Using Data Tables you can show and aggregate data in a table format. You can aggregate on multiple dimensions and look at different measures (e.g., summary of per unit values).

 For Data Tables, there are hardcoded limits of maximum 100,000 displayed rows and 8 'Group by' levels. The row limit can be changed using the application property paDataAnalyzerMaxRows. If you need to show more rows in a dashboard and it is just for paged display, Analytics query should be used instead.

 See also a comparison with Rollups which are somewhat similar to Data Tables.

Specify Data Table Details

To specify a Data Table:

1. Choose a Datamart from the Data Source drop-down list. It can be a Datamart, Simulation Datamart, Rollup or Optimization Model (DMT tables organized by Models to which they belong).

2. Select a Currency to which money data will be converted.

3. You can set up the Generic filter (all dimensions, dates and values):

   1. Click Add Generic Filter, the Generic Filter dialog will open.

   2. Specify the filter criteria. You can combine individual rules with groups of rules as clauses and subclauses.

   3. Click Apply.

4. You can create an Aggregation filter that allows you to filter the Datamart query results, i.e., to determine, which values will be shown in the table.

5. Product filter allows you to select products from the drop-down list or filter by all attributes from the product master data. You can use the quick filters under the table header, set up an advanced filter or select an attribute value in the table, which selects all products with the same attribute value. Attributes that are not available for filtering are grayed out.

6. Customer filter allows you to select customers from the drop-down list or filter by all attributes from the customer master data. You can use the quick filters under the table header, set up an advanced filter or select an attribute value in the table, which selects all customers with the same attribute value. Attributes that are not available for filtering are grayed out. Only the filtered data will be used in the analysis.

7. You can set up a Dimension filter:

   1. Select the filter dimension from the drop down list.

   2. Select the values to filter by.

   3. Add more dimensions if required. In all subsequent filters you will only be able to select values complying with all previous filters.

8. Determine different 'Group by' levels. Click Add Group By and select a value from the drop-down list. You can add more than one 'Group by' level. You can reorder the levels by drag and drop.
   You can switch on or off the grouping by using the Group/Ungroup icons. This setting is remembered when you save the table.

9. Click Add Measure to add a measure in the Data Table.

   1. Select the dimension / measure from the drop-down list.

   2. Specify the value. The selectable options depend on the data type. For details see Data Calculation Options.

10. (Optional) Click Add Series to be able to compare this data table with other data series. The selection of Data Source, all filters and the settings from the Data Display Options will be copied to the new series from Series 1. The maximum number of series in a Data Table is 10.

11. (Optional) In a configuration with multiple data series, you can compare series by creating a Join series. Set the relation (joining key) between the added data series and the base series. Note that series are always joined to the base Series 1, so you cannot compare, for example, Series 2 and 3. You can define up to 4 Join series. See Accelerate Actionable Insights for configuration examples.

12. Click the Apply and Refresh button or the Refresh icon on the toolbar to update the chart.

Group Data

It is possible to group the table rows and save the grouping to the logic, so that next time you open the table or when you add it to a Dashboard, the table rows are kept grouped.

To set the grouping, enable Group data by default on the Options tab.

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