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4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
4 secrets of fit Business Warehouse
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4 secrets of fit Business Warehouse

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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 …

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.

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  • 1. 4 secrets for SAP BW fitness
  • 2. Typical distribution of data in a BW system Master data 5% Temporary data 5%3% 5% 15% Other data PSA data Changelog data ODS data 15% 32% Cube E data Cube F data Cube D data 9% 11% Data you report on is only 13-17% of the system size Temporary data is subject to housekeeping (BALDAT, RS*DONE, ...) ©  2013 DataVard GmbH #2
  • 3. 4 categories of BW fitness 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 ©  2013 DataVard GmbH #3
  • 4. 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 ©  2013 DataVard GmbH #4
  • 5. 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 ©  2013 DataVard GmbH #5
  • 6. 3. Query performance •  Use BIA or go directly to HANA (?) YOU HAVE ANOTHER OPTION ©  2013 DataVard GmbH #6
  • 7. 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  Avoid outdated indexes and database statistics. 2.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  u  As of BW 7.3 the Semantically Partitioned Objects can be used. Before 7.3 “SPO” can be implemented manually 7.  Consider the Near-Line archiving of rarely used (“cold”) data to reduce data volume. ©  2013 DataVard GmbH #7
  • 8. 4. SAP BW Information Lifecycle Management The art of managing your data in line with its business value USER current 0-2 years >2 years ©  2013 DataVard GmbH HOT BW Accelerator / SAP HANA WARM Nearline Storage §  Data stored in a cost optimized way §  95% compression §  Data remains readily available COLD #8
  • 9. 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. ©  2013 DataVard GmbH #9
  • 10. Wanna know how? www.bwft.datavard.com bwft@datavard.com
  • 11. Copyright Copyright DataVard GmbH. All rights reserved. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of DataVard GmbH. The information contained herein may be changed without prior notice. DataVard and OutBoard are trademarks or registered trademarks of DataVard GmbH and its affiliated companies. SAP, R/3, SAP NetWeaver, SAP BusinessObjects, SAP MaxDB, SAP HANA and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP AG in Germany and other countries. All other product and service names mentioned are the trademarks of their respective companies. Data contained in this document serves informational purposes only. National product specifications may vary. These materials are provided by DataVard GmbH and its affiliated companies (“DataVard") for informational purposes only, without representation or warranty of any kind, and DataVard shall not be liable for errors or omissions with respect to the materials. The only warranties for DataVard products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. ©  2013 DataVard GmbH # 11

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