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Data Model and Matrix Schemas

Data Model and Matrix Schemas XI European Banking Supervisors XBRL Workshop in Vienna 19th November 2009 Katrin Schmehl Member of CEBS XBRL Network. Agenda. Multidimensional terminology Appliance on FINREP framework Overview on matrix schema. Multidimensionality of data.

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Data Model and Matrix Schemas

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  1. Data Model and Matrix Schemas XI European Banking SupervisorsXBRL Workshop in Vienna19th November 2009 Katrin Schmehl Member of CEBS XBRL Network

  2. Agenda • Multidimensional terminology • Appliance on FINREP framework • Overview on matrix schema

  3. Multidimensionality of data Dimensional view on gross revenue

  4. Multidimensionality of data - Measures 500 Gross revenue Books France … product group 500 country measures Measures: data mostly in numerical dimensions

  5. Multidimensionality of data - Dimensions 500 Gross revenue Books France … product group Other dimensions country of origin buying country country measures Dimensions: views or objects for which data should be reported, specific breakdown of a measure, ie. “by country”

  6. Multidimensionality of data - Domain 500 Gross revenue country Books France France Domain … Spain Austria Belgium Sub domain Germany Italy Domain: a set of items that have a specific coherence

  7. Multidimensionality of data – Domain member 500 Gross revenue country Books France France Domain … Spain Austria Domain member Belgium Germany Italy Domain member: a specific member of a domain

  8. Multidimensionality of data – Data point Dimensional view on gross revenue 634

  9. gross revenue product group News papers country Spain Multidimensionality of data – Data point

  10. Multidimensionality of data – data base Country ID name Period ID year month day Facts ID_Product group ID_Country ID_Period Gross revenue Product group ID name Dimensions have the character of keys for multidimensional data

  11. Measure Hypercube Dimension1 Domain a b c d Dimension2 Domain A B C D gross revenue product group News papers country Spain Multidimensionality of data - Hypercube product group country measure Hypercube: binds dimensions together in order to build a Cartesian product

  12. Multidimensionality of data - sections Dimensional view on gross revenue by November 2009

  13. Multidimensionality of data – definition of sections Dimensional views on gross revenue Cartesian product 16 Combinations of one member of product group with one member of country 12 Combinations of one member of product group with one member of country and one member of book category

  14. Multidimensionality of data – definition of sections Same section (same extended link role) Cartesian product defined by a hypercube All Set of combinations 16 Combinations of one member of product group with one member of country All Set of combinations 12 Combinations of one member of product group with one member of country and one member of book category VALIDATION! The intersection of both sets is null  no combination is allowed.

  15. Multidimensionality of data – definition of sections Different sections (different extended link roles) Cartesian product defined by a hypercube All Set of combinations 16 Combinations of one member or product group with one member of country All Set of combinations 12 Combinations of one member or product group with one member of country and one member of book category VALIDATION! The union of both sets  every combination is allowed.

  16. Agenda • Multidimensional terminology • Appliance on FINREP framework • Overview on matrix schema

  17. FINREP Data model – measures and dimensions

  18. FINREP Data model – measures and dimensions measures dimension dimension dimension

  19. FINREP Data model – definition of sections Section 1 Section 2 Section 3

  20. FINREP Data model – definition of sections Section 4

  21. FINREP Data model – Common elements • Data points are repeated • Identification should be the same ! • same primary • same dimensions • same dimension members CONSISTENCY STABILITY

  22. FINREP Data model – Movement tables • Data refers • to an instant in time (opening balance and closing balance) • to a duration in time (variations in time) • Possible solutions • Two primaries (two dimensions) • Primaries in the columns • Primaries in the rows CONSISTENCY STABILITY

  23. Agenda • Multidimensional terminology • Appliance on FINREP framework • Overview on matrix schema

  24. Matrix schema – What is a matrix schema? • Representation of the multidimensional structure of XBRL taxonomies in Microsoft Excel • Generated by a reverse-engineering process of the Bank of Italy • Initially designed for reviewing COREP and FINREP taxonomies • Does XBRL match the business requirements? • Matrix schemas are used since several years in the CEBS XBRL Network ? XBRL taxonomy Matrix schema

  25. Matrix schema – How is it now used? FINREP tables Data classification ? XBRL taxonomy Matrix schema

  26. Matrix schema - How should it be read? measures reference to sub domains

  27. Matrix schema – The domain / sub domain list

  28. Matrix schema – The advantages • Easy to read and understand (in comparison to XBRL) • Very compact format • Eases the review process for the data classification • Shows the matching between business requirements and the data model to be implemented • Tool for quality assurance • Prospects: Consolidated matrix schema approach

  29. www.c-ebs.org www.eurofiling.info Katrin Schmehl E-mail: Katrin.Schmehl@bundesbank.de The XBRL Network of the

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