a combination of the attribute identifier obtained by reference to the domain information and the domain identifier of the domain specified in the data set search condition are obtained. A data integration method comprising each process.

3. 3. The data integration method according to claim 1, further comprising: The processor, accepting a user's selection of one of the data sets; Extracting the data set selected by the user; performing said matching process on said matching data items included in said data set; generating integrated data including the data set as the data item; The integrated data is displayed on the display device. A data integration method comprising each process.

4. 4. The data integration method according to claim 3, the data matching method information is managed in association with a processing type indicating whether the matching process is automatic, which is executed without human intervention, semi-automatic, which requires input of processing parameters, or manual, which is executed by human intervention; The processor, Refer to the data matching method information, and refer to the domain information to acquire the processing type corresponding to the attribute identifier acquired; If the processing type is semi-automatic, the input of the parameters is accepted and the matching processing is executed based on the parameters. A data integration method comprising each process.

5. 5. The data integration method according to claim 4, The parameters include at least one of a time granularity that represents a time interval of the value of the data item and a method of complementing missing values.

13. A data integration method comprising:

6. 5. The data integration method according to claim 4, The processor, When the processing type is the manual processing, the plurality of data before the execution of the matching processing is displayed on the display device.

23. A data integration method comprising the steps of:

7. 2. The data integration method according to claim 1, The storage unit is storing search history information for managing the KPI in association with the data set extracted based on the data set search condition including the KPI; The processor, The data set having an association with the KPI included in the data set search condition is extracted from the search history information.

23. A data integration method comprising the steps of:

8. 2. The data integration method according to claim 1, The storage unit stores data information for managing information related to the reliability of the data, The data is managed in association with a data identifier for identifying the data; The processor, obtaining the data identifier for identifying the data by referring to the data having the data item corresponding to the data set; Refer to the data information to obtain the information related to the reliability of the data identified by the data identifier; Calculating the reliability based on the information; The reliability is displayed on the display device. A data integration method comprising each process.

9. A data integration system for extracting a data set consisting of each data item of a plurality of data, comprising: The data integration system includes a processor, a memory, and a storage unit. The storage unit is domain information for managing a domain identifier that identifies a domain representing an application field of the data, the data item, and an attribute identifier that identifies a data attribute of the data item in association with each other; storing data matching method information for managing a matching method identifier for identifying a processing method for matching the data items among the plurality of data, the attribute identifier, a necessary processing identifier for identifying a necessary processing required for the matching process, and a processing man-hour for the matching process in association with each other; The processor, Accepting input of data set search conditions including a KPI (Key Performance Indicator), a designated data item which is the data item to be included in the data set, and a matching data item which designates the data item to be matched when performing the matching process; Extracting, as the data set, the data items related to the KPI from the data including the data items corresponding to the specified data items or the matching data items; Refer to the domain information to obtain the attribute identifier corresponding to the data item corresponding to the matching data item; Refer to the data matching method information, and obtain the matching processing method identifier and the processing man-hours corresponding to the attribute identifier obtained by referring to the domain information; The processing method and the processing man-hours corresponding to the matching processing method identifier are displayed on a display device together with a list of data items of the data set including the specified data item. A data integration system comprising:

10. 10. The data integration system of claim 9, the data matching method information and the data are managed in association with the domain identifier; The processor, Accepting input of the dataset search conditions including the designation of the domain; Extracting the dataset from the data that corresponds to the domain identifier of the domain specified in the dataset search conditions and includes the data item that corresponds to the matching data item; Refer to the domain information, and obtain the attribute identifier corresponding to a combination of the domain identifier of the domain specified in the data set search condition and the data item corresponding to the data set; The data matching method information is referenced, and the matching processing method identifier and the processing man-hours corresponding to a combination of the attribute identifier obtained by reference to the domain information and the domain identifier of the domain specified in the data set search condition are obtained. A data integration system comprising:

11. 11. The data integration system according to claim 9 or 10, The processor, accepting a user's selection of one of the data sets; Extracting the data set selected by the user; performing said matching process on said matching data items included in said data set; generating integrated data including the data set as the data item; The integrated data is displayed on the display device. A data integration system comprising:

12. 12. The data integration system of claim 11, the data matching method information is managed in association with a processing type indicating whether the matching process is automatic, which is executed without human intervention, semi-automatic, which requires input of processing parameters, or manual, which is executed by human intervention; The processor, Refer to the data matching method information, and refer to the domain information to acquire the processing type corresponding to the attribute identifier acquired; If the processing type is semi-automatic, the input of the parameters is accepted and the matching processing is executed based on the parameters. A data integration system comprising:

13. 13. The data integration system of claim 12, The parameters include at least one of a time granularity that represents a time interval of the value of the data item and a method of complementing missing values. A data integration system comprising:

14. 13. The data integration system of claim 12, The processor, When the processing type is the manual processing, the plurality of data before the execution of the matching processing is displayed on the display device. A data integration system comprising:

15. 10. The data integration system of claim 9, The storage unit is storing search history information for managing the KPI in association with the data set extracted based on the data set search condition including the KPI; The processor, The data set having an association with the KPI included in the data set search condition is extracted from the search history information. A data integration system comprising:

16. 10. The data integration system of claim 9, The storage unit stores data information for managing information related to the reliability of the data, The data is managed in association with a data identifier for identifying the data; The processor, obtaining the data identifier for identifying the data by referring to the data having the data item corresponding to the data set; Refer to the data information to obtain the information related to the reliability of the data identified by the data identifier; Calculating the reliability based on the information; The reliability is displayed on the display device. A data integration system comprising:

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