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Data Owner & Data Steward guidebook October 2011 – V1

The 360-degree view on your parties relationships. Party Ecosystem MDM by. Data Owner & Data Steward guidebook October 2011 – V1. Welcome to Party Ecosystem MDM.

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Data Owner & Data Steward guidebook October 2011 – V1

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  1. The 360-degree view on your parties relationships Party Ecosystem MDM by Data Owner & Data Steward guidebookOctober 2011 – V1

  2. Welcome to Party Ecosystem MDM • You are interested in Party Ecosystem MDM to benefit from a unified data repository collecting all information needed to define relationships between parties: namely their ecosystem • Types of party and types of relationship between parties shall be able to evolve over time quickly without generating any IT changes in the repository • Therefore you need an agile 360-degree view on your parties relationships Now let us show you how we can help

  3. Preamble This all too common type of data modeling shall be given up Too many pains with this type of data modeling • Adding a new type of Party or a new interaction between parties mandate database modifications • Sharing information when a party plays many roles becomes a real nightmare • Therefore: rigid, not agile, risky and too IT oriented Find out how to do more sustainable (see next)

  4. Achieving Party Ecosystem MDM 2 • Adding a new type of Party or a new interaction between parties don’t entail any database modification • Sharing information when a party plays many roles is enforced • Therefore: agile, reliable, not IT oriented 3 1 1 2 3

  5. Now let’s start in Party Ecosystem MDM

  6. Party: identity Party identification Adding attributes to collect detailed information about Party is easy to enforce in smartdatagovernance.com (address, contact details…). This doesn’t impact the purpose of Party’s Ecosystem MDM domain presented here To complement with this tabular view you can use data hierarchy views (see next)

  7. Party identity predefined data hierarchy view View by Type of party Predefined type of party

  8. List of Party Role Pre-defined values To complement with this tabular view you can use data hierarchy views (see next)

  9. Party Role predefined data hierarchy view View by Family Predefined family (category of Party Role)

  10. Party: interaction Party’s ecosystem Period Stems from Party Role Stems from Party Role To complement with this tabular view you can use data hierarchy views (see next) Predefined type of relationship

  11. Party: interaction detailed view • The reversed interaction allows for quering data by both Husband and Wife terms depending on needs • Eg. of reversed interaction: • Customer – Provider • Headquarter – Subsidiary • Father – Son • Husband - Wife • Etc. Very easy-to-use grammar to define party’s ecosystem: This party [party] has this interaction [party role] with this party [party] in this type of relation [type of relationship] from this date [start] to this date [end] To complement with this tabular view you can use data hierarchy views (see next)

  12. Party: interaction predefined data hierarchy views View by Main Party (This party) • For every party you can easily see its ecosystem. Here applied to PreaBook publisher we get • it is the Headquarter of Herpaing publisher and Wouly publisher • it is a competitor against SATS GO publisher • it is a partner with Bank of new area, Endeavor construction, Parway publisher and Photo book company • it is managed by a CEO named David King

  13. Party: interaction predefined data hierarchy views View by Reversed Party (With this party) • The reversed Party view applied to the next example PreaBook publisher is highlighted in red

  14. Party: interaction predefined data hierarchy views View by interaction • Provides a direct view of which parties play which roles • Eg. Richard Moor is the father of John Smith • Eg. PreaBook is the Headquarter of the two subsidiairies already saw in the previous example (slide above)

  15. Party: interaction predefined data hierarchy views View by Type of relation

  16. Synthesis of objects Party Ecosystem MDM Logical data modeling space(data modeler) Semantic space(data stewarding)

  17. Going further Keep in mind that smartdatagovernance can deliver much more data management functions Customizing the predefined Party Ecosystem data model Data approval process (workflow) Permission management Collaborative work Audit trail Data services and connection to systems Data versioning Data quality ../.. It’s easy to use Don’t forget to try it

  18. Now you start! Use the trial access from www.smartdatagovernance.com And…

  19. Last point If you need support contact us

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