In SAP Business Intelligence (SAP BI), managing data growth efficiently is a critical challenge for organizations. As data volumes expand rapidly, performance, storage costs, and system manageability can be impacted. Implementing effective Data Archiving Strategies ensures that historical or less frequently accessed data is moved to archive storage while keeping the active system lean and responsive. This article explores the importance, approaches, and best practices for implementing data archiving in SAP BI environments.
Data Archiving is the process of moving data that is no longer actively used but must be retained for compliance or historical reference from the primary SAP BI system into a separate archive storage. This process helps reduce the volume of data in the active BI system without losing access to valuable historical information.
In the SAP BI context, archiving typically involves data stored in InfoProviders such as DataStore Objects (DSOs), InfoCubes, or Data Archiving Objects.
- Optimize System Performance: Archiving reduces the data volume in the active system, improving query response times and data load performance.
- Reduce Storage Costs: Moving old data to cheaper storage lowers the total cost of ownership.
- Maintain Compliance: Ensures that data retention policies are followed without compromising system efficiency.
- Simplify System Maintenance: Smaller datasets are easier to backup, restore, and manage.
- Enable Scalability: Archiving facilitates long-term data growth management, enabling the BI system to scale efficiently.
Archiving objects define the structure and rules for archiving specific data types or InfoProviders. In SAP BI, archiving objects typically relate to transactional data or master data.
The typical archiving process includes:
- Data Selection: Identify the data eligible for archiving based on criteria like age, status, or business rules.
- Data Extraction: Extract selected data from active BI objects.
- Data Storage: Store data in an archive file or external storage system.
- Data Deletion: Remove archived data from the active system.
- Data Retrieval: Provide access to archived data through reports or queries if needed.
While archiving moves data to an external location with retrieval capability, deletion permanently removes data without retention.
Understand data usage patterns and retention requirements. Categorize data into active, less active, and archival phases.
Set clear policies regarding:
- Which data to archive (e.g., data older than 3 years).
- Retention periods based on legal or business requirements.
- Data retrieval needs after archiving.
- Use SAP standard archiving tools like Data Archiving Workbench (transaction SARA) for transactional data.
- For SAP BW, leverage archiving strategies for InfoProviders, such as archiving historical data from DSOs or InfoCubes.
- Integrate with external archiving systems or third-party solutions if necessary.
- Configure archiving objects and define filters.
- Execute test runs to verify data selection, extraction, and deletion without loss of critical data.
- Validate archived data integrity and retrieval capability.
¶ Step 5: Monitor and Optimize
- Continuously monitor archiving jobs and system performance.
- Optimize archiving schedules and data selection criteria based on evolving business needs.
- Start Early: Implement archiving strategies during early phases of SAP BI deployment.
- Automation: Schedule regular archiving jobs to avoid data buildup.
- Documentation: Maintain detailed records of archiving policies, schedules, and archived data locations.
- Data Security: Ensure archived data is protected according to compliance and security standards.
- User Training: Train BI users on accessing archived data and understanding the impact of archiving.
¶ Challenges and Considerations
- Data Access Post-Archiving: Archived data may not be as readily accessible; plan for efficient retrieval mechanisms.
- Data Consistency: Ensure that archived data relationships (e.g., master data links) are preserved.
- System Impact: Archiving processes may impact system performance temporarily; schedule during low usage periods.
- Legal Compliance: Stay updated with data retention laws and audit requirements.
Implementing effective data archiving strategies in SAP BI is essential to manage data growth sustainably, optimize system performance, and meet compliance requirements. By carefully planning, configuring, and monitoring data archiving processes, organizations can ensure that their SAP BI environment remains agile, cost-effective, and reliable over time. Archiving transforms the challenge of ever-growing data volumes into a manageable asset that supports long-term business intelligence success.