About this task
In this example, we create a basic column analysis using simple statistics and generate an evolution report on this analysis. This evolution report provides us with the evolution of the simple statistics indicators through comparing current and historical statistics to determine the improvement or degradation of the data in the analyzed column.
Prerequisite(s):At least one type of analysis has already been created in the Profiling perspective of the studio.
To create an evolution report on a column analysis, do the following:
Follow the steps outlined in Creating a basic analysis on a database column to create a simple
In this analysis, you analyze one column using the Row Count, Blank Count and Distinct Count indicators.
Right-click the analysis name in the DQ
Repository tree view and select New
Report from the contextual menu.
The report editor is displayed with the selected analysis already listed in the Analysis List.
- In the Analysis list view and from the Template type list, select Evolution as the type for the report you want to generate.
- Select the Refresh All check box to refresh the listed analysis before generating the report.
- Click Generated Report Settings to display the corresponding view, and then define the settings for the generated report.
- Click Presentation Settings to open the corresponding view, and then personalize the presentation settings for the generated report.
Click Database Connection Settings and set
the connection parameters to the database where you want to store the report
For further information about creating a report, see Creating a report on specific analyses.
- Click the save icon on the toolbar of the report editor to save the report settings.
From the toolbar of the open report editor, click to generate the report file.
The listed analysis is executed, the data is historized in the report database and finally a report document is generated in the selected format (pdf, html, xsl or xml). Every time you generate this report, it will compare the current and historical statistics to determine the improvement or degradation of the data in the analyzed column.
In every evolution report, you will have two graphics: the first indicates the change in the statistics and the second indicates the percentage of that change.
The above report then tracks the evolution through time of the row count, distinct count and blank count of the data records in the column.