SAP Datasphere – Interview Cheatsheet


1. Core Concepts

What is SAP Datasphere?

  • SAP Datasphere = SAP’s unified data management + data warehousing + data modeling platform in SAP BTP.
  • Successor to SAP Data Warehouse Cloud (DWC).
  • Combines semantic modeling + virtualization + governance + cataloging.

Key Layers

  1. Data Integration Layer – Data flows, connections, replication.
  2. Data Modeling Layer – Views, entities, analytical models.
  3. Business Modeling Layer – BW-like semantics.
  4. Consumption Layer – BI tools like SAC, Power BI, Tableau.

2. Key Components

a) Spaces

  • Logical containers for data modeling.
  • Allow quota management (memory, storage).
  • Enable decentralized modeling and data governance.

b) Connections

  • Connect to SAP & non-SAP sources:
    • SAP S/4HANA
    • SAP BW/4HANA
    • SAP ECC
    • JDBC, OData, Data Federation
  • Types: Cloud, On-Premise via DP Agent, Live, Remote Table Replication

c) Data Builder

Used for:

  • Creating Tables, Views, Graphical Views, SQL Views
  • Remote tables
  • Data Flows
  • Business entities

d) Business Builder

  • Semantic modeling layer for:
    • Business Entities
    • Business Data Models
    • Analytical Models
  • Uses rich metadata: consumption behavior, measures, attributes.

e) Datasphere Catalog

  • Enterprise-wide metadata discovery
  • Lineage and impact analysis
  • Classification & governance integration

3. Datasphere vs BW/4HANA

FeatureSAP BW/4HANASAP Datasphere
ModelingRigid / IT-drivenFederated & business-driven
StorageRequires data loadingSupports virtualization via remote tables
SemanticsInfoObjects, ADSOsBusiness Entities, BDM
IntegrationMostly SAPSAP + Non-SAP cloud-native
ConsumptionBEx/SACSAC, Power BI, Tableau, Python

4. Datasphere Modeling

Model Types

  1. Tables
  2. Views
    • Graphical
    • SQL
  3. Analytical Models (replacement for BW Queries)
  4. Business Entities
  5. Relational Datasets

Key Concepts

  • Remote Table: Virtualized data from source.
  • Replication Flow: Load + sync data into Datasphere.
  • Data Flow: ETL transformation pipeline.
  • Analytical Model = Measures + Associations + Dimensions.

5. Integration

SAP S/4HANA → Datasphere

  • Live access via InA protocol
  • Remote tables via ODP
  • Replication flows (Change Data Capture)

SAP BW → Datasphere

  • BW Bridge
  • Import InfoProvider metadata
  • Migrate BW queries → Datasphere Analytical Models

3rd Party Tools

  • Tableau
  • Power BI
  • Databricks
  • Snowflake
  • JDBC / OData connections

6. Security & Governance

  • Role-based privileges
  • Space-level access
  • Connection credential policies
  • Data masking
  • Lineage tracking

Key Objects:

  • Technical Roles (Admin, Modeler, Viewer)
  • Business Roles
  • Row-level security in Analytical Models

7. Performance Optimization

  1. Push-down of SQL to remote sources
  2. Use of caching
  3. Denormalizing models where necessary
  4. Using replication for high-performance analytical workloads
  5. Optimized joins using associations instead of unions
  6. Columnar in-memory storage

8. Common Real-Time Scenario Questions

1. How do you model data from multiple SAP/Non-SAP systems?

  • Use Remote Tables → Combine with Graphical or SQL Views → Publish as Business Entity → Build Analytical Model.

2. How to migrate BW models to Datasphere?

  • Use BW Bridge
  • Migrate InfoProviders → Build semantic layer in Business Builder
  • Replace BEx Queries with Analytical Models

3. When to choose replication vs virtualization?

  • Replication: High performance reporting, heavy transformations
  • Virtualization: Real-time data access, minimal storage

4. How does Datasphere ensure governance?

  • Metadata catalog
  • Data lineage
  • Classification & tagging
  • Semantic-rich Business Entities

9. Most Frequently Asked Interview Questions

  1. What is SAP Datasphere?
  2. Explain Spaces and why they are used.
  3. Difference between Data Builder and Business Builder.
  4. What is an Analytical Model?
  5. What are Remote Tables?
  6. What is BW Bridge?
  7. Difference between Datasphere and BW/4HANA.
  8. What is a Replication Flow?
  9. When to use Data Flow vs Replication Flow?
  10. How do you implement row-level security?
  11. What is the role of the Catalog?
  12. What are Business Data Models?
  13. Difference between associations and joins.
  14. How does Datasphere integrate with SAC?
  15. Explain Data Federation vs Data Replication.
  16. How do you optimize model performance?
  17. SAP Datasphere vs SAP HANA Cloud.
  18. Explain semantic modeling in Datasphere.
  19. What is change data capture (CDC) in Datasphere?
  20. Steps to build an end-to-end data pipeline.

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