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Implementing Data Management: Vision and Current Activities

Implementing Data Management: Vision and Current Activities. March 2nd, 2007. Michael C. Daconta. Vice President, Enterprise Data Management. mdaconta@oberonassociates.com. Agenda. Vision: Understanding Real-Time Relevance Outcomes and Activities Initial Focus Areas Applying Scope

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Implementing Data Management: Vision and Current Activities

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  1. Implementing Data Management: Vision and Current Activities March 2nd, 2007 Michael C. Daconta Vice President, Enterprise Data Management mdaconta@oberonassociates.com

  2. Agenda • Vision: Understanding Real-Time Relevance • Outcomes and Activities • Initial Focus Areas • Applying Scope • Know what you know… • Know what it means… • Initial Implementation …

  3. Content & Services User Context & Requirements Relevance The Vision… • Strategic Goal • Real-time Relevance: “The Right Information to the Right Person at the Right Time” What the User Needs RIGHT NOW! What you have available? What we mean by “Right” Can you calculate this in real-time? Do you know your users? How much of what you have do you actively manage?

  4. Progress Gauge The Enterprise Data Management Program Vision This will deliver tangible results!

  5. Our initial focus areas for implementing Enterprise Data Management are: • “Know What You Know” • “Know What It Means” • “Share What You Should” Business Requirements IT Tasks Discovery Solutions Enterprise Modeling Sharing & Governance Processes CURRENT FUTURE These business requirements are clear and measurable!

  6. Applying Scope: What is Enterprise Data? • Enterprise Data is any data which intersects with the enterprise in one of 3 ways: • Shared data – data that is exposed to multiple parties or exchanged with multiple parties. • Common data – data that has fields in common with other business units; for example, airport codes or organization codes. • Decision support data – data that is aggregated for enterprise decision making. Remember: All Data is Not Equal!

  7. Table/Column Def Schemas Data Models Apps/Services The Data Asset Inventory Step 1: Compile & Analyze High-level Data Asset Information Step 2: Manage & Re-use Data Asset Artifacts (Information Discovery) System Documentation “Know what you know” Data Models Data Asset Surveys Statistics MRR MRR Scorecard Reuse Can you use it enterprise-wide? Developers i.e. What systems have data on security incidents?

  8. Web App #1 • Survey – simple questions and easy access • Scorecard – Are you enterprise ready? • Do you D.A.R.E. to Share?

  9. Data Asset Readiness for the Enterprise Score Card Data Asset X Applying Scope: Sample Score Card

  10. Applying Scope: Data Asset Readiness Visualization

  11. Master Data Incidents Threats People Business Glossary Facilities Locations Code Look-ups NIEM Exchanges “You know what it means” through the Enterprise Data Model Enterprise Data Model Data Warehouse MRR Production Databases “If you cannot model it, you don’t really know what it means nor how it fits into the big picture.”

  12. Web App #2 • Business Glossary – Driving to “preferred” definitions

  13. Governance “Share what you should” begins with Transparency and ends with Quality Transparency Quality MRR Models, Metadata, Definitions Authoritative Sources Source 2 Source 1 Source 3 Source N ………… We follow the W3C Principle: “If it is not accessible… then it does not exist!” On Transparency, We Lead By Example!

  14. Web App #3 • Code Lookup – authoritative source for codes!

  15. EDMO Discipline Credibility Transparency Policy Process Standards Authoritative Sources Data Warehouse An EDMO needs an Operational Arm! Discipline Transparency Credibility These three elements must be implemented together!

  16. Web App #4 – Transparency in Job #1 • Data Management Portal DM Portal N A V I G A T I O N Announcements Introduction Statistics Interface to Web-Apps RSS Feed Gauges If it does not exist on the DM Portal, then it does not exist!

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