This is the documentation for Clover Club 12.0.
Documentation for the upcoming version Rampur 13.0 can be found here.

Rollups

Rollups are persisted Analytics queries aggregating measures along one or more dimensions.

Comparison with Data Tables

Rollups and Data Tables have a certain functionality overlap. They both show rows contained in Data Feeds, Data Sources or Datamarts but the form and other related features are slightly different.  

Area

Rollup

Data Table

Area

Rollup

Data Table

Displayed data

Shows the data in an aggregated form.

Rollups do not have to load all the data at once (the browser downloads approx. 300 rows in one go and as you scroll down, it fetches another batch of rows only when needed).

Shows the lowest level rows. 

Data Tables can do aggregation too but they need to load all the data in the browser to be able to show it.

Customization



Can be more customized (e.g., using a dictionary).

Comparison tools 

Has built-in pivot and comparison support. 



Performance

Loads large amounts of data faster.

But pivoting can increase the query time significantly.

It is slow when loading more than just a few 100s of rows.

Data Source creation

You can create a Data Source modeled on a Rollup, in which you can (schedule to) load data from the Rollup query ('sort of a materialized rollup').



Managing Rollups

To create a new Rollup:

  1. Select a Datamart from the Data Source drop-down list.

  2. Create a query by selecting fields in the following sections:

    1. Generic Filter – Specify the filter criteria. You can combine individual rules with groups of rules as clauses and subclauses.

    2. Filters – Allows you to filter by all attributes from the product and customer master data.

    3. Group By section, defining the dimensions along which to roll up the projected measures. (See also a note on Integers as dimensions.)

    4. Measures section, where additionally an aggregation function can be specified to complete the query definition. For details see Data Calculation Options (note that not all options are supported by Rollups) and Number Formatting.
      Setting up either a group by or a measure is mandatory. 

  3. At any point where the query under construction is valid, it can be saved by clicking the Save Rollup button. You can save it as 'private' (visible only to you) or 'published' (visible to all users but only you or users with Manage Saved Rollups role can edit/delete it) or 'open for all' (visible and editable by any user).
    The saved Rollup will be available from the Load Rollup dialog under the assigned Label.

  4. Click the Apply and Refresh button and inspect the results in the data section. For queries on large data sources, this can take several minutes.

To open an existing Rollup, click Load Rollup and select one from the list. Rollups can also be deleted in this dialog.

To change the order of columns in the results section, change the order of the fields in the Group by and Measures sections by drag and drop.

All layout customizations can be saved as a preference.

 To be able to save Rollups, you must have the Manage Saved Rollups user role assigned.

Pivot & Compare

You will often need to compare data for different periods, regions etc. In the following example, we aggregate sales numbers along region and year. By choosing the Invoice Year as the Pivot, it is now easier to compare results for subsequent years:

Note that the total number of rows of the source field selected as pivot must be 500 or fewer as the number of pivot columns is limited to 500.

When you have a pivot selected, you can, in addition, check the Compare option against a measure. The query will then calculate and return the delta of the aggregated measure between the different periods:

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