Data analysis support device and data analysis support method

Abstract

To provide a data analysis support device capable of presenting an appropriate dashboard without accumulating templates in advance.SOLUTION: A CSV file input unit 111 captures a CSV file. An analysis data generation unit 112 generates analysis data obtained by analyzing the CSV file, and generates a plurality of items of shaped data obtained by shaping the analysis data into a plurality of formats. A template processing unit 114 generates multiple templates for a dashboard for displaying data in a predetermined display format based on the plurality of items of shaped data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a data analysis support device and a data analysis support method. [Background technology]

[0002] 2. Description of the Related Art In IT service operations, a monitoring system is required that monitors the capacity status of operating devices and the usage status of the system.

[0003] Traditionally, the monitoring results of a monitoring system have been output in a format such as CSV (Comma Separated Value) data and entered into a ledger using spreadsheet software, etc. However, in recent years, there has been a trend toward abolishing ledgers created using spreadsheet software, etc., in order to reduce operational costs, and instead, visualization and analysis of monitoring results using dashboards that organize and display multiple pieces of information has become more common. As a result, the demand for software that implements dashboards is increasing.

[0004] The display content of a dashboard varies depending on the content of the data to be analyzed and the customer's requests, so when developing software that implements a dashboard, the creator usually creates the software at the request of the customer. However, there are many cases where the customer himself does not understand the ideal display content of the dashboard, and the customer is not satisfied with the completed dashboard, which causes rework in the software development and increases the time required to deliver the software.

[0005] In response to this, Patent Document 1 discloses a technique for extracting a template corresponding to data to be analyzed from a template database that stores dashboard templates. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] International Publication No. 2014 / 010071 Summary of the Invention [Problem to be solved by the invention]

[0007] However, the technology described in Patent Document 1 uses a template database that accumulates dashboard templates. Therefore, in cases where there is no template suitable for the data to be processed, an appropriate dashboard cannot be presented, and the problem of the long time it takes to provide the software cannot be solved.

[0008] In addition, since Patent Document 1 does not describe anything about how to handle cases where there is a defect in the data to be processed, there is a risk that an appropriate dashboard cannot be presented when there is a defect in the data to be analyzed. Also, in CSV files and the like, there are multiple types of formats for describing date data, but if the data to be analyzed has a format other than the specified format, the date data cannot be imported appropriately, and there is a risk that an appropriate dashboard cannot be presented.

[0009] An object of the present disclosure is to provide a data analysis support device and a data analysis support method that are capable of presenting an appropriate dashboard without having to store templates in advance. [Means for solving the problem]

[0010] A data analysis support device according to one aspect of the present disclosure is a data analysis support device that generates a template for a dashboard that displays data in a predetermined display format, and has an import unit that imports data to be processed, a generation unit that generates analysis data by analyzing the data to be processed and generates a plurality of formatted data by formatting the analysis data into each of a plurality of formats, and a template processing unit that generates a plurality of the templates based on the plurality of formatted data. Effect of the Invention

[0011] According to the present invention, it is possible to present an appropriate dashboard without storing templates in advance. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram illustrating a configuration of a dashboard proposal system according to an embodiment of the present disclosure. [Diagram 2] 11 is a flowchart illustrating an example of a main process. [Diagram 3] 11 is a flowchart illustrating an example of a template process. [Figure 4] 11 is a flowchart illustrating an example of a numeric sequence process. [Diagram 5] 11 is a flowchart illustrating an example of character string processing. [Figure 6] 13 is a flowchart illustrating an example of a date string process. [Figure 7] 11 is a flowchart illustrating an example of a bar graph creation process. [Figure 8] 13 is a flowchart illustrating an example of a template display process. [Figure 9] 11 is a flowchart illustrating an example of a first error process. [Figure 10] 10 is a flowchart illustrating an example of a second error process. [Figure 11] 13 is a flowchart illustrating an example of an analysis output process. [Figure 12] FIG. 13 is a diagram showing an example of a result file. [Figure 13] FIG. 13 is a diagram illustrating an example of a template. [Figure 14] FIG. 11 is a diagram for explaining an example of data transition. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.

[0014] Fig. 1 is a diagram illustrating a configuration of a dashboard proposal system according to an embodiment of the present disclosure. The dashboard proposal system 1 illustrated in Fig. 1 is a data analysis support system that generates and presents a template of a dashboard that displays data in a predetermined display format, and is communicably connected to a user terminal 2 via a network 3.

[0015] The user terminal 2 is a terminal device used by a user who uses the dashboard proposal system 1, and includes an operation execution unit 21 and an output screen 22. The operation execution unit 21 accepts various operations from the user. The output screen 22 displays various information from the dashboard proposal system 1.

[0016] The dashboard proposal system 1 includes a WEB / AP (Application) server 11 and a storage device 12 .

[0017] The WEB / AP server 11 is a data analysis support device that generates and presents a dashboard template, and includes a CSV file input unit 111, an analysis data generation unit 112, an arithmetic processing unit 113, a template processing unit 114, an error processing unit 115, and a result file output unit 116. The WEB / AP server 11 is configured, for example, by a computer system including a processor (computer) and a memory (both not shown). In this case, each component and each function of the WEB / AP server 11 described below is realized, for example, by the processor reading a computer program and executing the read computer program. The computer program can be recorded on a recording medium that can be read by a computer. The recording medium is, for example, a semiconductor memory, a magnetic disk, an optical disk, a magnetic tape, a magneto-optical disk, or the like.

[0018] The storage device 12 is a device that stores data used or generated by the WEB / AP server 11, and has a template information storage unit 121, an error data storage unit 122, a processing result data storage unit 123, and an analysis data storage unit 124. In addition, the analysis data storage unit 124 has a numeric data storage unit 131, a numeric character data storage unit 132, a pie chart data storage unit 133, a bar chart data storage unit 134, a header information storage unit 135, and a date data storage unit 136.

[0019] The CSV file input unit 111 is an import unit that imports processing target data, which is data for creating a dashboard template. In this embodiment, the processing target data is data having a matrix structure, and more specifically, is a CSV file. However, the processing target data is not limited to a CSV file, and may be a file compatible with a predetermined spreadsheet software or the like.

[0020] The analysis data generation unit 112 is a generation unit that generates analysis data by analyzing the CSV file imported by the CSV file input unit 111, and generates a plurality of formatted data by formatting the analysis data into each of a plurality of formats. The formatted data includes the analysis data itself. The analysis data generation unit 112 also detects defects (errors) in the CSV file.

[0021] The calculation processing unit 113 performs calculation processing such as counting processing, etc. The template processing unit 114 generates a plurality of dashboard templates based on the shaped data generated by the analysis data generation unit 112.

[0022] Error processing unit 115 is a processing unit that performs error processing in response to an error detected by analysis data generation unit 112. Result file output unit 116 is an output unit that outputs error notification data indicating the content of the error detected by analysis data generation unit 112 as a result file and notifies the user of the content of the error.

[0023] Template information storage unit 121 stores template information indicating the template generated by template processing unit 114. Error data storage unit 122 stores error data indicating the processing result of error processing by error processing unit 115. Processing result data storage unit 123 stores processing result data related to errors detected by analysis data generation unit 112.

[0024] The analysis data storage unit 124 stores the analysis data generated by the analysis data generation unit 112. Specifically, the numeric data storage unit 131 stores numeric data related to numeric strings in the CSV file. The numeric character data storage unit 132 stores numeric character data related to pairs of numeric strings and character strings in the CSV file. The pie chart data storage unit 133 stores pie chart data showing a pie chart related to the CSV file. The bar chart data storage unit 134 stores bar chart data showing a bar chart related to the CSV file. The header information storage unit 135 stores header information extracted from the CSV file. The date data storage unit 136 stores date data related to date strings in the CSV file.

[0025] FIG. 2 is a flowchart for explaining an example of a main process in the dashboard proposal system 1. As shown in FIG.

[0026] In the main process, the user terminal 2 logs in to the dashboard proposal system 1 in accordance with a user's operation on the operation execution unit 21 (step S1). The user terminal 2 uploads a CSV file, which is data to be analyzed, to the dashboard proposal system 1 in accordance with a user's operation on the operation execution unit 21 (step S2).

[0027] The dashboard proposal system 1 executes template processing (see FIG. 3) to generate and display multiple templates of a dashboard of the CSV file based on the numeric column of the uploaded CSV file and the value of the numeric column for each value of the other column in a group consisting of the numeric column and the other column different from the numeric column (step S3). The other column is a column having a data value other than a numeric value.

[0028] Thereafter, the user terminal selects one of the displayed templates in accordance with the user's operation on the operation execution unit 21. The dashboard proposal system 1 specifies the selected template as a designated template (step S4).

[0029] Then, the dashboard proposal system 1 executes a result output process (see FIG. 11) for generating and outputting a result file indicating the contents of the error in the uploaded CSV file (step S5), and ends the process.

[0030] FIG. 3 is a flowchart illustrating an example of the template process in step S3 of FIG.

[0031] In the template processing, first, the CSV file input unit 111 takes in the CSV file uploaded in step S2 of FIG. 2 (step S111).

[0032] The analysis data generation unit 112 acquires header information of the CSV file imported by the CSV file input unit 111, and stores it in the header information storage unit 135 of the analysis data storage unit 124 (step S112). The header information is management information for each column of the CSV file, and includes, for example, information written in the header row, which is the first row of the CSV file. The header information may include, for example, information indicating the item name of each column of the CSV file, and information defining the data format of each column.

[0033] The analysis data generating unit 112 determines whether or not there is a blank line other than the header line in the CSV file (step S113). A blank line is a line in which no value is stored.

[0034] If a blank line is present, the analysis data generation unit 112 identifies the blank line and stores blank line data indicating the blank line as processing result data in the processing result data storage unit 123 (step S114). The analysis data generation unit 112 deletes the blank line from the CSV file (step S115). If a blank line is not present, the analysis data generation unit 112 skips the processing of steps S114 and S115.

[0035] Then, the analysis data generating unit 112 determines whether or not a numeric string exists in the CSV file (step S116). A numeric string is a string whose data format is numeric.

[0036] If the numeric sequence does not exist, the error processing unit 115 executes a first error processing (see FIG. 9) to notify the user that the numeric sequence does not exist (step S117), and ends the main processing. On the other hand, if the numeric sequence exists, the analysis data generation unit 112 executes a numeric sequence processing (see FIG. 4) to analyze the numeric sequence (step S118).

[0037] When the numeric string processing is completed, the analysis data generating unit 112 judges whether or not a character string exists in the CSV file (step S119). A character string is a string other than a numeric string, and has a data format of a character string.

[0038] If the character string exists, the analysis data generation unit 112 executes character string processing (see FIG. 5) to analyze the character string (step S120), and then executes date string processing (see FIG. 6) to analyze the date string (step S121). On the other hand, if the character string does not exist, the analysis data generation unit 112 skips the processing of steps S120 and S121.

[0039] When the date column process of step S121 is completed, the template processing unit 114 executes a template display process (see FIG. 8) for generating and displaying a dashboard template (step S122), and ends the process.

[0040] FIG. 4 is a flowchart for explaining an example of the numeric string processing in step S118 of FIG.

[0041] In the numeric string process, first, the analysis data generation unit 112 acquires all numeric strings from the CSV file (step S211). The analysis data generation unit 112 determines whether or not each numeric string includes a zero string, which is a numeric string whose values ​​are all zero (step S212).

[0042] If the zero string exists, the analysis data generating unit 112 stores the zero string data indicating the zero string as the processing result data in the processing result data storage unit 123, and excludes the zero string from the analysis target (step S213). If the zero string does not exist, the analysis data generating unit 112 skips the process of step S213.

[0043] The analysis data generating unit 112 determines whether or not each numeric string contains a value other than a numeric value (step S214).

[0044] If there is a non-numeric value, the error processing unit 115 proceeds to a second error processing (see FIG. 10) in which the non-numeric value is removed from the numeric string (step S215). If there is no non-numeric data, the analysis data generation unit 112 skips the processing of step S215.

[0045] After that, the arithmetic processing unit 113 counts the number of numeric strings as the number of target strings N (step S216). The arithmetic processing unit 113 determines whether the number of target strings N is greater than 0 (step S217).

[0046] If the number of target columns N is greater than 0, the analysis data generation unit 112 selects one of the numeric columns that has not yet been selected as a target column, and calculates the sum of each value included in the target column (step S218). The analysis data generation unit 112 calculates the average value of each value included in the target column (step S219). Then, the analysis data generation unit 112 stores the sum and average value of the target column in the numeric data storage unit 131 in the analysis data storage unit 124 as numeric data related to the target column (step S220).

[0047] Thereafter, calculation processing unit 113 decrements number of target columns N (step S221) and returns to the process of step S217. As a result, the sum and average are stored in numeric data storage unit 131 as statistical values ​​of the values ​​of each numeric sequence. Then, when it is determined in step S217 that number of target columns N is 0, analysis data generation unit 112 ends the numeric sequence processing. Note that the statistical values ​​of the values ​​of the numeric sequence are analysis data obtained by analyzing the values ​​of the numeric sequence, and are not limited to the sum and average, and may be other values.

[0048] FIG. 5 is a flowchart illustrating an example of the character string processing in step S120 of FIG.

[0049] The analysis data generation unit 112 creates all character-value pairs, which are groups (pairs) including one character string and one numeric string included in the CSV file (step S311). As a result, for example, if there are m character strings and n numeric strings, m×n pairs are created.

[0050] The arithmetic processing unit 113 counts the number of character-numeric pairs as the number of pairs L (step S312). The arithmetic processing unit 113 determines whether the number of pairs L is greater than 0 (step S313).

[0051] If the number of pairs L is greater than 0, the analysis data generation unit 112 selects one of the character-value pairs that has not yet been selected as a target pair, and divides each row (record) included in the target pair into a group of rows with the same string value (character) included in the target column (step S314).

[0052] The calculation processing unit 113 counts the number of groups as the group number M (step S315). The calculation processing unit 113 determines whether the group number M is greater than 0 (step S316).

[0053] If the number of groups M is greater than 0, the analysis data generation unit 112 selects a group that has not yet been selected as the target group, eliminates duplicate values ​​(i.e., the same characters) of each line of strings contained in the target group, and replaces the strings in the target group with a single character data (step S317).

[0054] The analysis data generating unit 112 determines whether the target group is a zero group in which all values ​​of the numeric string of the target group are 0 (step S318).

[0055] If the target group is the zero group, the analysis data generation unit 112 stores the zero group data identifying the target group as processing result data in the processing result data storage unit 123 in the storage device 12, and excludes the zero group from the analysis target (step S319).

[0056] If the target group is not a zero group, the analysis data generation unit 112 calculates the sum of each value of the numeric string in the target group as the group total (step S320). The analysis data generation unit 112 stores the group total in the numeric character data storage unit 132 in the analysis data storage unit 124 (step S321). As a result, the group total is stored as a statistical value of the numeric string values ​​for each character string value in the character-numeric value pair. Note that this statistical value is analysis data obtained by analyzing the CSV file. Also, the statistical value is not limited to the sum, and may be an average value, etc.

[0057] When step S319 or S321 ends, the calculation processing unit 113 decrements the number of groups M (step S322), and returns to the process of step S316.

[0058] Then, when it is determined in step S316 that the number of groups M is 0, the calculation processing unit 113 decrements the number of pairs N (step S323), and returns to the process of step S313.

[0059] Then, when it is determined in step S313 that the number of pairs N is 0, the analysis data generation unit 112 obtains the group total value of each group of character-numeric value pairs from the numeric-character data storage unit 132 in the analysis data storage unit 124 (step S324).

[0060] The arithmetic processing unit 113 counts the number of character-numeric pairs as the pair number E (step S325). The arithmetic processing unit 113 determines whether the pair number E is greater than 0 (step S326).

[0061] If the number of pairs E is greater than 0, the analysis data generation unit 112 selects one of the character-value pairs that has not yet been selected as a target pair, and generates pie chart data showing a pie chart according to the group total value of each group of the target pair (step S327). The analysis data generation unit 112 stores the pie chart data of the target pair in the pie chart data storage unit 133 in the analysis data storage unit 124 (step S328).

[0062] Thereafter, calculation processing unit 113 decrements the number of pairs E (step S329), and returns to the process of step S316. If it is determined in step S316 that the number of pairs E is 0, analysis data generation unit 112 ends the process.

[0063] Fig. 6 is a flowchart for explaining an example of the date string processing in step S121 in Fig. 3. In this embodiment, it is assumed that the CSV file contains a maximum of one date string. If there are multiple date strings, date string processing is performed for each date string.

[0064] In date string processing, first, the analysis data generation unit 112 determines whether or not the CSV file contains a date string having values ​​in a specified format (step S411). The date string is a string whose data format is a date string, and in this embodiment, the specified format is "yyyy-mm-dd". Note that "yyyy" indicates the year expressed in the Gregorian calendar, "mm" indicates the month, and "dd" indicates the date. Furthermore, if the month and date are less than two digits, the tens digit is set to 0. Furthermore, all of the numbers (y, m, d) are half-width.

[0065] If a date string in the specified format exists, the analysis data generation unit 112 creates all date string groups, which are groups including one each of a date string, a character string, and a numeric string included in the CSV file (step S412). The analysis data generation unit 112 generates date string group data indicating each date string group, and stores the data in the date data storage unit 136 in the analysis data storage unit 124 (step S413). The analysis data generation unit 112 proceeds to a bar graph creation process (see FIG. 7) in which bar flags are created based on the date string group data (step S500).

[0066] If there is no date string in the specified format, the analysis data generation unit 112 determines whether or not there is a date string in a first non-standard format in which the value is not in the specified format in the CSV file (step S414). In this embodiment, the first non-standard format is "yyyymmdd".

[0067] If a date string in a first non-standard format exists, the analysis data generation unit 112 converts the date data values ​​into the standard format by inserting a "- (half-width hyphen)" between the fourth and fifth digits from the left of each value in the date string (step S415), and further inserting a "-" between the seventh and eighth digits from the left of each value in the date string (step S416).

[0068] Then, the analysis data generation unit 112 creates all date string groups, which are groups including one each of date strings, character strings, and numeric strings included in the CSV file (step S417). The analysis data generation unit 112 generates date string group data indicating each date string group, and stores it in the date data storage unit 136 in the analysis data storage unit 124 (step S418). The analysis data generation unit 112 proceeds to a bar graph creation process (see FIG. 7) (step S500).

[0069] If the first non-standard format date string does not exist, the analysis data generating unit 112 determines whether the CSV file contains a second non-standard format date string whose values ​​are not in the standard format (step S419). In this embodiment, the second non-standard format is "yyyy / mm / dd".

[0070] If a date string in the second non-standard format exists, the analysis data generation unit 112 converts the " / (half-width slash)" in the date data to a "- (half-width hyphen)" to convert the date data to the standard format (step S420).

[0071] Then, the analysis data generation unit 112 creates all date string groups, which are groups including one each of date strings, character strings, and numeric strings included in the CSV file (step S421). The analysis data generation unit 112 generates date string group data indicating each date string group, and stores it in the date data storage unit 136 in the analysis data storage unit 124 (step S422). The analysis data generation unit 112 proceeds to a bar graph creation process (see FIG. 7) (step S500).

[0072] On the other hand, if there is no date data in the second non-standard format, the analysis data generation unit 112 ends the date string process and proceeds to a template display process (see FIG. 8) in which a dashboard template is generated and displayed (step S122).

[0073] Fig. 7 is a flowchart for explaining an example of the bar graph creation process in step S500 in Fig. 6. The bar graph creation process is included in the date string process in step S121 in Fig. 3.

[0074] In the bar graph creation process, the analysis data generation unit 112 acquires date string group data from the date data storage unit 136 in the analysis data storage unit 124 (step S511).

[0075] The calculation processing unit 113 counts the number of date string groups indicated by the date string group data as group H (step S512). The calculation processing unit 113 determines whether the number of groups H is greater than 0 (step S513).

[0076] If the number of groups H is greater than 0, the analysis data generation unit 112 selects one of the date string groups that has not yet been selected as a target date string group, and generates bar graph data showing a bar graph corresponding to the character string included in the target date string group, with the date string included in the target date string group as the horizontal axis (X axis) and the numeric string as the vertical axis (Y axis) (step S514). The analysis data generation unit 112 stores the bar graph data of the character string (date string group) in the bar graph data storage unit 134 in the analysis data storage unit 124 (step S515).

[0077] Thereafter, calculation processing unit 113 decrements the number of groups H (step S516) and returns to the process of step S513. Then, if it is determined in step S513 that the number of groups H is 0, analysis data generation unit 112 proceeds to the template display process (see FIG. 8) (step S122).

[0078] FIG. 8 is a flowchart illustrating an example of the template display process in step S122 of FIG.

[0079] In the template display process, first, the template processing unit 114 obtains the total value and average value of each numeric column from the numeric data storage unit 131 of the analysis data storage unit 124, and generates a dashboard including the total value and average value of each numeric column (step S611).

[0080] Next, template processing unit 114 obtains the group total value of each group of each character-value pair from numeric character data storage unit 132 of analysis data storage unit 124, and adds these group total values ​​to the dashboard generated in step S611 (step S612).

[0081] The template processing unit 114 stores the dashboard information indicating the dashboard to which the group total value has been added in the template information storage unit 121 as first template information indicating a first template of the dashboard (step S613).

[0082] Template processing unit 114 acquires pie chart data from pie chart data storage unit 133 of analysis data storage unit 124, and adds the pie chart indicated by the acquired pie chart data to the first template (step S614).

[0083] The template processing unit 114 stores the dashboard information indicating the first template to which the pie chart has been added in the template information storage unit 121 as second template information indicating the second template of the dashboard (step S615).

[0084] Template processing unit 114 acquires bar graph data from bar graph data storage unit 134 of analysis data storage unit 124, and adds the bar graph indicated by the acquired bar graph data to the second template (step S616).

[0085] The template processing unit 114 stores the dashboard information indicating the second template to which the bar graph has been added in the template information storage unit 121 as third template information indicating the third template of the dashboard (step S617).

[0086] The template processing unit 114 displays the first to third templates indicated by the first to third template images on the output screen 22 of the user terminal 2 (Step S618), and ends the template display processing.

[0087] FIG. 9 is a flowchart illustrating an example of the first error processing in step S117 of FIG.

[0088] In the first error processing, the error processing unit 115 displays an error message indicating that the numeric string does not exist on the output screen 22 of the user terminal 2 (step S711). The error processing unit 115 stores the error message in the error data storage unit 122 in the analysis data storage unit 124 (step S712), and ends the processing.

[0089] FIG. 10 is a flowchart illustrating an example of the second error processing in step S215 of FIG.

[0090] The error processing unit 115 identifies an error cell, which is a cell (field) in which non-numeric data is stored in a numeric column, and obtains the column number and row number of the error cell (step S811). The error processing unit 115 counts the number of identified error cells as the number of errors (step S812).

[0091] The error processing unit 115 displays an error message on the output screen 22 of the user terminal 2, notifying the user that non-numeric data exists in the numeric column (step S813). The error processing unit 115 stores the error cell information indicating the column number, row number and number of errors of the error cell, and the error message in the error data storage unit 122 of the analysis data storage unit 124 (step S814).

[0092] The error processing unit 115 converts the non-numeric data stored in the error cell into a specific numeric value (here, "0") (step S815), and ends the process.

[0093] FIG. 11 is a flowchart for explaining an example of the analysis output process in step S5 of FIG.

[0094] The result file output unit 116 acquires the header information from the header information storage unit 135 in the analysis data storage unit 124 (step S911).

[0095] The result file output unit 116 acquires the error cell information and the error message from the error data storage unit 122 of the storage device 12 (step S912).

[0096] The result file output unit 116 acquires the processing result data (blank row data, zero column data, and zero group data) from the processing result data storage unit 123 (step S913).

[0097] The result file output unit 116 creates table data having fields for storing the column number of the CSV file, the item name of the CSV file, the target cell indicating the cell (field) in the CSV file where the error has occurred, an error message describing the error content, and a determination result indicating the presence or absence of an error, as error notification data indicating the error content of the CSV file.Then, the result file output unit 116 adds the error content to the error notification data based on the error cell information, the error message, and the processing result data (step S914).

[0098] For example, the result file output unit 116 adds the error cell information and the column number indicated by the processing result data to the error notification data. The result file output unit 116 adds information indicating a cell corresponding to the column number and row number indicated by the error cell information and the processing result data as a target cell corresponding to the added column number, and further adds the content of the error as an error message corresponding to the added column number. The content of the error is an error message obtained from the error data storage unit 122, a message according to the content of the processing result data, etc.

[0099] The result file output unit 116 adds "NG", indicating an error, to the determination result corresponding to the added column number (step S915).

[0100] Based on the header information, the result file output unit 116 stores in the error notification data those column numbers of the CSV file that have not yet been added, and further stores the item names corresponding to each column number (step S916).Then, the result file output unit 116 stores "OK", indicating that there is no error, in the determination result corresponding to the column number stored in step S916 (step S917).

[0101] The result file output unit 116 sorts the error notification data by column number (step S918), outputs the sorted error notification data as a result file (step S919), and ends the process.

[0102] 12 is a diagram showing an example of a result file. A result file 1200 shown in FIG.

[0103] A field 1201 stores a column number. A field 1202 stores an item name. A field 1203 stores a target cell. A field 1204 stores an error message. A field 1205 stores a determination result.

[0104] Fig. 13 is a diagram showing an example of a template of a dashboard. In Fig. 13, templates A to C are shown.

[0105] Template A is an example of a first template, and includes a sum 1301 for each numeric column of the CSV file, an average value 1302 for each numeric column of the CSV file, and a group sum 1303 for each group of each character-value pair in the CSV file. Template B, in addition to the sum 1301, the average value 1302, and the group sum 1303, further includes a pie chart 1304 corresponding to each group sum 1303. Template C, in addition to the sum 1301, the average value 1302, and the group sum 1303, includes a bar chart 1305 corresponding to each date column group in the CSV file.

[0106] In this embodiment, a pie chart and a bar graph are generated as graphs, but the graphs are not limited to pie charts and bar graphs, and are not particularly limited as long as they can be generated from a CSV file. Furthermore, the templates are not limited to the example shown in Fig. 13. For example, a template may include both a pie chart 1304 and a bar graph 1305, or may not include any of the total value 1301, the average value 1302, and the group total value 1303.

[0107] 14A and 14B are diagrams showing an example of processing for a CSV file. It is assumed that a CSV file 1400 shown in FIG. 14A is imported in step S111 of FIG.

[0108] In this case, as shown in Fig. 14(b), blank lines 1401 are deleted from CSV file 1400 in step S115. Then, as shown in Fig. 14(c), the values ​​of error cells 1402 in CSV file 140 (i.e., non-numeric data in a numeric column) are converted to "0" in step S815. Furthermore, as shown in Fig. 14(d), the values ​​of date column 1403 are converted to the specified format "yyyy-mm-dd" in step S419. Also, zero column 1404, which is all zeros, is excluded from the analysis target in step S213.

[0109] As described above, in this embodiment, the CSV file input unit 111 imports a CSV file. The analysis data generation unit 112 generates analysis data by analyzing the CSV file, and generates a plurality of pieces of formatted data by formatting the analysis data into a plurality of formats. The template processing unit 114 generates a plurality of dashboard templates that display data in a predetermined display format, based on the plurality of pieces of formatted data. Therefore, since the dashboard template is generated based on the imported data, it becomes possible to present an appropriate dashboard without having to accumulate templates in advance.

[0110] In this embodiment, the analysis data generation unit 112 creates groups based on the CSV file data, each group consisting of a numeric column, which is a column item having a numeric value, and other columns, which are column items storing values ​​other than numeric values, and generates analysis data by analyzing the CSV file based on the numeric column value for each other column value in each group. This makes it possible to perform an analysis of the CSV file suitable for creating a template.

[0111] In this embodiment, the analysis data generating unit 112 generates the analysis result based on the statistical values ​​of the values ​​of the numeric string. Therefore, it is possible to perform an analysis suitable for creating a template on the CSV file.

[0112] Furthermore, in this embodiment, a template including statistical values ​​of column values ​​and a template including statistical values ​​and graphs corresponding to the statistical values ​​are generated as templates, making it possible to generate templates with high validity.

[0113] Furthermore, in this embodiment, a pie chart corresponding to a character string and a numeric string, and a bar graph corresponding to a date string and a numeric string are generated as graphs, so that it is possible to generate a template with high validity.

[0114] Furthermore, in this embodiment, when a value other than a numeric value is stored in a numeric string, the error processing unit 115 changes the value to a predetermined numeric value of "0." This makes it possible to prevent errors from occurring when attempting to calculate totals, averages, and the like for non-numeric data.

[0115] Furthermore, in this embodiment, if a blank line exists in the CSV file, the error processing unit 115 deletes the blank line from the CSV file, which makes it possible to properly analyze the CSV file.

[0116] Furthermore, in this embodiment, if there is an error in the CSV file, the result file output unit 116 notifies the user of the content of the error, thereby making it possible to improve user convenience.

[0117] In this embodiment, if the format of the date string is not a specified format, the analysis data generation unit 112 changes the format of the date string to a specified format. This makes it possible to prevent the CSV file from being unable to be analyzed correctly because the date string is not in a specified format.

[0118] The above-described embodiments of the present disclosure are illustrative examples of the present disclosure, and are not intended to limit the scope of the present disclosure to only these embodiments. A person skilled in the art can implement the present disclosure in various other forms without departing from the scope of the present disclosure. [Explanation of symbols]

[0119] 1: Dashboard proposal system 2: User terminal 11: Server 12: Storage device 111: CSV file input unit 112: Analysis data generation unit 113: Calculation processing unit 114: Template processing unit 115: Error processing unit 116: Result file output unit 121: Template information storage unit 122: Error data storage unit 123: Processing result data storage unit 124: Input data storage unit 131: Numeric data storage unit 132: Numeric character data storage unit 133: Pie chart data storage unit 134: Bar chart data storage unit 135: Header information storage unit 136: Date data storage unit

Claims

1. A data analysis support device that generates a template for a dashboard that displays data in a predetermined display format, an import unit that imports data to be processed; a generation unit that generates analysis data by analyzing the processing target data, and generates a plurality of pieces of formatted data by formatting the analysis data into a plurality of formats; A data analysis support device comprising: a template processing unit that generates the template including the analysis data, and the template including the analysis data and at least one shaped data of the plurality of shaped data.

2. the processing target data has a matrix structure, 2. The data analysis support device of claim 1, wherein the generation unit creates groups from each column of the data to be processed, the groups being composed of a numeric column that is a column that stores numeric values ​​as values ​​and other columns that are columns that store data values ​​other than numeric values ​​as values, and generates the analysis data based on the value of the numeric column for each value of the other columns in each group.

3. the generating unit generates, as the analysis data, a statistical value of the values ​​of the numerical sequence for each value of the other sequence, and generates, as the shaping data, a graph corresponding to the statistical value; The data analysis support device according to claim 2 , wherein the template processing unit generates the template including the statistical value, and the template including the statistical value and the graph.

4. The other column includes a character string that stores characters as the value, The data analysis support device according to claim 3 , wherein the generating unit generates a pie chart as the graph.

5. the other columns include a date column that stores a date as the value; The data analysis support device according to claim 3 , wherein the generating unit generates a bar graph as the graph.

6. 3. The data analysis support device according to claim 2, further comprising an error processing section which, if a value other than a numeric value is stored in the numeric string, changes the value to a predetermined numeric value.

7. The data analysis support device according to claim 2 , wherein when a blank line exists in the data to be processed, the generating unit deletes the blank line from the data to be processed.

8. 2. The data analysis support device according to claim 1, further comprising an output section that, if there is a defect in the processing target data, notifies the content of the defect.

9. the processing target data includes date data indicating a date, The data analysis support device according to claim 1 , wherein, when the format of the date data is not a specified format, the generating unit changes the format of the date data to the specified format.

10. A data analysis support method using a data analysis support device that generates a template for a dashboard that displays data in a predetermined display format, comprising: Import the data to be processed, generating analysis data by analyzing the processing target data, and generating a plurality of pieces of formatted data by formatting the analysis data into a plurality of formats; A data analysis support method comprising: generating a template including the analysis data; and generating a template including the analysis data and at least one shaped data of the plurality of shaped data.

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