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FIN923 : Why Choose a Standard DW Data Model?

FIN923 : Why Choose a Standard DW Data Model?. Preben Gudbergsen IT Data Warehouse Manager preben.gudbergsen@almbrand.dk / +45 35477478 6th August 2003. Agenda. The Company – Alm. Brand Business situation IT situation Selection process Project phase 1 Where are we today ? Questions.

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FIN923 : Why Choose a Standard DW Data Model?

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  1. FIN923 : Why Choose a Standard DW Data Model? Preben GudbergsenIT Data Warehouse Managerpreben.gudbergsen@almbrand.dk / +45 35477478 6th August 2003

  2. Agenda • The Company – Alm. Brand • Business situation • IT situation • Selection process • Project phase 1 • Where are we today ? • Questions

  3. The Company – Alm. Brand • Alm. Brand A/S • Insurance - Property & Casualty • Insurance – Life & Pension • Bank - Investments & savings • Property & Casualty Insurance • Founded 1792 • Products covering – private, business and agriculture • 4th largest in the private segment • Life • Bought in the 1990´s • Market share of 2% • Bank • Bought in the 1990´s • 9th largest bank • Moving into the retail banking market

  4. After internal merger Background Information Business Before

  5. Background Information Business • Common culture values • Enterprise orientation • Enterprise strategic goals • 20% “Helkunde” in 2006

  6. Independend data warehouses Enterprise data warehouse Background Information IT

  7. Background Information IT • New Insurance operational system • Existing insurance data warehouse needs reengineering • Bank data warehouse • Did not match business needs • Enterprise focus not matched • Enterprise view of the customer • IT strategy • Focused on standard systems

  8. Selection Process The stages Project start Gap analysis Vendor selection Arguments to management Business pre-analysis Technical workshops

  9. Selection Process • Market screening • One day technical workshop • Examination of model • Handling of metadata • Ease of use • Knowledge transfer Project start Gap analysis Vendor selection Arguments to management Business pre-analysis Technical workshops Mar / Apr 2002

  10. Selection Process • Exploration of business needs • Based on strategic goals • Identify gaps • Identify data warehouse projects • Prioritize data warehouse projects • Conclusion Project start Gap analysis Vendor selection Arguments to management Business pre-analysis Technical workshops Mar / Apr 2002 May / Jun 2002

  11. Selection Process • Talk data model with business management !!!! • Enterprise focus supported • Speed of implementation • Lower risk • Known and proven method • Data modelling ressources • Performance Project start Gap analysis Vendor selection Arguments to management Business pre-analysis Technical workshops Mar / Apr 2002 May / Jun 2002 Jun / Oct 2002

  12. Selection Process • Selection criteria • Model • Metadata handling • Knowledge transfer • Ease of use • Price Project start Gap analysis Vendor selection Arguments to management Business pre-analysis Technical workshops Mar / Apr 2002 May / Jun 2002 Jun / Oct 2002 Oct / Dec 2002

  13. Selection Process • Fit assesment • One week workshop • Selected definitions and measurements • Important reports • Covering all business areas • Evaluation criteria • Result Project start Gap analysis Vendor selection Arguments to management Business pre-analysis Technical workshops Mar / Apr 2002 May / Jun 2002 Jun / Oct 2002 Oct / Dec 2002 Oct 2002

  14. Selection Process • Three weeks business exploration • Master plan • Phase 1 • Enterprise customer & retail bank • Phase 2 & 3 – Bank • Phase 4 - Insurance Project start Gap analysis Vendor selection Arguments to management Business pre-analysis Technical workshops Mar / Apr 2002 May / Jun 2002 Jun / Oct 2002 Oct / Dec 2002 Oct 2002 Jan 2003

  15. Where are we today ? . • Phase 1 delivered • Enterprise customer • Retail bank to staging area • Challenges • Too ambitious scope • ETL complexity • Estimation skills • Conclusion

  16. Questions ?

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