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Data-Ed Webinar: Data Governance Strategies

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Much like project team management and home improvement, Data Governance sounds a lot simpler than it actually is. In a nutshell, Data Governance is the process by which an organization delegates responsibility and exercises control over mission-critical data assets. In practice, though, Data Governance directs how all other Data Management functions are performed, meaning that much of your Data Management strategy’s capacity to function at all depends on your effectiveness in governing its implementation. Understanding these aspects of governance is necessary to eliminate the ambiguity that often surrounds effective Data Management and stewardship programs, since the goal of governance is to manage the data that supports organizational strategy.

This webinar will:

Illustrate what Data Governance functions are required for effective Data Management, how they fit with other Data Management disciplines, and why Data Governance can be tricky for many organizations
Help you develop a detailed vocabulary and set of narratives to facilitate understanding of your business objectives and imperatives that demand governance
Provide direction for selling Data Governance to organizational management as a specifically motivated initiative
Discuss foundational Data Governance concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)

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Data-Ed Webinar: Data Governance Strategies

  1. 1. Peter Aiken, Ph.D. Data Governance Strategies Copyright 2018 by Data Blueprint Slide # !1 • DAMA International President 2009-2013 • DAMA International Achievement Award 2001 (with Dr. E. F. "Ted" Codd • DAMA International Community Award 2005 Peter Aiken, Ph.D. • 33+ years in data management • Repeated international recognition • Founder, Data Blueprint (datablueprint.com) • Associate Professor of IS (vcu.edu) • DAMA International (dama.org) • 10 books and dozens of articles • Experienced w/ 500+ data management practices • Multi-year immersions:
 – US DoD (DISA/Army/Marines/DLA)
 – Nokia
 – Deutsche Bank
 – Wells Fargo
 – Walmart
 – … PETER AIKEN WITH JUANITA BILLINGS FOREWORD BY JOHN BOTTEGA MONETIZING DATA MANAGEMENT Unlocking the Value in Your Organization’s Most Important Asset. The Case for the Chief Data Officer Recasting the C-Suite to Leverage Your MostValuable Asset Peter Aiken and Michael Gorman Copyright 2018 by Data Blueprint Slide #
  2. 2. Experian enables organizations to unlock the power of data. We focus on the quality of our clients’ information so they can explore the meaningful ways they can use it. We have the data, expertise, and proven technology to help our customers quickly turn information into insight. To learn more, visit www.edq.com.
  3. 3. 2 © Experian Data quality defined Cleansing Standardization Matching MonitoringEnrichment Profiling
  4. 4. 3 © Experian Data quality is the cornerstone of data governance Data governance and data quality are two sides of the same coin.
  5. 5. 4 © Experian The most valuable data is data you can trust 95% of businesses struggle to implement data governance programs Accurate Clean Complete Consistent Consolidated Controlled
  6. 6. Confusion • IT thinks data is a business problem – "If they can connect to the server, then my job is done!" • The business thinks IT is managing data adequately – "Who else would be taking care of it?" !3Copyright 2018 by Data Blueprint Slide # Separating the Wheat from the Chaff !4Copyright 2018 by Data Blueprint Slide #
  7. 7. Separating the Wheat from the Chaff • Better organized data increases in value • Poor data management practices are costing organizations much money/time/effort • Minimally 80% of organizational data is ROT – Redundant – Obsolete – Trivial • The question is – Which data to eliminate? !5Copyright 2018 by Data Blueprint Slide # Incomplete Data Assets Win! Data 
 Assets Financial 
 Assets Real
 Estate Assets Inventory Assets Non- depletable Available for subsequent use Can be 
 used up Can be 
 used up Non- degrading √ √ Can degrade
 over time Can degrade
 over time Durable Non-taxed √ √ Strategic Asset √ √ √ √ Data Assets Win! • Today, data is the most powerful, yet underutilized and poorly managed organizational asset • Data is your – Sole – Non-depletable – Non-degrading – Durable – Strategic • Asset – Data is the new oil! – Data is the new (s)oil! – Data is the new bacon! • As such, data deserves: – It's own strategy – Attention on par with similar organizational assets – Professional ministration to make up for past neglect !6Copyright 2018 by Data Blueprint Slide # Asset: A resource controlled by the organization as a result of past events or transactions and from which future economic benefits are expected to flow [Wikipedia]
  8. 8. Managing Data with Guidance? !7Copyright 2018 by Data Blueprint Slide # • Federal employees • 44 users from whitehouse.gov • Thousands of military and 
 government e-mails • Canadian citizens • One-fifth of Quebec Managing Data with Guidance? !8Copyright 2018 by Data Blueprint Slide #
  9. 9. 
 Ashley
 Madison
 37,000,000 
 
 25,000,000
 OPM 
 
 
 70,000,000
 Target How the Government Jeopardized 
 Our National Security 
 for More than a Generation !9Copyright 2018 by Data Blueprint Slide # !10Copyright 2018 by Data Blueprint Slide # https://oversight.house.gov/report/opm-data-breach-government-jeopardized-national-security-generation/ How the Government Jeopardized Our National Security for More than a Generation
  10. 10. Lewis in front of the cummins safe !11Copyright 2018 by Data Blueprint Slide # ! !12Copyright 2018 by Data Blueprint Slide # Beth Jacobs abruptly 
 resigned in March These decisions have consequences!
  11. 11. Why is Data Governance important? • Cost organizations millions each year in – Productivity – Redundant and siloed efforts – Poorly thought out hardware and software purchases – Delayed decision making using inadequate information – Reactive instead of proactive initiatives – 20-40% of IT spending can be reduced through better data governance !13Copyright 2018 by Data Blueprint Slide # The DAMA Guide to the Data Management Body of Knowledge • Published by DAMA International – The professional association for Data Managers (40 chapters worldwide) • DM BoK organized around – Primary data management functions focused around data delivery to the organization – Organized around several environmental elements !14Copyright 2018 by Data Blueprint Slide # Data 
 Management Functions
  12. 12. Data Governance from the DMBOK !15Copyright 2018 by Data Blueprint Slide # from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International Data Governance Strategies • Strategy – Term of Recent Usage – Context: Organizational -> IT -> Data – Difficult Choices • Data Governance – What is it? – Why is it important? – Requirements for Effective Data Governance • Data Governance Components – Frameworks – Building Blocks – Checklists – Worst Practices • Data Governance Strategy in Action (Storytelling) • Take Aways/References/Q&A !16Copyright 2018 by Data Blueprint Slide # Tweeting now: #dataed
  13. 13. !17Copyright 2018 by Data Blueprint Slide # Organizational
 Strategy Data Strategy IT Projects Organizational Operations Data Governance Data Strategy and Data Governance in Context Data asset support for 
 organizational strategy What the data assets do to support strategy How well the data strategy is working Operational feedback How data is delivered by IT How IT supports strategy Other aspects of organizational strategy !18Copyright 2018 by Data Blueprint Slide # Data Strategy Data Governance Data Strategy & Data Governance What the data assets do to support strategy
 How well the data strategy is working
 (Business Goals) (Metadata)
  14. 14. Simon Sinek: How great leaders inspire action !19Copyright 2018 by Data Blueprint Slide # http://www.ted.com/talks/simon_sinek_how_great_leaders_inspire_action.html 
 
 
 
 
 
 
 
 
 What 
 
 
 
 
 
 How Why • “It’s not what you do, it’s why you do it” • Rev. Martin Luther King Jr. gave the - "I have a dream speech" - not the - "I have a plan speech" What is a Strategy? • Current use derived from military • "a pattern in a stream of decisions" [Henry Mintzberg] !20Copyright 2018 by Data Blueprint Slide #
  15. 15. Strategy in Action: Napoleon defeats a larger enemy • Question? – How to I defeat the competition when their forces are bigger than mine? • Answer: – Divide 
 and 
 conquer! – “a pattern 
 in a stream 
 of decisions” !21Copyright 2018 by Data Blueprint Slide # – “a pattern 
 in a stream 
 of decisions” !22Copyright 2018 by Data Blueprint Slide # Supply Line Metadata
  16. 16. First Divide !23Copyright 2018 by Data Blueprint Slide # !24Copyright 2018 by Data Blueprint Slide # Then Conquer
  17. 17. Wayne Gretzky’s
 Definition of Strategy He skates to where he 
 thinks the puck will be ... !25Copyright 2018 by Data Blueprint Slide # Former Walmart Business Strategy !26Copyright 2018 by Data Blueprint Slide # Every Day Low Price
  18. 18. Corporate Governance • "Corporate governance - which can be defined narrowly as the relationship of a company to its shareholders or, more broadly, as its relationship to society….", 
 Financial Times, 1997. • "Corporate governance is about promoting corporate fairness, transparency and accountability" James Wolfensohn, World Bank, President Financial Times, June 1999. • “Corporate governance deals with the ways in which suppliers of finance to corporations assure themselves of getting a return on their investment”,
 The Journal of Finance, Shleifer and Vishny, 1997. !27Copyright 2018 by Data Blueprint Slide # Definition of IT Governance IT Governance: • "putting structure around how organizations align IT strategy with business strategy, ensuring that companies stay on track to achieve their strategies and goals, and implementing good ways to measure IT’s performance. • It makes sure that all stakeholders’ interests 
 are taken into account and that processes
 provide measurable results. • An IT governance framework should 
 answer some key questions, such 
 as how the IT department is functioning 
 overall, what key metrics management 
 needs and what return IT is giving back 
 to the business from the investment it’s 
 making." CIO Magazine (May 2007) IT Governance Institute, five areas of focus: • Strategic Alignment • Value Delivery • Resource Management • Risk Management • Performance Measures !28Copyright 2018 by Data Blueprint Slide #
  19. 19. No clear connection exists between to business priorities and IT initiatives !29Copyright 2018 by Data Blueprint Slide # Grow expenses slower than sales Grow operating income faster than sales Pass on savings Drive efficiency with technology Leverage scale globally Leverage expertise Deploy new formats Grow productivity of existing assets Attract new members Expand into new channels Enter new markets Make acquisitions Produce significant free cash flow Drive ROI performance Deliver greater shareholder value Customer Perspectiv e Open new stores Develop new, innovative formats Appeal to new demographics Integrate shopping experience Develop new, innovative formats Remain relevant to all customers Increase "Green" Image Internal Perspectiv e Create competitive advantages Improve use of information Strengthen supply chain Improve Associate productivity Making acquisitions Increase benefit from our global expertise Present consistent view and experience Integrate channels Match staffing to store needs Increase sell through Financial Perspectiv e Reduce expenses Inventory Management Human and Intell. Capital investment Manage new facilities Improve Sales and margin by facilities Increased member-base revenues Revenue growth Cash flow Return on Capital Walmart Strategy Map See more uniform brand and retail experience Leverage Growth Return Gross Margin Improvement CEOPerspective Attract more customers & have customer purchasing more Associate Productivity Customer Insights Human Capital Corp. Reputation Acquisition Strategic Planning Real estate CRM CRM Analytic and reporting processes Corporate Reputation - Risk Management, Compliance, Marketing, IT and Data Governance Corporate Processes Corporate Data Inventory Mgmt TransformationPortfolio Supply Chain Multi ChannelMerchant ToolsSupply Chain Strategic Initiatives AcctingSales Transactional Processing Logistics AssociateLocations and Codes Item CustomerSuppliers Retail Planning ( Alignment Gap ) Adapted from John Ladley Data Strategy in Context !30Copyright 2018 by Data Blueprint Slide # Organizational
 Strategy IT Strategy Data Strategy
  20. 20. Organizational
 Strategy IT Strategy Data Strategy This is wrong! !31Copyright 2018 by Data Blueprint Slide # Organizational
 Strategy IT Strategy Data Strategy Organizational
 Strategy IT Strategy This is correct … !32Copyright 2018 by Data Blueprint Slide # Data Strategy
  21. 21. Data Governance Strategies • Strategy – Term of Recent Usage – Context: Organizational -> IT -> Data – Difficult Choices • Data Governance – What is it? – Why is it important? – Requirements for Effective Data Governance • Data Governance Components – Frameworks – Building Blocks – Checklists – Worst Practices • Data Governance Strategy in Action (Storytelling) • Take Aways/References/Q&A !33Copyright 2018 by Data Blueprint Slide # Tweeting now: #dataed Data Governance Strategies • Strategy – Term of Recent Usage – Context: Organizational -> IT -> Data – Difficult Choices • Data Governance – What is it? – Why is it important? – Requirements for Effective Data Governance • Data Governance Components – Frameworks – Building Blocks – Checklists – Worst Practices • Data Governance Strategy in Action (Storytelling) • Take Aways/References/Q&A !34Copyright 2018 by Data Blueprint Slide # Tweeting now: #dataed
  22. 22. !35Copyright 2018 by Data Blueprint Slide # TheFileNamingConventionCommittee'sOutput 7 Data Governance Definitions • The formal orchestration of people, process, and technology to enable an organization to leverage data as an enterprise asset. - The MDM Institute • A convergence of data quality, data management, business process management, and risk management surrounding the handling of data in an organization – Wikipedia • A system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods – Data Governance Institute • The execution and enforcement of authority over the management of data assets and the performance of data functions – KiK Consulting • A quality control discipline for assessing, managing, using, improving, monitoring, maintaining, and protecting organizational 
 information – IBM Data Governance Council • Data governance is the formulation of policy to optimize, secure, and leverage information as an enterprise asset by aligning the objectives of multiple 
 functions – Sunil Soares • The exercise of authority and control over the management of data 
 assets – DM BoK !36Copyright 2018 by Data Blueprint Slide #
  23. 23. Organizational Data Governance Purpose Statement • What does data governance mean to my organization? – Managing data with guidance – Getting some individuals (whose opinions matter) – To form a body (needs a formal purpose/authority) – Who will advocate/evangelize for (not dictate, enforce, rule) – Increasing scope and rigor of – Data-centric development practices !37Copyright 2018 by Data Blueprint Slide # Use Their Language ... • Getting access to data around here is like that Catherine Zeta Jones scene where she is having to get thru all those lasers … !38Copyright 2018 by Data Blueprint Slide #
  24. 24. What is the Difference Between DG and DM? • Data Governance – Policy level guidance – Setting general guidelines and direction – Example: All information not marked public should be considered confidential • Data Management – The business function of planning 
 for, controlling and delivering 
 data/information assets – Example: Delivering data 
 to solve business challenges !39Copyright 2018 by Data Blueprint Slide # What do I include in my Data Governance Program? • Security and Privacy of Data • Quality of Data • Life Cycle Management • Risk Management • Standards (Data Design, Models and Tools) • Content Valuation • Governance Tool Kits and Case Studies !40Copyright 2018 by Data Blueprint Slide #
  25. 25. Goals and Principles • To define, approve, and communicate data strategies, policies, standards, architecture, procedures, and metrics. • To track and enforce regulatory compliance and conformance to data policies, standards, architecture, and procedures. • To sponsor, track, and oversee the delivery of data management projects and services. • To manage and resolve data related issues. • To understand and promote the value of data assets. Illustration from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International !41Copyright 2018 by Data Blueprint Slide # Primary Deliverables • Data Policies • Data Standards • Resolved Issues • Data Management Projects and Services • Quality Data and Information • Recognized Data Value Illustration from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International !42Copyright 2018 by Data Blueprint Slide #
  26. 26. Roles and Responsibilities • Suppliers: – Business Executives – IT Executives – Data Stewards – Regulatory Bodies • Consumers: – Data Producers – Knowledge Workers – Managers and Executives – Data Professionals – Customers • Participants: – Executive Data Stewards – Coordinating Data Stewards – Business Data Stewards – Data Professionals – DM Executive – CIO Illustration from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International !43Copyright 2018 by Data Blueprint Slide # Practices and Techniques !44Copyright 2018 by Data Blueprint Slide # Illustration from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International • Data Value • Data Management Cost • Achievement of Objectives • # of Decisions Made • Steward Representation/Coverage • Data Professional Headcount • Data Management Process Maturity
  27. 27. 4 four up Goals and Principles • To define, approve, and communicate data strategies, policies, standards, architecture, procedures, and metrics. • To track and enforce regulatory compliance and conformance to data policies, standards, architecture, and procedures. • To sponsor, track, and oversee the delivery of data management projects and services. • To manage and resolve data related issues. • To understand and promote the value of data assets. Illustration from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International 132Copyright 2017 by Data Blueprint Slide # Primary Deliverables • Data Policies • Data Standards • Resolved Issues • Data Management Projects and Services • Quality Data and Information • Recognized Data Value Illustration from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International 133Copyright 2017 by Data Blueprint Slide # Roles and Responsibilities • Suppliers: – Business Executives – IT Executives – Data Stewards – Regulatory Bodies • Consumers: – Data Producers – Knowledge Workers – Managers and Executives – Data Professionals – Customers • Participants: – Executive Data Stewards – Coordinating Data Stewards – Business Data Stewards – Data Professionals – DM Executive – CIO Illustration from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International 134Copyright 2017 by Data Blueprint Slide # Practices and Techniques • Data Value • Data Management Cost • Achievement of Objectives • # of Decisions Made • Steward Representation/Coverage • Data Professional Headcount • Data Management Process Maturity 135Copyright 2017 by Data Blueprint Slide # Illustration from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International !45Copyright 2018 by Data Blueprint Slide # Data Steward • Business data steward – Manage from the perspective of business elements (i.e. business definitions 
 and data quality) • Technical data steward – Focus on the use of data by systems and models (i.e. code operation) • Project data steward – Gather definitions, quality rules and issues for referral to business/technical stewards • Domain data steward – Manage data/metadata required across multiple business areas (i.e. customer data) • Operational data steward – Directly input data or instruct those who do; aid business 
 stewards identifying root cause and addressing issues • Metadata Data Steward – Manage metadata as an asset • Legacy Data Steward – Manage legacy data as an asset • Data steward auditor – Ensures compliance with data guidance • Data steward manager – Planning, organizing, leading and controlling !46Copyright 2018 by Data Blueprint Slide # (list adapted from Plotkin, 2014)
  28. 28. one who actively directs the use of 
 organizational data assets in support 
 of specific mission objectives • one who actively directs !47Copyright 2018 by Data Blueprint Slide # Steward, Data !48Copyright 2018 by Data Blueprint Slide # Managing Data with Guidance What is Data Governance?
  29. 29. Ask anyone ... • Would you want your sole, non- depletable, non- degrading, durable asset managed without guidance? !49Copyright 2018 by Data Blueprint Slide # Data Governance Strategies • Strategy – Term of Recent Usage – Context: Organizational -> IT -> Data – Difficult Choices • Data Governance – What is it? – Why is it important? – Requirements for Effective Data Governance • Data Governance Components – Frameworks – Building Blocks – Checklists – Worst Practices • Data Governance Strategy in Action (Storytelling) • Take Aways/References/Q&A !50Copyright 2018 by Data Blueprint Slide # Tweeting now: #dataed
  30. 30. Making a Better 
 Data Governance Sandwich !51Copyright 2018 by Data Blueprint Slide # Standard data Data supply Data literacy Making a Better Data Governance Sandwich !52Copyright 2018 by Data Blueprint Slide # Data literacy Standard data Data supply
  31. 31. Making a Better Data Governance Sandwich !53Copyright 2018 by Data Blueprint Slide # Standard data Data supply Data literacy Making a Better Data Sandwich !54Copyright 2018 by Data Blueprint Slide # Standard data Data supply Data literacy This cannot happen without engineering and architecture! Quality engineering/architecture work products 
 do not happen accidentally!
  32. 32. !55Copyright 2018 by Data Blueprint Slide # • Before further construction could proceed • No IT equivalent Our barn had to pass a foundation inspection Data Governance Frameworks • A system of ideas for guiding analyses • A means of organizing 
 project data • Priorities for data decision making • A means of assessing progress – Don’t put up walls until foundation inspection is passed – Put the roof on ASAP • Make it all dependent upon continued funding !56Copyright 2018 by Data Blueprint Slide #
  33. 33. Data Governance from the DMBOK !57Copyright 2018 by Data Blueprint Slide # from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International Data Governance Institute • A system of ideas for guiding analyses • A means of organizing project data • Data integration priorities decision making framework • A means of assessing progress !58Copyright 2018 by Data Blueprint Slide # http://www.datagovernance.com/
  34. 34. KiK Consulting • A system of ideas for guiding analyses • A means of organizing project data • Data integration priorities decision making framework • A means of assessing progress !59Copyright 2018 by Data Blueprint Slide # http://www.kikconsulting.com/ IBM Data Governance Council • A system of ideas for guiding analyses • A means of organizing project data • Data integration priorities decision making framework • A means of assessing progress !60Copyright 2018 by Data Blueprint Slide # http://www-01.ibm.com/software/data/system-z/data-governance/workshops.html
  35. 35. Elements of Effective Data Governance !61Copyright 2018 by Data Blueprint Slide # See IBM Data Governance Council, http://www-01.ibm.com/software/tivoli/ governance/servicemanagement/ data-governance.html. Baseline Consulting (sas.com) !62Copyright 2018 by Data Blueprint Slide #
  36. 36. American College Personnel Association !63Copyright 2018 by Data Blueprint Slide # Data Governance Checklist ✓ Decision-Making Authority ✓ Standard Policies and Procedures ✓ Data Inventories ✓ Data Content Management ✓ Data Records Management ✓ Data Quality ✓ Data Access ✓ Data Security and Risk Management !64Copyright 2018 by Data Blueprint Slide # Source: “Data Governance Checklist for Educators” by Angela Guess; http://www.dataversity.net/archives/5198
  37. 37. Scorecard: Data Governance Practices/Techniques • Data Value • Data Management 
 Cost • Achievement of 
 Objectives • # of Decisions Made • Steward Representation/Coverage • Data Professional Headcount • Data Management Process Maturity !65Copyright 2018 by Data Blueprint Slide # from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International 10 DG Worst Practices 1. Buy-in but not Committing: Business vs. IT 2. Ready, Fire, Aim 3. Trying to Solve World Hunger or Boil the Ocean 4. The Goldilocks Syndrome 5. Committee Overload 6. Failure to Implement 7. Not Dealing with Change Management 8. Assuming that Technology Alone is the Answer 9. Not Building Sustainable and Ongoing Processes 10. Ignoring “Data Shadow Systems” !66Copyright 2018 by Data Blueprint Slide #
  38. 38. Data Governance Strategies • Strategy – Term of Recent Usage – Context: Organizational -> IT -> Data – Difficult Choices • Data Governance – What is it? – Why is it important? – Requirements for Effective Data Governance • Data Governance Components – Frameworks – Building Blocks – Checklists – Worst Practices • Data Governance Strategy in Action (Storytelling) • Take Aways/References/Q&A !67Copyright 2018 by Data Blueprint Slide # Tweeting now: #dataed Toyota versus Detroit Engine Mounting (Circa 1994) • Detroit – 3 different bolts – 3 different wrenches – 3 different bolt inventories • Toyota – 1 bolt used 
 for all three assemblies – 1 bolt inventory – 1 type of wrench !68Copyright 2018 by Data Blueprint Slide #
  39. 39. Toyota versus Detroit Engine Mounting (Circa 1994) • Detroit – many different bolts – many different wrenches – many different bolt inventories • Toyota – same bolts used for all three assemblies – same 1 bolt inventory – same 1 type of wrench !69Copyright 2018 by Data Blueprint Slide # IT Project or Application-Centric Development Original articulation from Doug Bagley @ Walmart !70Copyright 2018 by Data Blueprint Slide # Data/ Information IT
 Projects 
 Strategy • In support of strategy, organizations implement IT projects • Data/information are typically considered within the scope of IT projects • Problems with this approach: – Ensures data is formed to the applications and not around the organizational-wide information requirements – Process are narrowly formed around applications – Very little data reuse is possible
  40. 40. Data-Centric Development Original articulation from Doug Bagley @ Walmart !71Copyright 2018 by Data Blueprint Slide # IT
 Projects Data/
 Information 
 Strategy • In support of strategy, the organization develops specific, shared data-based goals/objectives • These organizational data goals/ objectives drive the development of specific IT projects with an eye to organization-wide usage • Advantages of this approach: – Data/information assets are developed from an organization-wide perspective – Systems support organizational data needs and compliment organizational process flows – Maximum data/information reuse 
 Q1
 Keeping the doors open
 (little or no proactive 
 data management) Q2
 Increasing organizational efficiencies/effectiveness Q3
 Using data to create 
 strategic opportunities
 Q4
 Both Improve Operations Innovation Only 1 is 10 organizations has a board approved data strategy! Data Governance Strategy Choices !72Copyright 2018 by Data Blueprint Slide #
  41. 41. • Telemetric data2005-07-17-srm-003.jpg Why management doesn't need to understand metadata - Link business objectives to technical capabilities !73Copyright 2018 by Data Blueprint Slide # healthcare.gov • 55 Contractors! • 6 weeks from launch and requirements not finalized • "Anyone who has written a line of code or built a system from the ground-up cannot be surprised or even mildly concerned that Healthcare.gov did not work out of the gate," 
 
 Standish Group International Chairman Jim Johnson said in a recent podcast. 
 • "The real news would have been if it actually did work. The very fact that most of it did work at all is a success in itself." !74Copyright 2018 by Data Blueprint Slide # • "It was pretty obvious from the first look that the system hadn't been designed to work right," says Marty Abbott. "Any single thing that slowed down would slow everything down." • Software programmed to 
 access data using 
 traditional technologies • Data components incorporated 
 "big data technologies"
 http://www.slate.com/articles/technology/bitwise/2013/10/ problems_with_healthcare_gov_cronyism_bad_management_and_too_ many_cooks.html
  42. 42. Formalizing the Role of U.S. Army Data Governance !75Copyright 2018 by Data Blueprint Slide # Suicide Mitigation !76Copyright 2018 by Data Blueprint Slide #
  43. 43. !77Copyright 2018 by Data Blueprint Slide # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 !78Copyright 2018 by Data Blueprint Slide #
  44. 44. Senior Army Official • Room full of Colonels • A very heavy dose of management support • Advised the group of his opinion on the matter • Any questions as to future direction – "They should make an appointment to speak directly with me!" • Empower the team – The conversation turned from "can this be done?" to "how are we going to accomplish this?" – Mistakes along the way would be tolerated – Implement a workable solution in prototype form !79Copyright 2018 by Data Blueprint Slide # Communication Patterns • !80Copyright 2018 by Data Blueprint Slide # Source: The Challenge and the Promise: Strengthening the Force, Preventing Suicide and Saving Lives - The Final Report of the Department of Defense Task Force on the Prevention of Suicide by Members of the Armed Forces - August 2010
  45. 45. Vocabulary is Important-Tank, Tanks, Tankers, Tanked !81Copyright 2018 by Data Blueprint Slide # How one inventory item proliferates data throughout the chain !82Copyright 2018 by Data Blueprint Slide # 555 Subassemblies & subcomponents 17,659 Repair parts or Consumables System 1:
 18,214 Total items
 75 Attributes/ item
 1,366,050 Total attributes System 2
 47 Total items
 15+ Attributes/item
 720 Total attributes System 3 16,594 Total items 73 Attributes/item 1,211,362 Total attributes System 4
 8,535 Total items
 16 Attributes/item
 136,560 Total attributes System 5
 15,959 Total items
 22 Attributes/item
 351,098 Total attributes Total for the five systems show above:
 59,350 Items
 179 Unique attributes
 3,065,790 values
  46. 46. Business Implications • National Stock Number (NSN) 
 Discrepancies – If NSNs in LUAF, GABF, and RTLS are 
 not present in the MHIF, these records 
 cannot be updated in SASSY – Additional overhead is created to correct 
 data before performing the real 
 maintenance of records • Serial Number Duplication – If multiple items are assigned the same 
 serial number in RTLS, the traceability of 
 those items is severely impacted – Approximately $531 million of SAC 3 
 items have duplicated serial numbers • On-Hand Quantity Discrepancies – If the LUAF O/H QTY and number of items serialized in RTLS conflict, there can be no clear answer as to how many items a unit actually has on-hand – Approximately $5 billion of equipment does not tie out between the LUAF and RTLS !83Copyright 2018 by Data Blueprint Slide # Barclays Excel Spreadsheet Horror • Barclays preparing to buy Lehman’s Brothers assets. • 179 dodgy Lehman’s contracts were almost accidentally purchased by Barclays because of an Excel spreadsheet reformatting error • A first-year associate reformatted an Excel contracts spreadsheet – Predictably, this work was done long after normal business hours, just after 11:30 p.m... • The Lehman/Barclays sale closed on September 22nd • the 179 contracts were marked as “hidden” in Excel, and those entries became “un-hidden” when when globally reformatting the document … • … and the sale closed … !84Copyright 2018 by Data Blueprint Slide #
  47. 47. 
 
 CLUMSY typing cost a Japanese bank at least £128 million and staff their Christmas bonuses yesterday, after a trader mistakenly sold 600,000 more shares than he should have. The trader at Mizuho Securities, who has not been named, fell foul of what is known in financial circles as “fat finger syndrome” where a dealer types incorrect details into his computer. He wanted to sell one share in a new telecoms company called J Com, for 600,000 yen (about £3,000). Possibly the Worst Data Governance Example Mizuho Securities Mizuho Securities • Wanted to sell 1 share for 600,000 yen • Sold 600,000 shares for 1 yen • $347 million loss • In-house system did not have limit checking • Tokyo stock exchange system did not have limit checking ... • … and doesn't allow order cancellations !85Copyright 2018 by Data Blueprint Slide # Data Governance Strategies • Strategy – Term of Recent Usage – Context: Organizational -> IT -> Data – Difficult Choices • Data Governance – What is it? – Why is it important? – Requirements for Effective Data Governance • Data Governance Components – Frameworks – Building Blocks – Checklists – Worst Practices • Data Governance Strategy in Action (Storytelling) • Take Aways/References/Q&A !86Copyright 2018 by Data Blueprint Slide # Tweeting now: #dataed
  48. 48. You can accomplish Advanced Data Practices without becoming proficient in the Foundational Data Management Practices however this will: • Take longer • Cost more • Deliver less • Present 
 greater
 risk
(with thanks to Tom DeMarco) Data Management Practices Hierarchy Advanced 
 Data 
 Practices • MDM • Mining • Big Data • Analytics • Warehousing • SOA Foundational Data Management Practices Data Platform/Architecture Data Governance Data Quality Data Operations Data Management Strategy Technologies Capabilities !87Copyright 2018 by Data Blueprint Slide # Take Aways • Need for DG is increasing – Increase in data volume – Lack of practice improvement • DG is a new discipline – Must conform to constraints – No one best way • DG must be driven by a data strategy complimenting organizational strategy • Comparing DG frameworks can be useful • DG directs data management efforts • The language of DG is metadata • Process improvement can improve DG practices !88Copyright 2018 by Data Blueprint Slide #
  49. 49. !89 IT Business Data As Is State of Data Copyright 2018 by Data Blueprint Slide # To Be State of Data !90Copyright 2018 by Data Blueprint Slide # IT Business Data
  50. 50. !91Copyright 2018 by Data Blueprint Slide # PETER AIKEN WITH JUANITA BILLINGS FOREWORD BY JOHN BOTTEGA MONETIZING DATA MANAGEMENT Unlocking the Value in Your Organization’s Most Important Asset. References Websites • Data Governance Book Data Governance Book Compliance Book !92Copyright 2018 by Data Blueprint Slide #
  51. 51. IT Governance Books !93Copyright 2018 by Data Blueprint Slide # 10124 W. Broad Street, Suite C Glen Allen, Virginia 23060 804.521.4056 Copyright 2018 by Data Blueprint Slide # !94

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