Using the Model Size Statistics and Analysis Tool

Objective

After completing this lesson, you will be able to describe how the Model Size Statistics and Analytis Tool can be used to analyze performance.

Model Size Statistics and Analysis Tool

The Model Size Statistics and Analysis tool is a predefined story that serves as a central overview for monitoring and analyzing data size, allowing you to able to take an informed action on data volumes before they become a critical issue.

Answer questions such as:

  • Which of our hundreds of models are the largest and contributing most to our data footprint?
  • Is the growth coming from transaction data, or is the audit log expanding rapidly?
  • In our largest models, which specific versions (e.g., Forecast, Budget) are consuming the most space?

Access the Tool

You can launch the tool by going to PerformanceModel Size Statistics and Analysis as shown here.

Menu path for the SAP Analytics Cloud Model Size Statistics and Analysis tool.

Key KPIs

The Key KPIs section provides you with overview information for models, dimensions, and total record size.

Key KPIs section of the Model Size Statistics and Analysis tool.

Analysis

The Analysis section presents a dashboard with a clear, ranked list of your top 30 models/dimensions by total record count, showing you exactly where the data is located.

When you select a model or dimension in the top 30 chart, the dashboard reveals a breakdown by data category, providing you with the understanding of the nature of your model's size. You can see if it's growing because of massive data loads or because of the audit trail from frequent planning activities. If you select a large planning model, you can see which versions are the biggest contributors, providing you with the information you need to target specific versions for cleanup or archiving.

Analysis section of the Model Size Statistics and Analysis tool.

Details

In the Details section, you can view historical charts that track record growth over time. More importantly, it overlays this data with import jobs and version publish events. You can visually correlate a spike in data with a specific data load or a major publishing cycle, creating a clear cause-and-effect relationship. This helps you understand why and when your data is growing, enabling you to optimize your data management processes.

Details section of the Model Size Statistics and Analysis tool.