Introduction
To build impactful stories in SAP Analytics Cloud (SAC), you need to start with the right data. This is where data models come in. A model serves as the structured data foundation behind every chart, table, or calculation you create in your story.Â
What is a Data Model in SAC?
A data model in SAC defines how data is structured, including dimensions (like region or product), measures (like revenue or quantity), hierarchies, and calculations. It can be based on:Â
- Acquired data (imported into SAC)Â
- Live data connections (such as SAP BW, SAP HANA, or other sources)Â
Models provide the underlying logic and fields that feed into your visualizations.Â
How to Add a Data Model to a Story
Option 1: When Creating a New Story
- Navigate to the Create > Story option in the SAC menu.Â
- After selecting Blank Canvas or Template, you’ll be prompted to add a model.Â
- Choose an existing model from your workspace or connect to a new data source.Â
Option 2: From Within an Existing Story
- Open your story in Edit mode.Â
- In the top toolbar, click the Add Data or Add Model option.Â
- Select one or more models to add. You can add multiple models for blending or filtering across different datasets.Â
- The attached models are visible in the Add New Data dropdown in the menuÂ
Tip
- If you use a chart or table before adding a model, SAC will automatically prompt you to select one before continuing
Replace or Remove a Data Model
If your model structure changes or if you want to switch to a more updated version:Â
- Go to Add New Data > Select the model > Select [ Replace, Remove, or set as default]Â
- You can choose to Replace Model, which will update widgets that are compatible with the new structure.Â
- To remove a model entirely, make sure no widgets are using it and select Remove Model from the same menu..Â
Working with Multiple Models
You can add multiple models in a single story to support:Â
- Blending: Combine data across models to create unified charts.Â
- Linked Dimensions: Use common dimensions (like time or region) to enable cross-model filtering.Â
Be aware that performance may vary depending on the size and type of models used (especially with live connections).Â
Best Practices
- Name your models clearly to avoid confusion when using multiple datasets.Â
- Pre-clean your data in the model layer before connecting it to your story.Â
- For live models, test response time and widget rendering early to avoid slow story loading.Â
- If you plan to use blending or filters across models, ensure consistent dimension naming and hierarchy setup.Â
