Within the time frame of 2023 QRC3, several new calculation view features have been released in SAP HANA Cloud that can be used with SAP Business Application Studio. Some of these features are highlighted below. You can find examples that illustrate the individual features here. An overview of features of other releases can be found here.
MDS Cubes
MDS Cubes represent submodels of calculation views. MDS Cubes are explicitly loaded via an
API so that materialized data can be queried. Data in MDS Cubes are stored in a highly-optimized way. This optimized data structure can be leveraged in analytical reporting that is based on MDS metadata, such as SAP Analytics Cloud. Using MDS Cubes is an option to
speed up analytical queries.
Example MDS Cube
Data in MDS Cubes reflect the state at the time the MDS Cube was loaded. Only data that were visible to the user who loaded the MDS Cube are included. Loaded data is not automatically updated. This can lead to differences when comparing reporting based on MDS Cubes and based on the online calculation view. To reflect data changes in reporting, it is necessary to manually re-load the MDS Cube.
If a calculation view feature is not supported by MDS Cubes, the tab MDS Cubes is inactive, and a list of feature(s) is displayed that prevents the usage of MDS Cubes. Removing these feature(s) from the calculation view activates the MDS Cubes tab.
If an MDS Cube is already defined in a calculation view, features of the calculation view that are not supported by MDS Cubes are deactivated. When hovering over the feature you will be informed that it is inactive due to the existence of an MDS Cube definition. If the MDS Cube definition is deleted, the feature will become available again.
Leverage MDS Cubes to speed-up SAP Analytics Cloud queries!
Propagate Column Name Changes
If a column name should be changed throughout the calculation view stack within the current HDI container the option “Propagate recursively in Consuming Views” of the “Rename & Adjust References” dialog can be used.
Propagate Column Renaming
If the option is checked the column will be renamed recursively throughout the calculation view stack.
Potential warnings such as that a mapped column name will be overwritten are shown:
Warning During Column Renaming
If renaming would lead to a conflict such as non-unique column names an error is shown and renaming is aborted:
Error During Column Renaming
If the option is unchecked only the input columns of directly dependent calculation views are renamed.
Use the renaming option to simplify refactoring!
Where-Used Functionality
Use Where Used Inside Calculation View to understand where a certain column is used in the current calculation view:
Where Used Inside Icon
Use Where Used Outside Current View to understand the usage of a column, input parameter or variable in other objects inside the same HDI container:
Where Used Outside Current View Icon
The dependencies within the same HDI container will then be listed:
Output Example Where-Used
Gain additional insights into column usage before starting refactoring of your columns!
Restrictions Based on Measures
Restrictions of restricted columns can now also be placed on measures. This can be used for example, to filter out outlier values before aggregation.
Define Restrictions on Measures
Graphical support of user-defined functions with multiple return values
The expression editor now displays the parameters that are returned by a function if multiple values are returned. Use the graphical support to choose which parameter value should be used in the expression:
Example User Defined Function With Multiple Return Values
Flexible Specification of T009 and T009B data during fiscal calendar data generation
When generating fiscal calendar data, it is now possible to specify tables or synonyms that point to tables to read the data that are expected in tables T009 and T009B. The structure of the target tables have to match the structure of the T009/B tables:
Example Data Generation Fiscal Calendar
This provides more flexibility and makes re-use of table data easier.
