Lean Data Management in SAP® BW
Download as PPTX, PDF1 like869 views
The document discusses lean data management in SAP BW, focusing on system performance analysis, data volume evaluation, and quality improvement recommendations. It outlines the BW fitness test project phases, key principles of lean data management, and a central automation approach for data housekeeping. The text emphasizes the importance of optimizing data storage costs in relation to business value and presents Datavard's expertise in enhancing SAP system landscapes.
Lean Data Management in SAP® BW
- 1. Lean Data Management in SAP®BW
- 2. # 2 27 analyses from the following areas: General system information Data volume analysis System performance Data quality System activity Results: Analysis report in form of offline HTML Benchmarking information for each analysis Workshop with result interpretation by experts Recommendations to unleash areas with improvements potential BW Fitness Test
- 3. # 3 BW Fitness Test Project Phases Customizable parallelization Collection of KPIs Consulting Duration : 5 days Collection of results Comparison with best practice / benchmark Customer requirement Building recommendations Duration : 2 days Presentation HTML, PPT or PDF Output Duration : 3 hours with customer SAP transport Abap based Authorization Functional ExecutionImport of BW FT Analyze of Results Delivery and presentation SAP BW
- 4. # 4 BW Fitness Test System Performance Which are the biggest bottlenecks? Which reports have critical performance? Which ETL consumes most runtime? Data Volume How is data distributed across the data model layers? How old is your data? How frequently is data being used? Where does data growth come from? System Activity Which are the outdated users? What are the most frequent system short dumps? Data Quality What are the consistency issues? Are there any unused DIMID & SID entries? What are the most frequent RSRV errors?
- 5. # 5 User happiness TCO&data access TCO Lean Data Management with OutBoard™ Performance optimization, Tuning In-memory Ensure SLAs are met GOALS TACTICS Set up central policies Use appropriate storage: Archiving, NLS, Smart data access Set up central policies Perform housekeeping Automation Information “at your fingertips” Speed and high availability is key Keep & store Reduce cost Purge, delete & housekeeping Hot Data Business critical data Data required for reporting and planning Cold Data / Old Data Aged data, history Infrequent, rare use Need to keep (external/legal, internal) Dead Data Technical data (e.g. logs, protocols, PSA) Redundant data
- 6. Future Planning and Roadmap
- 7. # 7 1. The cost of storage needs to match the business value of your data. 2. Separate Data Management from Storage Technology. An open architecture secures your current and future investments. 3. Automation and central rules ease Data Management. 4. Iterate through the DMAIC cycle several times. Refine rules based on actual data usage statistics. 5. Start reducing data volumes from bottom (staging) to top (reporting). 5 Key principles of Lean Data Management
- 8. # 8 Speed of Access Lower TCO Business Warehouse OutBoard™ OutBoard™ – Architecture overview HANADB or Smart Data Access* SAP cluster tables IQ RDBMSHadoop For NON- HANA only File / Cloud Deletion INTERNALEXTERNAL NLS Interface Data Archiving DeletionHousekeeping Dynamic Tiering* * under evaluation, currently not recommended
- 9. # 9 OutBoard™ - Storage Layer Concept Enables you to manage cost of storage inline with the value of information. Data can be transferred to other layers managing various aging thresholds using Aging Profiles. Example: Up to 2 years in HANA 2-7 years in IQ 8-20 years in files 21+ will be deleted
- 10. # 10 OutBoard™ - Scope of Housekeeping (ERNA) Scope of Housekeeping Unused customers Unused vendors Phantom change documents Phantom texts Application log Batch log IDoc tables (EDI40, EDIDS) qRFC, tRFC Job-Tables (TBTCO, TBTCP etc.) Change & Transportsystem Spool data (TST03) Table Change Protocols Batch Input Folders Alert Management Data (SALRT*) Old short dumps Batch input data … ERP and Netweaver PSAs & Change Logs Request logs & tables (RSMON* and RS*DONE) Unused dimension entries Unused master data Cube & Aggregate compression Temporary database objects NRIV buffering Table buffering BI-Statistics Process Chain Log Errorlogs Unused Queries Empty partitions BI Background processes Bookmarks Web templates … Business Warehouse Housekeeping addresses data which is not relevant for business Housekeeping should be automated to avoid manual work Housekeeping should be done centrally for the complete SAP landscape.
- 11. # 11 The Recycle Bin adds an important Safety Layer similar to Windows or Mac. Instead of just deleting data, you can move it to a highly compressed Recycle Bin (ratio 10:1), from which it can be automatically deleted or retrieved. ERNA - Recycle Bin
- 12. # 12 Housekeeping – Central automation is key Housekeeping addresses data which is not relevant for business and which cannot be archived Housekeeping should be automated to avoid manual work Housekeeping should be done centrally for the complete SAP landscape.
- 13. # 13 DataVard presents DataVard Specialized in helping you to run your SAP system landscape smarter and better since 1998 More than 200 projects delivered p.a. Customers range from SMEs (60 users) to Fortune 500 (e.g. Allianz, BASF, KPMG, Roche, Nestle) SAP & DataVard, a partnership we are 100% committed towards SAP preferred vendor since 1999 Development partner of SAP® Landscape Transformation Suite (LT) and Information Lifecycle Management (ILM) Gartner Cool Vendor 2013, 2015 Magic Quadrant for Data Archiving Privately held 7 locations in Germany (HQ), Italy, Slovakia, United Kingdom and the US Growth gives Credibility Experience gives Safety Focus gives Strength
- 14. # 14 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, OutBoard, ERNA, CanaryCode, BW Fitness Test and ERP Fitness Test 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. CR Copyright DataVard GmbH. All rights reserved.CR Copyright DataVard GmbH. All rights reserved.