1. Verklaren van exceptionele waarden in multi-dimensionele bedrijfsdatabanken Emiel Caron, November 14, 2013

2. Business Intelligence

3. Stichting Aanpak voertuigcriminaliteit (AVc) Goal AVc: reduction of vehicle crime by means of prevention and by supporting public partners Important way to support the tackling of vehicle crime is to perform analyses on vehicle criminality data National Information Centre Vehicle Crime

4. Multi-dimensional model Measures Dimensions Dimension hierarchy

5. Vehicle crime data cube Time Vehicle Location Sum V1 V3 V2 Q1 Q2 Q3Q4 A B C Sum All, All, All Annual number of stolen vehicles in Location “A” for Vehicle “V1” Navigational operators: Roll-up, Drill-down, Slice, Dice…

6. “How can multi-dimensional databases be extended with explanatory analysis?”

7. Value which is significantly different from expected value based on a normative model Normative models: −Managerial models −Statistical models Chapter 3: Exceptions in mult-dimensional data

8. Events are explained by giving their causes Chapter 4: General explanation formalism 3-place relation: 1actual object aprofit(2012.Q1, Spain, All-Products) 2reference object rprofit(2011.Q1, Spain, All-Products) 3property Fprofit in 2012 low compared to 2011 Explanations are based on equations

9. Business model equations Systems of equations in OLAP Drill-down equations

10. Case study: Sales analysis (exception identification) Low exception: c = (2001, U.S.A., Binoculars)

11. Explanation trees that partially explain the exceptional cell c in the Product, Time & Location dimension Case study: Sales analysis (explanation)

12. Business applications Sales & financial analysis Variance analysis in accountancy Continuous auditing/ Risk assessment Competition benchmarking