KR101505858B1 - A templet-based online composing system for analyzing reports or views of big data by providing past templets of database tables and reference fields - Google Patents

Abstract

The present invention relates to a template-based online analysis report creation support system for converting a table relation of cube data storing large amount of data and reference item data into a database as a template and supporting the search for the template by a keyword, A template constructing unit for constructing and storing a table relation diagram and a reference item created for referring to the data of the template; And a template search unit for searching for a template by a keyword input by the client and displaying the searched templates, wherein the table relationship diagram is configured by a join relationship between a DB table of the data cube and a DB table, The reference item is composed of a field item of the DB table and a derivation item defined by the field items, and the template search unit defines a name of the template, a name of the DB table, a name of the reference item, The search is performed by using the keyword with respect to at least one of the names of the field items.
By storing the table relation and the reference item data in the past as templates and reusing them by the above method, it is possible to provide a service environment in which a report can be generated by inputting desired information, .

Description

Technical Field [0001] The present invention relates to a template-based on-line analysis report creation support system for searching a table relationship and a reference template for easy analysis of a large amount of data, and reference fields}

In order to easily analyze a large amount of data, the present invention stores table relation and reference data generated when an analysis report is created by a user in the past as a template, searches the template when creating a new analysis report, Based analysis report supporting system for supporting the analysis report creation.

Generally, business intelligence (BI) analyzes a company's vast amount of data in a formal or informal manner, such as statistical analysis, or processes the analyzed information into an easy-to-understand and easy-to-understand report, To a set of tools that allow you to proceed to

There are a lot of data that companies accumulate as they do business. These data convey the vividness of the business scene, and if it is properly analyzed, it can extract the information needed for the business. Especially, as the importance of analysis of data such as SNS and social media continues to grow, there are many companies that need to analyze and collect big data for customer management and product promotion for products of companies ought. The term big data refers to data sets that have common software tools and computer systems to collect, manage, store, search, share, analyze, and visualize data belonging to a certain amount of time (data set). The size of the big data may have a range of terabytes, exabytes, or zeta bytes. Big data can exist in a variety of fields, including web logs, RFID, sensor networks, social networks, social data, Internet text and documents, Internet search indexing, POS (point of sale) data, , Photo recording, video recording, and electronic commerce.

An on-line analytical processing (OLAP) system and the like are introduced and used in order to accumulate such big data in a data warehouse (DW) or a data structure and analyze the accumulated data by using the accumulated big data have.

However, it is not so easy to draw meaningful analysis results from the large amount of data accumulated in the field. Many tools have been developed individually for this analysis. Examples include data extraction and transformation (ETT) tools, online analytical processing (OLAP) tools for multidimensional data analysis, reporting tools for generating reports, and data mining tools for finding hidden associations between data. It is a type of business intelligence (BI) that forms a suite of tools into a suite of software.

However, conventional business intelligence (BI) has gathered a variety of analytical tools, but it was difficult to use universally, except for specific analysis, because users had to be skilled in dealing with various analytical tools.

In order to solve this problem, a reporting technique for searching and analyzing a database in a web environment has been proposed [Patent Document 1]. The prior art is a technology in which a report developer designs a frame of a report and a user requests output of the report according to a designed report frame. At this time, the developer can design the frame of the report using WYSWYG and drag & drop method. Specifically, 4GL (4th Generation Programming Language) method, Visual Basic, Delphi, PowerBuilder is used. However, these techniques have the problem that developers must learn reporting tools or languages in order to design the framework of the report. Of course, WYSIWYG programming languages or development tools such as PowerBuilder are easy to learn compared to other tools, but they are an unfamiliar tool for general office worker. For this reason, even though reporting tools for business intelligence (BI) are introduced, they are not well used by business people, especially small business people.

In addition, techniques for creating an analysis report or screen on-line by processing basic data stored in a database have been proposed [Patent Document 2]. In the prior art, a DB object corresponding to an SQL statement for querying a database is created and linked with a pivot table cache of Excel, and a pivot table or a chart object is created on an Excel sheet based on the created DB object, . Using these analytical report generation tools, users can easily create analytic reports online with data from the database.

However, even if it is easy to create using the online analysis report tool, the general user selects the DB table from the database (or data warehouse, data cube) every time the analysis report is created, sets the relationship between the DB tables, Create a query and create a table or graph for the analysis report. That is, the general user has to repeatedly perform such similar analysis report creation work.

If you create tables or graphs of the same type, you can use the analysis results you created in the past. However, if there is a slight difference in the analysis result, the user has to perform the operation again from the beginning. In particular, most analyst reports created by ordinary users are not very different from analytical reports created in the past, but are slightly modified. Therefore, if you provide an environment in which you can reuse the results of the analysis report that you created in the past, you will be able to make the analysis report work easier.

[Patent Document 1] Korean Patent No. 10-0497811 (published on June 18, 2005) [Patent Document 2] Korean Patent No. 10-0969656 (published on July 14, 2010)

An object of the present invention is to solve the above-mentioned problems, and it is an object of the present invention to provide a method and a system for storing a table relation and reference item data generated when an analysis report is created by a user in the past as a template, And a template-based on-line analysis report creation support system for supporting the analysis report creation based on the retrieved template.

In particular, an object of the present invention is to provide a template-based on-line analysis report which supports the template relation of the cube data and the reference item data, which are created at the time of creating the analysis report by the user, into a database as a template, And to provide a support system.

In addition, the object of the present invention is to divide reference items into items of a dimension type and items of a measurement value type in a template to which the cube data has been referred, and when the template is searched, the reference items corresponding to the dimension and the measurement value are automatically And to provide a template-based on-line analysis report creation support system for generating analysis results.

In order to accomplish the above object, the present invention provides a template-based online analysis report creation support system connected to a user terminal installed with a client and connected to a data cube storing data, A template constructing unit for constructing and storing a table relationship diagram and a reference item as templates; And a template search unit for searching for a template by a keyword input by the client and displaying the searched templates, wherein the table relationship diagram is configured by a join relationship between a DB table of the data cube and a DB table, The reference item is composed of a field item of the DB table and a derivation item defined by the field items, and the template search unit defines a name of the template, a name of the DB table, a name of the reference item, The search is performed by the keyword on at least one of the names of the field items.

According to another aspect of the present invention, there is provided a template-based on-line analysis report creation support system, wherein the template composition unit collects data of table relationships and reference items created by online analysis processing (OLAP) and forms the template.

According to another aspect of the present invention, there is provided a template-based on-line analysis report creation support system, wherein the template composition unit forms the template from query statements generated by online analysis processing (OLAP) Extracts a table relationship table of the template from the DB table referenced in the query and the field condition therebetween.

According to another aspect of the present invention, there is provided a template-based online analysis report creation support system, wherein when the template search unit searches a plurality of templates, the search result list is displayed in a high- .

According to another aspect of the present invention, there is provided a template-based on-line analysis report creation support system, wherein the template search unit sets a priority level higher than the other candidates when the keyword matching target is a template name, The priority is set to a high priority or the priority is set to be higher as more keywords are matched when a plurality of keywords are input.

The present invention is also directed to a template-based online analysis report creation support system, wherein the template search unit receives a query sentence in place of a keyword, and extracts a keyword from the query sentence through morphological analysis.

In addition, the present invention provides a template-based online analysis report creation support system, wherein the reference items are classified into a dimension format and a measurement value format.

According to another aspect of the present invention, there is provided a template-based online analysis report creation support system, which displays an interface screen (hereinafter referred to as a query design screen) capable of configuring a query based on only reference items of a selected template, Wherein the query design screen comprises an area (hereinafter referred to as an item display area) for displaying reference items of a template and an area for displaying selected reference items (hereinafter referred to as a selection display area) And automatically generating a query statement that refers to the reference items of the selection display area when the reference items are selected in the selection display area on the query design screen.

According to another aspect of the present invention, there is provided a system for supporting the creation of a template-based online analysis report, wherein the query creating unit sets a reference item of a dimension type among the selected reference items as a group in the query statement.

According to another aspect of the present invention, there is provided a template-based online analysis report creation support system, comprising: an interface screen (hereinafter referred to as a pivot design screen) capable of configuring a pivot table only by reference items of a selected template when one template is finally selected from the retrieved templates; Wherein the pivot design screen comprises an area (or item display area) for displaying reference items of the template and an area for displaying selected reference items (hereinafter referred to as a selection display area), and the selected reference The item area (or the selection display area) is divided into a column area, a row area, and a data area, and the report creating part automatically generates a pivot table when reference items are selected in the selection display area on the pivot design screen do.

According to another aspect of the present invention, there is provided a system for generating a template-based online analysis report, wherein the query generator automatically generates a query statement by automatically selecting a reference item using a keyword input from the template search unit.

Further, the present invention is characterized in that in the template-based online analysis report creation support system, the selection of the reference item is performed by a drag-and-drop method.

As described above, according to the template-based online analysis report creation support system according to the present invention, the table relationship and the reference item data generated in the past can be saved as a template and reused, It is possible to provide a very easy analysis environment in which an analysis report can be produced only by inputting a service environment or a keyword.

In addition, according to the template-based online analysis report creation support system according to the present invention, even if the table structure of the cube data storing the large-volume data is complicated, it is possible to easily and quickly analyze large- Effect is obtained.

BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1 is a configuration diagram of an entire system for implementing the present invention; Fig.
2 is a block diagram of a configuration of a template-based online analysis report creation support system according to an embodiment of the present invention;
3 is a table diagram of a template according to the present invention and an example of a reference item.
FIG. 4 is an example in which a template is formed into a database in accordance with an embodiment of the present invention.
5 is an example of a real-time template search screen of a template-based online analysis report creation support system according to an embodiment of the present invention.
6 is an example of a screen displaying a template search result of a template-based online analysis report creation support system according to an embodiment of the present invention.
7 is an example of a query design screen of a template-based online analysis report creation support system according to the present invention.
FIG. 8 is an example of a screen in which reference items are organized into hierarchical folders on a digital screen of a template-based online analysis report creation support system according to the present invention.
9 is an example of a pivot design screen of a template-based online analysis report creation support system according to the present invention.
10 is an example of a pivot report screen of a template-based online analysis report creation support system according to the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the present invention will be described in detail with reference to the drawings.

In the description of the present invention, the same parts are denoted by the same reference numerals, and repetitive description thereof will be omitted.

First, an example of the overall system configuration for carrying out the present invention will be described with reference to FIG. The template-based online analysis report creation support system 30 according to the present invention can be implemented as a server system on a network.

As shown in FIG. 1, the overall system for implementing the present invention comprises a client 20, a creation support server 30, and a data cube 60. In addition, the creation support server 30 may be configured by adding a database 60 for storing data such as meta templates.

The client 20 is a client program system installed in the user terminal 10 and has a user interface through a web browser. That is, the user performs a data analysis processing operation on-line via a screen interface such as a web browser or a web browser. At this time, the client 10 receives a command or the like of the user, executes the command, and displays the processing result on the screen or the web browser. On the other hand, the user terminal 10 is a computer terminal having a computing function such as a personal computer (PC), a PDA, and a smart phone.

In addition, the client 20 requests the creation support server 30 to perform an analysis processing on an online basis such as a meta template search, a data request, and a data analysis, and obtains the result from the server 30 and displays it on the web browser do. For example, when a keyword input window is displayed on a web browser and a keyword is input in the input window, a search result list based on the keyword is displayed as a combo box list in the input window.

The user terminal 10 and the creation support server 30 are connected to each other via a network so that the client 20 on the user terminal 10 can perform an analysis report creation operation on-line.

Next, the creation support server 30 is a server that processes online analysis processing (OLAP), receives a request for template search, data analysis, and the like from the client 20, processes the search or analysis request, To the client (20).

In particular, the authoring support server 30 fetches data stored in the data cube 60 using a query (or a data reference query statement) requesting the data. A query is a data manipulation language that describes a question or inquiry that occurs when retrieving or updating data stored in a database. In a database, a query acts as a kind of command. It is expressed in the form of a structured query language (SQL) of a relational database, but in some cases, it may be expressed in a format other than SQL.

In order to create a data reference query, the creation support server 30 establishes and defines a relationship between tables (or DB tables) in the data cube 60, and stores reference items (or column names) Select.

Preferably, the creation support server 30 includes a database 40 for storing data used by the server. The database 40 includes a template DB 41 for storing a meta template representing information on a table relationship and reference items for referring to data of the data cube, a search result DB 42 for storing search results such as a searched template, And a reference data DB 43 for storing data fetched from the data cube 60 according to a reference query constructed on the basis of the reference query. However, the configuration of the database 40 is only a preferred embodiment. In the development of a specific device, the database 40 may have a different structure in consideration of ease of access and retrieval, efficiency, and the like.

Next, the data cube 60 is a normal data warehouse or data cube for storing big data accumulated by a company or the like during business, and has a DBMS for managing data, and stores data, Of the tasks are performed through the query. In particular, the data cube 60 is a commercialized database, and performs a data query service using a general query function for processing data. In particular, the data cube 60 is a database for storing big data. Also, preferably, the data cube 60 may be comprised of a relational database (RDB).

Next, a configuration of a template-based online analysis report creation support system according to an embodiment of the present invention will be described with reference to FIG.

2, the template-based online analysis report creation support system 30 according to an embodiment of the present invention includes a template configuration unit 31, a template search unit 32, a query creation unit 33, And a report creating unit 34. [

The template constructing unit 31 constructs and stores a table relationship diagram and a reference item, which are created to refer to the data of the data cube 60, as templates (or meta). Preferably, the template is constructed in a database for searching by a keyword.

In one embodiment, the template data may be collected in real time. For example, a new table relationship diagram and a reference item for referring to data of the data cube 60 may be generated by modifying the retrieved template in the data analysis unit 34. [ At this time, if table relationships other than the stored templates and reference items are configured, these table relationships and reference items can be added as new template data.

Further, in another embodiment, the template data may be constructed by collecting data of table relationships and reference items created in other online analysis processing (OLAP).

As another embodiment, the user can directly generate the template data. That is, the user can directly select a DB table, establish a join relationship between the DB tables, and directly select items to be referred to, thereby forming a template. For example, the end user sets the table relationships of A, B, C, and D as in the example of Fig. 3, and sets the reference items as <title name>, <name>, < , "Address", "Address", "Address", and "Address_ City / Town", and stores the template as a template named "Personnel and Payroll Information".

Also, preferably, the template data may be extracted from a DB query statement (e.g., an SQL statement, etc.) that references the data cube 60. The reference item may be extracted from a reference item of the query statement (e.g., the reference items described in the SELECT statement), and the table relationship diagram may be extracted from the DB table referenced in the query statement and the field conditions therebetween.

Template data consists of table relationships and reference items.

The table relationship diagram is composed of a DB table and a join relationship. Table relationships are similar to normal ERD (Entity-Relationship Diagram). However, in order to refer to data of a specific purpose (data of a data cube), a join relation capable of automatically generating SQL by defining a join relation of a DB table is set in advance.

The DB table refers to a table configured in the data cube 60. The DB table is a normal database table, which is composed of a plurality of columns (or fields), and each data of the DB table has a value of each field.

A join relationship is a condition for joining between at least two DB tables, and is expressed as a condition between fields of DB tables. The join relationship is a join relationship in a normal database, and a detailed description thereof will be omitted.

Figure 3 illustrates a table relationship diagram. In Fig. 3, it is composed of four DB tables. That is, it is composed of four DB tables of <Employee>, <Salary>, <Address>, and <Work position>. And the relationship of joins has relationship between <staff-salary>, <staff-address>, and <staff-position>, respectively. In the <employee-salary> relationship, the employee field is the same, the <employee-address> relationship is the same in the address code field, and the <employee-position> is the same in the position code field.

Reference items are items for referring to data in the data cube 60, and are made up of field items of the DB table and derived items obtained by processing the field items. That is, the reference item is composed of a column name of a table selected by the user as a reference item, or a reference item (derived item) defined by a user using a column name or the like.

On the other hand, reference items are classified into a dimension type and a measure type. Preferably, if the value of the reference item (or column) is a character, it is designated as a dimension type, and if the value of the reference item is a number, it is designated as a measurement value type.

Each column of a table in an OLAP cube definition or DW (Datawarehouse) can be pre-categorized in the form of dimension and measure. In particular, dimensions provide structured label information. As described above, if the field (or column) of the DB table is set in the form of a dimension or measurement value in advance in the data cube 60, the format of the reference item is set according to the setting.

On the other hand, the measured value means an unaligned numerical value. In all cases, the string value is not a dimension, or a numeric value is not a measure. For example, an item called a product number is classified as a numerical value or a dimension type. In addition, when a string item is counted (for example, the number of registered users is a user name count), it should be classified in the measurement value format. The criterion to automatically classify is string or number, and the format of the reference item can be corrected by the user or the administrator.

3, column names <title name>, <name>, <citizen number 1>, <date>, <postal code>, <address_try>, and <address_state> , Column name <base rate>, and <allowance> are items of the measurement value format.

The reason for dividing a reference item into a dimension type and a measure type is that the measurement value becomes an aggregation for each dimension. In the definition of the reference item, the reference items of the measure type have the attribute of the aggregation function. Here, the group function refers to sum, min, max, avg, count, distinct count, and so on. Also, the data area of the pivot table displays the value calculated by the group function.

For example, if a reference item of two dimensional form selects a reference item of one measure type, the query statement (SQL) is generated as follows.

[Query statement 2]

Select dim1, dim2 sum (measure) from table

Group by dim1, dim2

In the example of FIG. 3, in the case of the <personnel and salary information> template, when only one <reference base> measurement reference item is selected, the result data becomes the base salary of all employees, and when the name (dimension) It becomes base sum sum by name. In addition, when the name (dimension), the year and month (dimension), and the basic level (measurement value) are selected, base rate data for each name and month can be retrieved.

On the other hand, only the columns referenced in the query to refer to the data in the data cube are selected as reference items. That is, not all columns of the DB table are set as reference items. In the example of FIG. 3, the reference items include the checkmarked fields in the DB table, i.e., <name name>, <name>, <resident number 1>, <month>, <postal code>, < _ City / county, <base rate>, <allowance>. <Subscriber number 2>, <Incident date>, <Department code> in the <Employee> table are not selected as reference items.

Next, a derived item is an operation on a column (or fields) of a DB table to generate an item that is not in the table as a derived item. A derived item is also a reference item, which is divided into a dimension format and a measurement format.

As an example of a reference item derived from a dimension value type, if there is a column of <year month> in the <period> table, it is possible to make <year>, <month>, etc. as a derivative item as follows.

 <Year>: substr (<month>, 1,4)

 <Month>: substr (<month>, 5,2)

Also, as an example of a reference item derived from a measurement value format, reference items using a calculation formula can be generated. For example, if there is a <volume> and <throughput> column in the DB table, you can create a <fault rate> column as a derived item through a formula.

<Rate of error>: <Production> / <Throughput> * 100

Preferably, the template constructing unit 31 constructs and stores reference items of the template as a table. Specifically, as shown in FIG. 4, the reference item table of the template includes a template name which is the name of the template, a reference item name which is the name of the reference item, a table name which is the name of the DB table, A form representing a value type, and a formula representing a corresponding calculation form in the case of a derivative item using a calculation formula.

Preferably, it is stored as a Formula attribute of the derived item. The stored formula is used as it is when you automatically generate the query (SQL) when you later recycle the template. On the other hand, formulas can be SQL grammatical formulas, or they can be managed with standardized formulas and automatically changed into SQL statements that match the type of data cube (or database). This is because the syntax of the functions provided for each type of DB may be different. For example, the substring function may be different for SUBSTR in Oracle (trademark ORACLE) and MID in MS-SQL.

Next, the template search unit 32 searches the template by the inputted keyword, and displays the searched templates.

The template retrieving unit 32 performs keyword retrieval on the names of the template of the template, the name of the reference item, the name of the DB table, the name of the column of the DB table referenced by the derived item, and the like. Perform keyword search by matching each name and keyword. The matching method uses a normal keyword search method. For example, a similarity matching method may be applied in keyword matching.

When a plurality of templates are searched by the input keyword, the template searching unit 32 displays the search result list in a high priority order by using a predetermined priority order.

Preferably, when the target to which the keyword is matched is the name of the template, the priority is set to be higher than other targets (e.g., names of reference items).

In addition, when a plurality of keywords are input, priority is set higher as the number of matching keywords increases. For example, when searching for two or more keywords such as <year month> and <sales organization name>, a template including all the reference items corresponding to the keywords is recommended as a priority and displayed.

In addition, the higher the number of times (or the number of views) the user has viewed from the searched templates, the higher the priority. If there are multiple templates that contain all the keywords, the most frequently viewed templates are sorted in order of priority.

On the other hand, the template search unit 32 can select a search target by the input of the user. Namely, it is possible to select only a part of the objects to be searched, such as the name of the template, the name of the reference item, the name of the DB table, and the name of the column of the DB table.

At this time, if the keyword is a column name of the table, it derives the column name and recommends the reference item name to be referred to. When the table name is targeted, the reference item name referring to the column in the corresponding table is displayed as a recommendation list.

As shown in FIG. 5, the template search unit 32 may display a search result list in real time when a keyword is input to the input window on the web in the user terminal 10, in an input window. In the example of FIG. 5, when the first <year> is input, template names included in the template most searched based on the search history of other users are sorted and prioritized in order of priority.

Alternatively, as shown in FIG. 6, if all of the keywords are input and the search command is finally input, the template search unit 32 can display the template name and the reference item name by dividing the search result into the templates.

In addition, the template search unit 32 may receive the query sentence desired by the user instead of the keyword, and may extract the keyword through morphological analysis of the query sentence. More preferably, the template search unit 32 can receive the query sentence as a voice, convert it into a text sentence through parsing, and analyze the sentence.

For example, a case in which a query sentence of &quot; information on sales performance by region by region 2013 &quot; is input is described. At this time, the query sentence can be recognized as text or voice. Keywords such as <2013>, <year>, <2013>, <region>, <product>, <sale>, and <sales performance> can be extracted by the morphological analysis of the query sentence.

Next, when one template is finally selected from among the retrieved templates, the query creating unit 33 displays an interface screen (hereinafter referred to as a query design screen) capable of configuring a query based only on the reference items of the selected template. In particular, the query design screen has a drag-and-drop interface.

As shown in Fig. 7, the query design screen comprises an area (hereinafter referred to as an item display area) for displaying reference items of the template and an area for displaying selected reference items (hereinafter referred to as a selection display area). The selected reference item area (or selection display area) is divided into a dimension type (dimension area) and a measurement value format (or data area). Preferably, the area of the selected reference item further comprises a filter area indicating a reference item selected by filtering.

In the query design screen, the reference items displayed in the item display area are selected by the drag and drop method, and the reference items selected in the selection display area are displayed.

When the reference items are selected in the selection display area on the query design screen, the query creation unit 33 automatically generates a query statement.

In particular, the query creation unit 33 can automatically generate a query statement using the keyword input by the template search unit 32. [ That is, it includes the input keyword, searches for similar reference items, and automatically selects the retrieved reference items.

For example, the case where the user inputs <name>, <month month>, and <base rate> in the template search unit 32 will be described. A query (SQL) is automatically generated with a template of the table relation having the keyword as a reference item. At this time, attributes of the reference items are grouped based on the dimension, measurement value, and group function defined in the template, and the data is searched for in the data cube by minimizing the number of data to the unique value of the dimension. The join syntax required for an SQL statement requires that only the table with the selected reference items be indexed by the minimum spanning tree algorithm in the relationship diagram of the relation template even if several hundred tables are defined in the table relation template SQL is generated as a join.

In the example of FIG. 7, a query statement (SQL) is automatically generated automatically as shown below according to the table relationship diagram of the template, and the data of the data cube 60 can be automatically inquired.

[Query statement]

SELECT B. Name, C. Year, sum (C. Basic) from F_employee B, F_SALARY C

Where b.

Group by B. Name, C. Year

It is assumed that the keyword search request is received from the template search unit 32 with the contents of "sales performance information for each product by region 2013 &quot;. The reference item is classified by the morphological analysis of the query sentence, and the year 2013 is selected as the filter item, the filter condition is set as the year 2013, the <region> and <product> You can create an analysis report by searching for a table-related template that has a measurement value item.

In addition, only the reference items of the template are displayed on the item display screen of the query design screen. That is, column names other than the reference items in the DB table including the reference item are not displayed. This is because there may be information in the DB table that should not be disclosed to the end user. That is, data security can be enhanced by the present invention.

The reference items of the template may be hierarchically organized into a logical bundle (folder) that does not exist in the actual table, and may include a function of separating and displaying the items so that the user can easily select the items. In the example of FIG. 8, logical groups such as <Dimension>, <organization>, <period>, <product>, and <security> are divided into folders and provided to the user so that reference items can be selected.

Next, when one template is finally selected from among the searched templates, the report creating unit 34 displays an interface screen (hereinafter referred to as a pivot design screen) capable of configuring a pivot table based only on the reference items of the selected template. In particular, the pivot design screen has a drag-and-drop interface.

As shown in Fig. 9, the pivot design screen comprises an area (or item display area) for displaying reference items of the template and an area for displaying selected reference items (hereinafter referred to as a selection display area). The selected reference item area (or selection display area) is divided into a column area, a row area, and a data area. Or further into page areas.

The value of the selected reference item in the page area provides the ability to filter the values displayed in the currently displayed row, column, and data area. For example, if you place the "month" reference item in the page area, you can select "December 2013" in the page area to check only the data of the corresponding month. .

In the pivot design screen, the reference items displayed in the item display area are selected by the drag and drop method, and the reference items selected in the selection display area are displayed.

The column area, the row area, and the data area correspond to columns, rows, and data fields, respectively, in the pivot table. That is, the reference items selected as the column area, the row area, and the data area are defined as columns, rows, and data fields of the pivot table, respectively. Since the pivot table uses a normal pivot table (for example, a pivot table in Microsoft's Excel) method, a detailed description will be omitted.

At this time, only the reference items of the dimensional format can be selected and displayed in the column area and the row area, and only the reference items of the measurement value format can be selected and displayed in the data area.

The report creating unit 34 automatically generates a pivot table or a pivot report when reference items are selected in the selection display area on the pivot design screen. An example of a pivot report is shown in FIG.

Among the reference items selected by the user, reference items of the measurement type are automatically arranged in the data area, and two of the dimension item values are automatically arranged in the row area, one in the column area and the remaining dimensions in the page area. With this arrangement, a pivot report is automatically generated.

After automatic generation, OLAP analysis can be performed by changing the layout to a desired layout by using a method provided by other tools. If you want to add a new item and analyze it later, you can change it to edit mode, and you can search for a keyword and add a reference item by automatically displaying a reference item display area (display window).

The invention made by the present inventors has been described concretely with reference to the embodiments. However, it is needless to say that the present invention is not limited to the embodiments, and that various changes can be made without departing from the gist of the present invention.

10: user terminal 20: client
30: creation support server 31:
32: template search unit 33: data construction unit
34: Data analysis section
40: Database 41: Template DB
42: Search result DB 43: Reference data DB
60: Data Cube

Claims (12)

A template-based online analysis report creation support system connected to a user terminal installed with a client and connected to a data cube storing data, the system comprising:
A template constructing unit for constructing and storing a table relationship diagram and a reference item created for referring to data of a data cube as a template; And
And a template search unit for searching for a template by a keyword inputted by the client and displaying the searched templates,
Wherein the table relationship diagram is constituted by a join relationship between a DB table of the data cube and a DB table, the reference item is composed of a field item of the DB table and a derivation item defined by the field items,
Wherein the template search unit searches for the keyword based on at least one of a name of the template, a name of the DB table, a name of the reference item, and a name of a field item defining the reference item Template based online analysis report creation support system.
The method according to claim 1,
Wherein the template constructing unit forms the template by collecting data of a table relationship diagram and reference items created in online analysis processing (OLAP).
The method according to claim 1,
Wherein the template constructing unit is configured to construct the template from a query sentence generated in online analysis processing (OLAP), extract a reference item of the template from a reference item of the query query, and generate a DB table referenced in the query statement, Extracts a table relationship diagram of the template from the template-based online analysis report creation support system.
The method according to claim 1,
Wherein the template search unit displays a search result list in a high priority order by a predetermined priority order when the plurality of templates are searched.
5. The method of claim 4,
The template search unit may set the priority of the template to be higher than the other candidates when the keyword matches the template, or may set the priority to be higher as the number of times viewed by the user increases, or may be matched when a plurality of keywords are input Wherein the priority level is set higher as the number of keywords increases.
The method according to claim 1,
Wherein the template search unit receives a query sentence instead of a keyword and extracts a keyword from the query sentence through morphological analysis.
The method according to claim 1,
Wherein the reference item is defined by being classified into a dimension format and a measurement value format.
8. The method of claim 7,
Further comprising a query creating unit for displaying an interface screen (hereinafter referred to as a query design screen) in which a query can be composed only of the reference items of the selected template when one template is finally selected from the retrieved templates,
The query design screen is composed of an area (hereinafter referred to as an item display area) for displaying reference items of a template and an area for displaying selected reference items (hereinafter referred to as a selection display area)
Wherein the query creating unit automatically generates a query statement that refers to the reference items in the selection display area when the reference items are selected in the selection display area on the query design screen.
9. The method of claim 8,
Wherein the query creating unit sets a reference item of a dimension type among the selected reference items as a group in the query statement.
10. The method of claim 9,
Further comprising a report creator for displaying an interface screen (hereinafter referred to as a pivot design screen) capable of configuring a pivot table based on only the reference items of the selected template when one template is finally selected from the searched templates,
The pivot design screen comprises an area (or item display area) for displaying reference items of the template and an area for displaying selected reference items (hereinafter referred to as a selection display area), and a selected reference item area A column region, a row region, and a data region,
Wherein the report creating unit automatically generates a pivot table when reference items are selected in the selection display area on the pivot design screen.
9. The method of claim 8,
Wherein the query creating unit automatically generates a query statement by automatically selecting a reference item using the keyword input from the template searching unit.
11. The method according to claim 8 or 10,
Wherein the selection of the reference item is performed by a drag-and-drop method.

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