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Data Governance
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Data Governance

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  1. Data Governance

  2. Overview • Background • Data Governance Defined • Data Governance Maturity Models & Assessments • Data Governance Frameworks • Next Steps • Data Governance Basics to Consider • Reading & Resources

  3. Background: Zenith Zenith Provide strategy and implementation services in specialty information management disciplines where the client is exposed to significant implementation risk. • Data Governance • Data Quality • Data Migration • Data Warehousing & Business Intelligence • Metadata Management • Master Data Management

  4. Background: Zenith Hudson

  5. Background: Stuart Brown • Certified Information Management Professional – Data Governance • Data Governance specialist at Zenith Solutions • Award winning data quality and data governance initiatives (ACT Health - IAIDQ APAC Data Quality Award, 2012) • Consulted across industries including Private Health Insurance, Public Healthcare, Defence, and Government.

  6. Data Governance: Defined • “The coordination of people, processes, and technology in order to manage and optimise the use of data as a valued enterprise asset” • “The exercise of authority, control, and shared decision-making (planning, monitoring, and enforcement) over the management of data assets.” DAMA Dictionary of Data Management, 2nd Edition

  7. Data Governance: Defined • Bridging business and IT for data related decisions and initiatives • Largely driven by audit and compliance in the US financial sector • Communication, change management, and soft skills are the core of good data governance • Technology helps, but not essential (at lower maturity levels) • Every organisation has some form of data governance!

  8. Data Governance Maturity Assessment • Open discussion with stakeholders at all levels • One on one interviews, group workshops, consulting SMEs • Pre-determined questions to be answered and maturity level determined • Identify current state maturity and a desired state • Ensure it is an educational process • The success of your data governance initiative can be highly dependant on a Maturity Assessment! The biggest part of the process: CONSULTING

  9. Data Governance Maturity Assessment Maturity Assessment Report

  10. Decide on a Maturity Model • Is there something similar in use throughout your organisation? • Can you leverage from a vendor? • Are there other options that suit your needs?

  11. Data Governance Maturity Models: CMM & CMMI

  12. Data Governance Maturity Models: IBM

  13. Data Governance Maturity Models: DataFlux

  14. Data Governance Maturity Models: Kalido

  15. Data Governance Framework: What is it? • The rules of engagement with data management in your organisation • Roles and Responsibilities, Decision Rights, Accountability, Data Governance Organisation and Stewardship program • Requires a comprehensive maturity assessment • Built to desired maturity level • Must be digestible and suited for your organisation!

  16. Data Governance Framework A Tailored Data Governance Framework

  17. Data Governance Framework: The Burning Questions • What is the scope of your program or initiative? • What data will be governed? • How will you approach Stewardship? • What are your business drivers and benefits? • How will you measure success or progress? • Who is your Data Governance Organisation?

  18. The Zenith Data Governance Framework Information & Data Governance Enablers • 11 Components or Domains • Sub-Components or Categories People & Culture Policy, Procedures, Processes Data Training & Communication Coredisciplines Data Quality Information Lifecycle Management Security, Compliance& Privacy  Supporting disciplines Architecture & Standards Metadata, Master Data Management Audit, Monitoring, Reporting Process Technology People & Process People, Process & Technology

  19. The DMBOK Functional Framework • 10 Components or Domains • Environmental Elements

  20. Data Governance Framework: Implementation Approaches • Comprehensive • Complete roll out, boiling the ocean, less rework • Partial • Focused on one capability, covers pain points, some rework if later it moves to a ‘comprehensive model’ • Blended • Focus on immediate needs and work towards strategic goals • Some rework, less than partial

  21. Next Steps: Data Governance Roadmap • What will be the implementation approach? • Where do you need to reach? • What activities will get you there? • What projects will be dependant on each other?

  22. Data Governance Basics: Stewardship • “The formal, specifically assigned, and entrusted accountability for business (non-technical) responsibilities ensuring effective control and use of information resources” DAMA Dictionary of Data Management, 2nd Edition

  23. Data Governance Basics: Stewardship • “A business leader and/or subject matter expert designed as accountable for: • The identification of operational and Business Intelligence data requirements within an assigned subject area; • The quality of data names, business definitions, data integrity rules and domain values within an assigned subject area; • Compliance with regulatory requirements and conformance to internal data policies and data standards; • Application of appropriate security controls; • Analysing and improving data quality; and • Identifying and resolving data related issues. • Data Stewards are often categorised as executive data stewards, business data stewards, or coordinating data stewards” DAMA Dictionary of Data Management, 2nd Edition

  24. Data Governance Basics: Stewardship • Generally speaking, there are 4 types of Stewardship • By Data Object or Domain (Customer, Employee, MDM); • By Business Unit (HR, Finance, etc.); • By Process (New Customer); or • By Project/System. • Generally speaking, there are 3 levels of Data Stewards • Executive Data Steward (Business Owners or Data Owners) • Coordinating Data Steward (Middle Management) • Business Data Steward (SMEs)

  25. Data Governance Basics: Stewardship You need to be… • Leader • Respected • Communicator • Change Agent • Consensus Builder … and have • Authority • Organisational Skills

  26. Data Governance Basics: Three Tiered Governance Data Governance Council Data Stewardship Committee Sub-Forum or Working Group Sub-Forum or Working Group Sub-Forum or Working Group Sub-Forum or Working Group

  27. Data Governance Basics: Three Tiered Data Governance • Data Governance Council • “C” Level or Executive level (DAMA – Exec Stewards), Resourcing and Mandate • Strategic level governance! • Data Stewardship Committee • Management/Middle-Management (DAMA – Coordinating Stewards) • Integrate the work of Data Stewards, or Data Stewardship teams; • Tactical level governance! • Sub-Forums, Stewardship Teams, Competency Centre, Centres of Excellence. Working Groups • SME-level DAMA – Business Stewards • Focused on a framework component(s) or topical area(s) i.e. what type of Stewardship program is there? • Operational level governance!

  28. Summary • You already have some form of data governance • Maturity Assessments are a corner stone to building your data governance strategy and approach • Form follows function and solution follows strategy • Work for the greater good, cater to your organisations needs and pain points • Find your champions and follow the path of least resistance

  29. Recommended Reading • The DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK) (by DAMA International) • IBM Data Governance Unified Process (by Sunil Soares) • The Data Governance Imperative (by Steve Sarsfield) • The Data Asset: How Smart Companies Govern Their Data for Business Success (by Tony Fisher) • Selling Information Governance to the Business: Best Practices by Industry and Job Function (by Sunil Soares)

  30. Quick Self-Assessment Resources • Mike2.0 ( • IBM Info Gov Community ( • Kalido (

  31. QUESTIONS? 0428202129