4 secrets of fit business warehouse
DESCRIPTION
Keep in mind the most important attributes to keep your Business Warehouse in shape. Keeping SAP BW under control will help you to get rid of ETL problems, system dumps, performance problems and save space in your database.TRANSCRIPT
4 secrets for SAP BW !tness
© 2013 DataVard GmbH # 2
5%
15%
15%
9% 11%
32%
5% 5% 3% Master data
Temporary data Other data PSA data Changelog data ODS data Cube E data Cube F data Cube D data
Typical distribution of data in a BW system
Data you report on is only 13-17% of the system size
Temporary data is subject to housekeeping (BALDAT, RS*DONE, ...)
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4 categories of BW !tness
Based on an in-depth analysis (BW Fitness Test) of 150+ BW systems we identified:
1. System robustness
2. Data quality
3. Performance: load and query
4. Information lifecycle management: managing data from cradle to grave
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1. System Robustness
Security
§ ABAP code
§ Authorizations
§ Basis parameters
BW Batch processing
§ Analysis of critical path with monitoring
Dumps
§ Minimize number of dumps per month with monitoring
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2. Data Quality
Technical data quality
§ Regularly check and remove unused SIDs, DIMIDs, Master data
Duplicates
§ Root cause analysis instead of band aiding
Semantical data quality
Manage data quality in source systems
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3. Query performance
• Use BIA or go directly to HANA (?)
YOU HAVE ANOTHER
OPTION
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3. Query performance
1. Avoid outdated indexes and database statistics.
2. Build secondary indexes on DSOs to speed up the data selections.
3. Build aggregates to improve the query performance and check size & utilization.
4. Compress InfoCubes regularly. u Initial compression may hurt, but is worth it!
5. Consider line-item dimensions in case of large dimensions u Initial dimensional remodeling may hurt, but is worth it!
6. Use partitioning for InfoProviders based on time characteristics to reduce the data volume in each InfoProvider. u As of BW 7.3 the Semantically Partitioned Objects can be used. u Before 7.3 “SPO” can be implemented manually
7. Consider the Near-Line archiving of rarely used (“cold”) data to reduce data volume.
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USER
4. SAP BW Information Lifecycle Management
BW Accelerator / SAP HANA
HOT
WARM
COLD
current
0-2 years
>2 years
Nearline Storage § Data stored in a cost
optimized way § 95% compression § Data remains readily
available
The art of managing your data in line with its business value
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How the best manage data growth
From cradle to grave Manage cold and old data using Nearline Storage
Biggest potential in DSOs, but also helpful in Cubes
Build a detailed housekeeping plan and adhere to it. If possible automate.
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