PBS Archiving Day 2009 CBW Workshop. Case Study: Archiving with CBW NLS IQ for a large SAP BW System

Transcription

1 PBS Archiving Day 2009 CBW Workshop Case Study: Archiving with CBW NLS IQ for a large SAP BW System

2 Agenda Overview Current Situation CBW NLS IQ in the CCH System Landscape Project Requirements Initial Results Q & A

3 Overview: Coca Cola Hellenic One of the largest Bottling and Distribution Companies for Coca Cola worldwide: 28 Countries 90 Brands Employees 2.1 billion unit cases

4 Overview: Coca Cola Hellenic Distribution Area

5 Overview: Coca Cola Hellenic Brands

6 Overview: Coca Cola Hellenic Metrics

7 Agenda Overview Current Situation CBW NLS IQ in the CCH System Landscape Project Requirements Initial Results Q & A

8 Current Situation IT System Strategy Move from local ERP und distribution system in individual operating companies to a centralized system Focus on SAP Solutions

9 Current Situation IT System Landscape Legacy and Core 4 - Non-template SAP - SAP FI/CO Templates - Local BW - Non-SAP Legacy - Custom Applications - BW 7.0 centralized reporting Wave 1 - SAP ERP ECC SAP BW SAP APO - Legacy Sales System Wave 2 - SAP ERP ECC SAP CRM SAP SCM SAP BW SAP XI

10 Current Situation Core 4 and Legacy Environments: 28 Countries Wave Wave

11 Agenda Overview Current Situation CBW NLS IQ in the CCH System Landscape Project Requirements Initial Results Q & A

12 CBW NLS IQ in the system landscape Wave 1 Wave 2 ECC 5.0 BW 3.5 ECC 6.0 CRM 5.0 BW 7.0 PBS add ons PBS PCL TJC ASC PBS CBW IQ PBS PCL PBS add ons PBS PCL TJC ASC PBS PCL PBS CBW IQ PBS PCL HP Superdome LPAR 2 4 CPU 4 8 GB memory PBS PCL PBS CBW IQ Sybase IQ

13 Agenda Overview Current Situation CBW NLS IQ in the CCH System Landscape Project Requirements Initial Results Q & A

14 Challenges Data volume and growth today 30 Volume (TB) ERP BW Wave 1 Wave 2

15 Challenges Data volume and growth today Growth per Month (GB) Wave 1 Wave 2 ERP BW

16 Challenges Growth forecast Wave 2 Growth per Month (TB) ERP BW

17 Challenges Dynamic environment requires frequent data model changes Data volume too large for full data loads from source systems for an extended time period PSA have to be retained Data distribution: PSA: 48% DSO: 27% Cubes: 25%

18 Challenges Long runtimes for delete jobs Runtime can be reduced drastically by partitioning InfoProviders corresponding to archiving strategy Close cooperation with BW development teams and system administrators required

19 Challenges Frequently changing requirements for queries from end users Design template doesn t cover all local requirements High data volume requires dedicated performance tuning to achieve good query response times

20 Agenda Overview Current Situation CBW NLS IQ in the CCH System Landscape Project Requirements Initial Results Q & A

21 Initial Results PSA Archiving can significantly reduce data volume Archiving using ADK Format Compression > 10:1 Cost-efficient retention with PBS ContentLink on EMC Centera

22 Initial Results Due to the high data volume, ADK-based archiving is inefficient for DSOs and Cubes High modeling effort for aggregates and indices Index generation runtime Response time NLS IQ delivers significantly better performance (almost) without administration effort

23 Initial Results Query response times for queries without master data or navigation attributes performance for queries over archived periods is comparable with query performance in production system Slower response times for queries with master data or navigational attributes

24 Next steps Evaluation of the new functionality Integration of users in operating companies into the test process Sizing and configuration for the production environment

25 Agenda Overview Current Situation CBW NLS IQ in the CCH System Landscape Project Requirements Initial Results Q & A

26 Questions & Answers Contact Information Phone: