SAP Business Intelligence (BI) is a powerful platform that enables organizations to collect, transform, and analyze data to drive informed decision-making. A fundamental step in the BI process is the creation of data sources, which serve as the entry points for data extraction from various operational systems into the BI environment.
This article provides an overview of creating data sources in SAP BI, highlighting the key concepts, steps, and best practices to establish reliable and efficient data extraction processes.
A Data Source in SAP BI is a metadata object that defines how data is extracted from the source system (such as SAP ERP, CRM, or external databases) and transferred into SAP BI. It contains information about the fields to be extracted, extraction methods, and technical configurations.
Data sources are crucial because they ensure that accurate and relevant data flows into the BI system for further processing, reporting, and analysis.
SAP BI supports several types of data sources depending on the source system and the nature of the data:
- SAP ERP DataSources: Extract data from SAP ECC or S/4HANA systems, including transactional and master data via standard extractors or custom data sources.
- SAP CRM DataSources: For extracting customer relationship data.
- SAP BW DataSources: Used in data warehousing scenarios to extract data from other BI systems.
- Flat Files and External Data Sources: Include CSV, Excel files, or databases connected via interfaces.
- Operational Data Provisioning (ODP): Modern framework supporting real-time data extraction.
¶ Step 1: Identify the Source System and Data Requirements
- Understand the business requirement and the specific data needed.
- Determine the source system (e.g., SAP ECC, S/4HANA, non-SAP systems).
- Identify existing standard extractors or decide on custom data source development.
- For SAP ERP sources, use transaction RSA6 to create or check available data sources.
- Activate the data source if it’s standard or create a custom data source using transaction RSA5.
- Define extraction logic and fields to be extracted.
- Log in to SAP BI system and open the Administrator Workbench (AWB) or SAP BW Modeling Tools.
- Create a new data source by specifying the source system connection.
- Import the data source metadata, including fields and extraction structures.
- Configure extraction settings such as delta extraction for incremental loads.
- Set filters to extract specific subsets of data if necessary.
- Map source fields to BI system fields.
- Establish processes that define how and when data is loaded from the source system into the BI system.
- Schedule initial and delta loads based on business needs.
¶ Step 6: Test and Validate Data Extraction
- Execute data loads to verify the extraction.
- Check for data consistency, completeness, and performance.
- Monitor and troubleshoot any errors in data extraction.
- Leverage Standard Extractors: Use SAP-provided standard data sources wherever possible to reduce development effort.
- Plan for Delta Extraction: Implement delta mechanisms to optimize data loads and reduce system impact.
- Maintain Documentation: Keep detailed records of data source definitions, field mappings, and extraction logic.
- Ensure Security: Apply appropriate authorizations to restrict access to sensitive data during extraction.
- Monitor Performance: Regularly review extraction and load times to identify bottlenecks.
- Collaborate with Source System Teams: Coordinate changes in source system data structures with BI teams to maintain data source integrity.
Creating data sources is a foundational activity in SAP BI that enables the accurate and efficient flow of data from source systems to BI environments. By understanding the types of data sources, following structured creation steps, and adhering to best practices, organizations can ensure their BI systems deliver timely and reliable insights to support business decisions.