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What's New: 2023.07

We have some great news to share with you. The Widget Analysis feature will be further updated to include information on Planning Versions that are used in the Widget.

This enhancement will provide content creators and planning users with critical information necessary for optimal performance while working on planning data. This new information will be presented in the existing Widget Analysis Dialog in a new tab.

By incorporating Planning Versions information into the Widget Analysis feature, users will be empowered to work faster and more efficiently, resulting in better outcomes for their projects. We are confident that this update will further improve the user experience of our Widget Analysis feature.

What's New: 2023.06

We are pleased to announce that we will be enhancing our query analysis feature to Widget Analysis, which will provide users with additional performance insights.

As part of our ongoing efforts to improve the performance of our Story Designer tool, we introduced the Backend Query Analysis feature in version 2022.15. This feature provided users with information on why their visualizations were slow to render from a query perspective.

Building on this functionality, we are now adding timings for the frontend, network, and backend to give users even more insight into potential performance issues that may arise from these areas. By analyzing and understanding the client and network runtimes, users can optimize their visualizations for better performance.

We believe that the Widget Analysis feature will be an important tool for content creators and designers who want to optimize their visualizations for the best possible user experience.


Starting with Wave 2022.15 release of SAP Analytics Cloud we introduce the "Backend Query Analysis"

The motivation behind the Query Analysis on widget level is simple. During the design phase of Stories in SAP Analytics Cloud (SAC), developers sometimes have to deal with a high overall complexity. This complexity relies not only on the scope of the business requirements but also on the technical details and requirements of their implementation in SAC.

A well adopted Story meets, among others, two criteria:

  • Data is well-prepared

  • Story is well-performing

We focus in this blogpost on the latter. To design a well-performing story it is helpful for the developer to get immediate feedback about each widgets performance. The importance of this feedback is proportional to the complexity of the Story design as it is getting more difficult to maintain the overview.

Among other scenarios, there are three performance factors that you should be aware of:

  • Performance of the client

  • Performance of the network

  • Performance of the widgets

While client and network performance are addressed in the SAP Analytics Cloud Performance Benchmark, SAC is considered by some people as a blackbox in regards to the widget's performance. We acknowledged the need to provide additional information in SAC, to help the designers to understand how the widget design affects the query performance and how they can reach the most efficient implementation. This information about the widget's query runtime in the backend system was missing. This is something that we introduce now by and by, the information of the query performance itself.

First we show widgets that have a backend runtime of more than one second and show what has been reported by the backend system as potential factors that might contribute to that runtime.

Content Overview

The query analysis will be available if:

  • the query runtime in the backed system was greater than 1s

  • the Story is in edit mode

  • Classic Mode

    • Table

    • Value Driver Tree (VDT)

  • Optimized Design Mode

    • Chart

    • Table

    • VDT

The query analysis is accessible via:

  • Classic Design Mode

    • Table: Context Menu/ Show Performance Analysis

    • VDT: Context Menu/ Show Performance Analysis

  • Optimized Design Mode

    • Chart: Context Menu/ Applied to Chart/ Errors and Warnings

    • Table: Context Menu/ Show Performance Analysis (design will be adopted according to chart)

    • VDT: Context Menu/ Show Performance Analysis (design will be adopted according to chart)

  • Table feature:

    • warning icon at the table


Query analysis aims to provide additional support to both, the Story designer and the query designer. It is not meant to be the final, complete or one and only answer, but a large piece on the way to solve the whole "puzzle".

Query analysis on widget level should be used together with other tooling, reporting and the documentation (best practices) in SAC like:

  • Identify SAC Stories and Analytic Applications that have the highest performance impact in the backend system

  • Analyze Backend Runtime Distribution of problematic scenarios

  • Use Performance Analysis Tool for workflow analysis of these problematic scenarios and identify time consuming Widgets

  • Identify most used Stories and Analytic Applications

  • Analyze workflows of problematic scenarios

  • Identify problematic widgets within these workflows

  • Use Model SAC_PERFORMANCE_E2E (Files/ System/ Common/ SAC Content) to analyze Entry Page and navigation within problematic Story to be able to redesign and optimize


  1. Hana / MDS

  2. BW / InA

  3. Many Calculations resulting in 30s query processing time


  • More information for InA and additional SAP Notes and recommendations for how to improve performance in dialogue

  • More information for MDS and additional SAP Notes and recommendations for how to improve performance in dialogue

  • Consideration of additional information for planning specific details

  • Widget Analysis as next step of query analysis adding client and network information to the dialogue

Prerequisite SAP Notes