Designing Stories in SAP Analytics Cloud (SACS 21): Selecting a Data Source

 

🎯 Objective

After completing this lesson, you’ll be able to:

  • Describe the types of data sources used in SAP Analytics Cloud stories.

🔗 Types of Data Sources in SAP Analytics Cloud

📁 1. Datasets

Datasets are created when importing data from:

  • Files (e.g., Excel, CSV)

  • Outside data sources (non-SAP or SAP systems without models)

🧩 Two Types of Datasets:

TypeDescription
EmbeddedUnique to the story, can change data source, not shareable
PublicShareable across stories, source cannot be changed once created

🔒 Both types support access security (who can use the dataset), but no column-level security.

⚠️ Limitations:

  • No scheduled refresh

  • Manual re-import is required for updates

  • Transformations are lost when converting an embedded dataset into a model

  • Public datasets cannot be converted into models

🧰 2. Models

Models are reusable, structured data sources designed for enterprise-level reporting.

  • Created from:

    • Imported data

    • Live data sources (e.g., SAP BW, SAP HANA)

  • Support column-level security, scheduling, calculated measures, and dimensions

  • Models allow more governance, consistency, and security

🌐 3. Live Data Connections

Used when accessing real-time data directly from an external system (no data import).

  • Examples: SAP BW/4HANA, SAP HANA, SAP Datasphere

  • Data remains in the source system

  • No data preparation possible within SAC

📌 Example: Using SAP Datasphere, you access live models stored in defined spaces. No transformation possible in SAC.

🔧 Data Preparation

Only available for imported data (not live sources). Allows:

  • Data cleaning

  • Renaming columns

  • Adding calculated fields

  • Using basic or advanced transformation editors

🔌 Administrator Role in Data Source Setup

  • SAC administrators are responsible for creating connections to:

    • SAP systems (BW, HANA, Datasphere, etc.)

    • Non-SAP sources (Google BigQuery, Snowflake, etc.)

  • These connections are then used to create datasets or models for stories.

🗂️ Summary Table

Source TypeEditable?Refreshable?Shareable?Transformation?Notes
Embedded DatasetYesManual onlyNoYesCan convert to model (lose transforms)
Public DatasetNoManual onlyYesYesSource cannot be changed
Model (Imported)YesScheduledYesYesFull modeling features
Live ConnectionNoReal-timeYesNoReal-time performance, no prep

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