¶ Building and Managing Data Virtualization Layers in SAP Datasphere
In the modern data landscape, enterprises face increasing challenges to access and integrate diverse data sources rapidly and efficiently. SAP Datasphere, SAP’s cloud-native data management platform, addresses these challenges with robust data virtualization capabilities. Data virtualization enables users to create unified, real-time views of data without physically moving or replicating it, simplifying data access and reducing latency. This article explores how to build and manage data virtualization layers in SAP Datasphere, empowering businesses to unlock timely insights and foster data agility.
Data virtualization is a data integration approach that allows users to access and manipulate data from multiple heterogeneous sources through a single, logical layer. Instead of copying data into a central repository, SAP Datasphere enables on-demand data access and integration, preserving data sovereignty and freshness.
In SAP Datasphere, virtualization layers are created using virtual tables and views that provide seamless connectivity and abstraction over underlying data sources such as SAP S/4HANA, SAP BW, cloud databases, and external APIs.
- Real-Time Data Access: Provides up-to-date information without the delay of batch processing.
- Reduced Data Redundancy: Minimizes storage costs by avoiding data duplication.
- Faster Time-to-Insight: Accelerates data integration and delivery for analytics.
- Simplified Data Governance: Centralized control with consistent security policies.
- Flexible Integration: Supports diverse sources, both SAP and non-SAP.
- In SAP Datasphere, start by creating Connections to your source systems.
- Supported connection types include SAP HANA, SAP BW, JDBC/ODBC databases, cloud storage, and OData services.
- Configure connection details and credentials, then test connectivity.
- Virtual tables act as live representations of external data sources.
- Navigate to the Data Builder and select Create Virtual Table.
- Choose the connected data source and select the relevant tables or views.
- Virtual tables do not store data physically; they query the source on-demand.
- Use the Graphical Data Builder or SQL editor to create views combining multiple virtual tables.
- Define joins, filters, calculations, and aggregations to shape the data logically.
- These virtual views form the virtualization layer, abstracting complexity from end users.
- While virtualization provides real-time access, query performance depends on source systems.
- Implement caching policies or materialized views in SAP Datasphere if necessary for heavy workloads.
- Use push-down capabilities where SAP Datasphere delegates filtering and calculations to the source system.
- Apply role-based access controls to virtual tables and views.
- Use SAP Datasphere’s data masking and authorization features to protect sensitive information.
- Monitor data usage and access through audit logs.
¶ Monitor Data Source Health and Connectivity
Regularly check the status of connected systems to avoid disruptions in data access.
¶ Maintain Metadata and Documentation
Keep clear documentation and metadata updated to help data consumers understand virtualization layers.
¶ Version Control and Change Management
Use SAP Datasphere’s project and lifecycle management tools to handle updates to virtual tables and views carefully.
¶ Governance and Compliance
Enforce policies around data privacy and regulatory compliance within virtualization layers.
- Unified Customer 360 Views: Integrate customer data from CRM, ERP, and external systems without replication.
- Real-Time Inventory Reporting: Access live inventory data from SAP S/4HANA and warehouse systems.
- Cross-System Analytics: Combine financial data from SAP BW with operational data in cloud databases seamlessly.
Building and managing data virtualization layers in SAP Datasphere is a powerful strategy to achieve agile, real-time data integration while maintaining data governance and minimizing redundancy. By leveraging virtual tables and views, organizations can deliver unified data access across diverse environments, accelerating decision-making and boosting business responsiveness.
Embracing data virtualization in SAP Datasphere equips enterprises to meet evolving data demands efficiently—without sacrificing control or performance.
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