1. Introduction Data Vault

2. Historical development Business Intelligence 1950 Turing : First computers 1960Codd : 3NF 1970Management Information Systems (MIS) Executive Information Systems (EIS) 1980Kimball : Dimensional Modeling Kimball Inmon : Corporate Information Factory 1990Enterprise Datawarehousing 2000Linstedt : Datavault 2010Ronstad : Anchor Modeling

3. Challenges Classical Datawarehouse Time-to-Build – Complexity, High Failure Rates Lack of Agility – Expensive and Extensive re-engineering required to adapt No auditability – Lack of tracebility, accountability and compliance Departmental scope – No enterprise view, inability to effectively integrate disparate systems Duplicate efforts and Spread Marts

4. Dan Lindstedt - Founder

5. Data Vault ”The Data Vault is a detail oriented, historical tracking and uniquely linked set of normalized tables that support one or more functional areas of business. It is a hybrid approach encompassing the best of breed between 3rd normal form (3NF) and star schema. The design is flexible, scalable, consistent and adaptable to the needs of the enterprise..” Dan Linstedt “The Data Vault is a data modelling approach and methodology that is specifically tuned to optimize your Enterprise Datawarehouse initiatives.” Hans Hultgren

6. “The Data Vault is the optimal choice for modeling the Enterprise Datawaerehouse in the DW 2.0 framework.” Bill Inmon, June 2007 The DWH Guru’s opinion

7. Datavault application in Netherlands

8. Datavault – 3 Building blocks Hub : Identification – Unique collection of Business Keys – Business Key: identity of an enterprise entity Link : Relationship – Unique collection of associations between two or more Business Keys – Unit Of Work (grain), transactions and events Satellite : Description – Adds context to a Hub orLink – Timebound (System Date/Time !)

9. Sample model Identification Relation Description

10. Datavault modelled Datawarehouse Architecture Source 1 Star 1 Star 4 Star 3 Star 2 Star 5 Source 2 Source 3 Source.. Source x Star 6 Star 9 Star 8 Star 7 Star x Business Data Vault Business Data Vault Data Vault EDW Data Vault EDW Error Marts (Operational) Reports (Operational) Reports

11. Example

12. Data Vault model Flight #FlightNr #ScheduledDate #ArrDepIndicator Flight #FlightNr #ScheduledDate #ArrDepIndicator Gate / Ramp #GateRampCode Shop #ShopNo Shop #ShopNo Product #ProductCode Lounge #LoungeCode Aircraft #RegNr Aircraft Flight Flight Gate Ramp Gate Lounge Shop Lounge Product Shop Sale Flight Product Sale Airline #IATA Code Aircraft Airline Product Product Sale Aircraft Shop Lounge Sale Gate / Ramp Flight Product Shop Sale Shop Airline Shop Lounge Product Hierarchy Sale #TrxID Sale Shop

13. Added value of Datavault modelling Build Incrementally – Think Big Start Small Scale to Infinity – Insert only Auditability – Tracebility of the data and it’s history, versioning of data Absorb all data all of the time – Store RAW data, Independent Loads, Lazy Updates, Single Point of Facts Adapts to new sources easily – No need for re-engineering when new sources need to be integrated Need for Operational Business Intelligence – Real Time Loading (SOA), Real Time Reporting and data maintenance

14. Build a flexible foundation with us! 14 Semantic layer Implementation Develop dashboards & reports Build an Analytics capability DWH / Datavault implementation Data Quality Management Self-service BI Implementation Self-service BI Implementation Data Integration Big data POC’s

15. Datavault implementation services & tools Datavault Education – By certified Datavault engineers Datavault Implementation consultancy – Assist you in creating your Datavault model Datavault Implementation Tools – Model driven Datawarehouse ETL code generation