The black box of data-actions has been opened: tracing capability is now available!

SAP Analytics Cloud (SAC) is SAP’s cloud-based Business Intelligence platform that provides a range of analytics and reporting-tools. It is a fast-evolving product, which gets updated frequently.

In this blog, Karlijn van den Hombergh and Kris van Brouwershaven explain the main takeaways for the latest release for SAP Analytics Cloud.

February 17th marked the first 2023 quarterly release for SAP Analytics Cloud (QRC1). For a detailed overview of the release cycle, please refer to an earlier McCoy blog, which can be found here.

Overall, the newest SAP Analytics Cloud release offers a range of exciting new features and enhancements that can help organizations make better, data-driven decisions. This blog explores the most exciting features, focusing on:

• The introduction of the new feature for Enterprise Planning.

• The optimized Forecasting Multi-Action.

• Improved user experience for Data Analyzer.

Enterprise Planning – Tracing Capability

The gem of this Q1 release will – for the Planning Experts – doubtlessly be the new debugging tool of data action tracing, allowing users to set their preferred trace points in a data action and then check intermediate results at these trace points after execution of the data action.
The tracing side panel will show all information about the trace that was set.
The ‘Show Table’ button will expose a detailed table of intermediate results for a specific tracer, allowing the user to filter the data as desired. Navigating the trace points in sequence will even highlight the data changing in this table.
Given the increasing complexity of data actions and the essential role they have in planning, this new tracing feature thus represents a big step forward in efficiently using SAC Planning.

Predictive Planning - Saving forecast values for past periods.

The newest release contains even more new planning related features.
As forecasting by machine learning has become an important aspect of planning cycles, there is great value to be found in the new multi-action feature. It is now possible to generate previous forecasting results using the predictive node in a multi action. A simple switch in the Predictive Step-window saves forecasting results generated in previous periods.
This feature can be most useful when evaluating the quality of predictive models, allowing the user to create a performance metric in stories.

Data Analyzer

Enabling Data Analyzer in an optimized story automatically introduces the next improvement of this 2023.01 release; opening the Data Analyzer from a table widget in a story. All current filters from the story or widget will be maintained and brought across, automatically appearing in the filter panel from the Data Analyzer.
The Data Analyzer itself has received a (UI) upgrade too, with an updated toolbar containing new export functions and the possibility to activate and de-activate BEx conditions. Table adjustments have become a whole lot easier now that drag-and-drop is available, allowing users to move measures and dimensions, both within the current axis and to the other axis. Additionally, filters can now be created through the selection of members in the table and then selecting the new ‘Filter Members’ feature.
The previous data analyzer, now known as classic insights, can still be accessed and is available through the file repository.

Interested?

Are you interested in learning more about SAP Analytics Cloud or looking for a team to help you put this and other features in SAP Analytics Cloud to use? Please reach out to Roel van Bommel or Joury Jonkergouw for more information!

Learn More

If you want to learn even more about the latest Data Analyzer-update, read this blog written by our expert. blog Sander Huisman over Data Analyzernl
If you want to learn more about the latest SAC-update, click here.
If you want to learn the main differences between SAP Analytics Cloud and Power BI, click here.
If you want to learn how to use Power BI on SAP, check out this McCoy TV Episode.
If you want to learn how to use the Data Analyzer, check out this McCoy TV Episode.