Modern enterprises often leverage a mix of data storage architectures to meet their diverse analytical needs. While SAP Data Warehouse Cloud (SAP DWC) provides a powerful, integrated environment for business data warehousing and analytics, many organizations also maintain external data lakes to store large volumes of raw and unstructured data.
Connecting SAP Data Warehouse Cloud with external data lakes enables organizations to combine the best of both worlds—structured, governed enterprise data with vast reservoirs of raw data—enabling comprehensive analytics, advanced machine learning, and scalable data management.
This article delves into the approaches, benefits, and best practices for integrating SAP Data Warehouse Cloud with external data lakes.
Data lakes—such as those built on Amazon S3, Azure Data Lake Storage (ADLS), or Hadoop HDFS—are ideal for storing vast amounts of raw, unstructured, or semi-structured data at low cost. However, these data lakes often lack the governance, semantic modeling, and business user accessibility of traditional data warehouses.
By connecting SAP DWC with external data lakes, organizations can:
SAP Data Warehouse Cloud supports virtual tables that allow direct query access to data stored externally without physically importing it.
For scenarios requiring frequent or high-performance access, data can be ingested or replicated from the data lake into SAP DWC:
Federated queries allow SAP DWC to join data across its own tables and external data lake tables seamlessly:
| Benefit | Description |
|---|---|
| Scalability | Leverage low-cost storage of external lakes while maintaining SAP DWC for business logic. |
| Flexibility | Support diverse data types and analytics use cases by combining raw and curated data. |
| Improved Governance | Apply SAP DWC’s security and metadata capabilities to lake data for consistent governance. |
| Faster Insights | Direct querying or staged data enable quicker access to fresh data. |
| Cost Optimization | Avoid unnecessary data duplication and reduce storage costs by using virtual tables. |
A retail company maintains a large external data lake storing clickstream, social media, and IoT sensor data, alongside structured sales and inventory data in SAP DWC.
By connecting SAP DWC with the external data lake:
Integrating SAP Data Warehouse Cloud with external data lakes empowers organizations to harness the richness of diverse data sources while maintaining control, governance, and semantic clarity. Whether through virtual tables, data ingestion, or federated querying, this connection enables modern analytics architectures that are scalable, flexible, and insightful.
By adopting best practices and leveraging SAP’s integrated tools, enterprises can unlock the full potential of their data landscape, turning raw data lakes into actionable business intelligence.