DataEd Slides: The Seven Deadly Data Sins
3 likes845 views
Peter Aiken's presentation discusses the critical importance of effective data management strategies, emphasizing the need to align organizational data goals with IT projects. It identifies key challenges, termed the 'seven deadly data sins,' such as lack of qualified data leadership and poor cultural readiness, which hinder effective data utilization. Aiken stresses the value of treating data as a strategic asset to enhance operational efficiencies and drive innovative solutions within organizations.
DataEd Slides: The Seven Deadly Data Sins
- 1. Peter Aiken, PhD Exorcising the Seven Deadly Data Sins !1 • DAMA International President 2009-2013 / 2018 • DAMA International Achievement Award 2001 (with Dr. E. F. "Ted" Codd • DAMA International Community Award 2005 Copyright 2018 by Data Blueprint Slide # !2 Peter Aiken, Ph.D. • I've been doing this a long time • My work is recognized as useful • Associate Professor of IS (vcu.edu) • Founder, Data Blueprint (datablueprint.com) • DAMA International (dama.org) • 10 books and dozens of articles • Experienced w/ 500+ data management practices worldwide • 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.
- 2. George Box British Statistician (1919-2013) “All models are wrong, ... ... some are useful.” !3Copyright 2018 by Data Blueprint Slide # !4Copyright 2018 by Data Blueprint Slide # • The highest level data guidance available to an organization, ... • ... focusing data-related activities on articulated data goal achievements and ... • ... providing directional but specific guidance when faced with a stream of decisions or uncertainties about organizational data assets and their application toward business objectives Your Data Strategy Link to amazon.com
- 3. IT Project Failure Rates (1994-2015) Source: Standish Chaos Reports as reported at: http://standishgroup.com !5Copyright 2018 by Data Blueprint Slide # 0% 15% 30% 45% 60% 1994 1996 1998 2000 2002 2004 2006 2008 2010 2011 2012 2013 2014 2015 Failed Challenged Succeeded System HardwareProcessesPeople Software • A set of detailed methods, procedures, and routines established or formulated to carry out a specific activity, perform a duty, or solve a problem. • An organized, purposeful structure regarded as a whole and consisting of interrelated and interdependent elements (components, entities, factors, members, parts, etc.). These elements continually influence one another (directly or indirectly) to maintain their activity and the existence of the system, in order to achieve the goal of the system. http://www.businessdictionary.com/definition/system.html#ixzz23T7LyAjJ System !6Copyright 2018 by Data Blueprint Slide # DataData
- 4. How much data, by the minute! For the entirety of 2017, every minute of every day: • (almost) Seventy thousand hours of Netflix • (almost) a half million tweets • 15+ million texts • 3.5+ million google searches • 103+ million email spams !7Copyright 2018 by Data Blueprint Slide # https://www.domo.com/learn/data-never-sleeps-5 There will never be less data than right now! !8Copyright 2018 by Data Blueprint Slide # As articulated by Micheline Casey
- 5. !9Copyright 2018 by Data Blueprint Slide # Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges !10Copyright 2017 by Data Blueprint Slide # Exorcising the Seven Deadly Data Sins g Data- ng Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ailing to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7
- 6. Diagnosing Organizational Readiness !11Copyright 2018 by Data Blueprint Slide # adapted from the Managing Complex Change model by Dr. Mary Lippitt, 1987 Culture is the biggest impediment to a shift in organizational thinking about data! !12Copyright 2018 by Data Blueprint Slide # Credit: Image credit: Matt Vickers
- 7. Change the status quo! • Keep in mind that the appointment of a CDO typically comes from a high-level decision. In practice, it can trigger an array of problematic reactions within the organization including: – Confusion, – Uncertainty, – Doubt, – Resentment and – Resistance. • CDOs need to rise to the challenge of changing the status quo if they expect to lead the business in making data a strategic asset. – from What Chief Data Officers Need to Do to Succeed by Mario Faria !13Copyright 2018 by Data Blueprint Slide # Change Management & Leadership !14Copyright 2018 by Data Blueprint Slide #
- 8. QR Code for PeterStudy • Free Case Study Download• Free Case Study Download – http://dl.acm.org/citation.cfm?doid=2888577.2893482 or http://tinyurl.com/PeterStudy or scan the QR Code at the right !15Copyright 2018 by Data Blueprint Slide # Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges !16Copyright 2017 by Data Blueprint Slide # Exorcising the Seven Deadly Data Sins g Data- ng Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ailing to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7
- 9. The DAMA Guide to the Data Management Body of Knowledge !17Copyright 2018 by Data Blueprint Slide # Data Management Functions fromTheDAMAGuidetotheDataManagementBodyofKnowledge©2009byDAMAInternational • Good enough to criticize – All models are wrong – Some models are useful • Missing two important concepts – Optionality – Dependency Our barn had to pass a foundation inspection • Before further construction could proceed • No IT equivalent !18Copyright 2018 by Data Blueprint Slide #
- 10. You can accomplish Advanced Data Practices without becoming proficient in the Foundational Data 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 Practices Data Platform/Architecture Data Governance Data Quality Data Operations Data Management Strategy Technologies Capabilities !19Copyright 2018 by Data Blueprint Slide # V1 Organizations without a formalized data strategy V3 Data Strategy: Use data to create strategic opportunities V4 Data Strategy: both Improve Operations Innovation The focus of data strategy should be sequenced !20Copyright 2018 by Data Blueprint Slide # Only 1 is 10 organizations has a board approved data strategy! V2 Data Strategy: Increase organizational efficiencies/ effectiveness X X
- 11. Sequencing the Reasons for a Data Strategy !21Copyright 2018 by Data Blueprint Slide # Improve your organization’s data Improve the way your people use its data Improve the way your data and your people support your organizational strategy • Because data points to where valuable things are located • Because data has intrinsic value by itself • Because data has inherent combinatorial value • Valuing Data – Use data to measure change – Use data to manage change – Use data to motivate change • Creating a competitive advantage with data What did Rolls Royce Learn • Old model – Sell jet engines • New model – Sell hours of thrust power – Power-by-the-hour – No payment for down time – Wing to wing – When was it invented? !22Copyright 2018 by Data Blueprint Slide # from Nascar?
- 12. Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges !23Copyright 2017 by Data Blueprint Slide # Exorcising the Seven Deadly Data Sins g Data- ng Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ailing to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Data Implementation Framework !24Copyright 2018 by Data Blueprint Slide # • Benefits & Success Criteria • Capability Targets • Solution Architecture • Organizational Development Solution • Leadership & Planning • Project Dev. & Execution • Cultural Readiness Road Map • Organization Mission • Strategy & Objectives • Organizational Structures • Performance Measures Business Needs • Organizational / Readiness • Business Processes • Data Management Practices • Data Assets • Technology Assets Current State • Business Value Targets • Capability Targets • Tactics • Data Strategy Vision Strategic Data Imperatives Business Needs Existing Capabilities ExecutionBusiness Value New Capabilities
- 13. Data Management Program Expenses • 5 Data Managers – Each paid $100,000/year – Do they feel obligated to demonstrate $500,000 in benefits annually? • When will you be done? – "It's okay my CIO gave me 5 years!" – Revised benefits goal is $2.5 million Copyright 2018 by Data Blueprint Slide # !25 improving how the state prices and sells its goods and services, and more efficiently matching citizens to benefits when they enroll. “The first year of our data internship partnership has been a success,” said Governor McAuliffe. “The program has helped the state save time and money by making some of our internal processes more efficient and modern. And it has given students valuable real-world experience. I look forward to seeing what the second year of the program can accomplish.” “Data is an important resource that becomes even more critical as technology progresses,” said VCU President Michael Rao, Ph.D. “VCU is uniquely positioned, both in its location and through the wealth of talent at the School of Business, to help state agencies run their data- centric systems more efficiently, while giving our students hands-on practice in the development of data systems.” During their internships, pairs of VCU students work closely with state agency CIOs to identify specific business cases in which data can be used. Participants gain practical experience in using data to drive re-engineering, while participating CIOs have concrete examples of how to make better use of data to provide innovative and less costly services to citizens. "Working with the talented VCU students gave us a different perspective on what the data was telling us,” said Dave Burhop, Deputy Commissioner/CIO of the Virginia Department of Motor Vehicles. “The VCU interns provided an invaluable resource to the Governor’s Coordinating Council on Homelessness,” said Pamela Kestner, Special Advisor on Families, Children and Poverty. “They very effectively reviewed the data assets available in the participating state agencies and identified analytic content that can be used to better serve the homeless population.” “It's always useful to have ‘fresh eyes’ on data that we are used to seeing,” said Jim Rothrock, Commissioner of the Department for Aging and Rehabilitative Services. “Our interns challenged us and the way we interpret data. It was a refreshing and useful, and we cannot wait for new experiences with new students.” The data internships support Governor McAuliffe’s ongoing initiative to provide easier access to open data in Virginia. The internships also support treating data as an enterprise asset, one of four strategic goals of the enterprise information architecture strategy adopted by the Commonwealth in August 2013. Better use of data allows the Commonwealth to identify opportunities to avoid duplicative costs in collecting, maintaining and using information; and to integrate services across agencies and localities to improve responses to constituent needs and optimize government resources. Virginia Secretary of Technology Karen Jackson and CIO of the Commonwealth Nelson Moe are leading the effort on behalf of the state. Students who want to apply for internships should contact Peter Aiken (peter.aiken@vcu.edu) for additional information. !26Copyright 2018 by Data Blueprint Slide # Virginia Governor's Data Interns Program
- 14. Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges !27Copyright 2017 by Data Blueprint Slide # Exorcising the Seven Deadly Data Sins g Data- ng Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ailing to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7 acking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ately tions Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 IT Project or Application-Centric Development Original articulation from Doug Bagley @ Walmart !28Copyright 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
- 15. Data-Centric Development Original articulation from Doug Bagley @ Walmart !29Copyright 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 Data Strategy with Data Governance in Context !30Copyright 2018 by Data Blueprint Slide # Organizational Strategy Data Strategy IT Projects Organizational Operations Data Governance 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
- 16. !31Copyright 2018 by Data Blueprint Slide # Organizational Strategy Data Strategy Data Governance Data asset support for organizational strategy What the data assets do to support strategy How well the data strategy is working (Business Goals) (Metadata) IT Projects How data is delivered by IT Data Strategy and Governance in Strategic Context Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges !32Copyright 2017 by Data Blueprint Slide # Exorcising the Seven Deadly Data Sins g Data- ng Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ailing to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7 t Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 acking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ately tions Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7
- 17. Data is not a Project • Durable asset – An asset that has a usable life more than one year • Reasonable project deliverables – 90 day increments – Data evolution is measured in years • Data – Evolves - it is not created – Significantly more stable • Readymade data architectural components – Prerequisite to agile development • Only alternative is to create additional data siloes! !33Copyright 2018 by Data Blueprint Slide # Verification Maintenance Systems Development (as described by Winston Royce) !34Copyright 2018 by Data Blueprint Slide # Requirements Design Implementation Requirements Design Requirements DesignDesign Implementation Design Requirements Design Implementation $ ...
- 18. Project Implementation !35Copyright 2018 by Data Blueprint Slide # Develop/Implement Software Develop/Implement Data This approach can only work when no sharing of data occurs! !35 XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Projects Are Silos Copyright 2018 by Data Blueprint Slide # Project 1 Project 2 Shared data structures require programmatic development and evaluation Project 3 X XX X X X X X XX X
- 19. Differences between Programs and Projects • Programs are Ongoing, Projects End – Managing a program involves long term strategic planning and continuous process improvement is not required of a project • Programs are Tied to the Financial Calendar – Program managers are often responsible for delivering results tied to the organization's financial calendar • Program Management is Governance Intensive – Programs are governed by a senior board that provides direction, oversight, and control while projects tend to be less governance-intensive • Programs Have Greater Scope of Financial Management – Projects typically have a straight-forward budget and project financial management is focused on spending to budget while program planning, management and control is significantly more complex • Program Change Management is an Executive Leadership Capability – Projects employ a formal change management process while at the program level, change management requires executive leadership skills and program change is driven more by an organization's strategy and is subject to market conditions and changing business goals !37Copyright 2018 by Data Blueprint Slide # Adapted from http://top.idownloadnew.com/program_vs_project/ and http://management.simplicable.com/management/new/program-management-vs-project-management Your data program must last at least as long as your HR program! Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges !38Copyright 2017 by Data Blueprint Slide # Exorcising the Seven Deadly Data Sins g Data- ng Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ailing to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7t Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 acking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ately tions Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7
- 20. Data ... • As a subject is – Complex and detailed – Taught inconsistently, and – Poorly understood !39Copyright 2018 by Data Blueprint Slide # What do we teach knowledge workers about data? !40Copyright 2018 by Data Blueprint Slide # What percentage of the deal with it daily?
- 21. Tacoma Narrows Bridge/Gallopin' Gertie • Slender, elegant and graceful • World's 3rd longest suspension span • Opened on July 1st, collapsed in a windstorm on November 7, 1940 • "The most dramatic failure in bridge engineering history" • Changed forever how engineers design suspension bridges leading to safer spans today. !41Copyright 2018 by Data Blueprint Slide # !42Copyright 2018 by Data Blueprint Slide # Similarly data failures cost organizations minimally 20-40% of their IT budget
- 22. Data Footprints • SQL Server – 47,000,000,000,000 bytes – Largest table 34 billion records 3.5 TBs • Informix – 1,800,000,000 queries/day – 65,000,000 tables / 517,000 databases • Teradata – 117 billion records – 23 TBs for one table • DB2 – 29,838,518,078 daily queries !43Copyright 2018 by Data Blueprint Slide # Running Query !44Copyright 2018 by Data Blueprint Slide #
- 23. Optimized Query !45Copyright 2018 by Data Blueprint Slide # Repeat 100s, thousands, millions of times ... !46Copyright 2018 by Data Blueprint Slide #
- 24. !47Copyright 2018 by Data Blueprint Slide # Data is a hidden IT Expense • Organizations spend between 20 - 40% of their IT budget evolving their data - including: – Data migration • Changing the location from one place to another – Data conversion • Changing data into another form, state, or product – Data improving • Inspecting and manipulating, or re-keying data to prepare it for subsequent use – Source: John Zachman !48Copyright 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.
- 25. What do we teach IT professionals about data? !49Copyright 2018 by Data Blueprint Slide # • 1 course – How to build a new database • What impressions do IT professionals get from this education? – Data is a technical skill that is needed when developing new databases !50Copyright 2018 by Data Blueprint Slide # If the only tool you know is a hammer you tend to see every problem as a nail (slightly reworded from Abraham Maslow)
- 26. Hiring Panels Are Often Challenged to Help !51Copyright 2018 by Data Blueprint Slide # • Dedicated solely to data asset leveraging • Unconstrained by an IT project mindset • Reporting to the business • 90 Percent of Large Global Organizations Will Have Appointed Chief Data Officers By 2019 (Gartner website accessed January 26, 2016 http://www.gartner.com/newsroom/id/3190117?) Top Operations Job Top Data Job !52Copyright 2018 by Data Blueprint Slide # Top Job Top Finance Job Top IT Job Top Marketing Job Data Governance Organization Top Data Job Enterprise Data Executive Chief Data Officer
- 27. The Enterprise Data Executive Takes One for the Team !53Copyright 2018 by Data Blueprint Slide # Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges !54Copyright 2017 by Data Blueprint Slide # Exorcising the Seven Deadly Data Sins g Data- ng Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ailing to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7t Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 acking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ately tions Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7
- 28. theDataDoctrine.com We are uncovering better ways of developing IT systems by doing it and helping others do it. Through this work we have come to value: Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !55Copyright 2018 by Data Blueprint Slide # That is, while there is value in the items on the right, we value the items on the left more. Mismatched railroad tracks non aligned Copyright 2017 by Data Blueprint Slide # !56 Data programmes preceding software development
- 29. Data programmes preceding software development !57Copyright 2018 by Data Blueprint Slide # Common Organizational Data (and corresponding data needs requirements) New Organizational Capabilities Systems Development Activities Create Evolve Future State (Version +1) Data evolution is separate from, external to, and precedes system development life cycle activities! Data management and software development must be separated and sequenced theDataDoctrine.com We are uncovering better ways of developing IT systems by doing it and helping others do it. Through this work we have come to value: Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !58Copyright 2018 by Data Blueprint Slide # That is, while there is value in the items on the right, we value the items on the left more.
- 30. Stable data structures preceding stable code !59Copyright 2018 by Data Blueprint Slide # Person Job Class Position BR1) One EMPLOYEE can be associated with one PERSON BR2) One EMPLOYEE can be associated with one POSITION Manual Job Sharing Manual Moon Lighting Employee Stable data structures preceding stable code !60Copyright 2018 by Data Blueprint Slide # Person Job Class Employee Position BR1) Zero, one, or more EMPLOYEES can be associated with one PERSON BR2) Zero, one, or more EMPLOYEES can be associated with one POSITION Job Sharing Moon Lighting
- 31. Stable data structures preceding stable code !61Copyright 2018 by Data Blueprint Slide # Data structures must be specified prior software development/acquisition (Requires 2 structural loops more than the more flexible data structure) More flexible data structure Less flexible data structure theDataDoctrine.com We are uncovering better ways of developing IT systems by doing it and helping others do it. Through this work we have come to value: Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !62Copyright 2018 by Data Blueprint Slide # That is, while there is value in the items on the right, we value the items on the left more.
- 32. Results Increasing utility of organizational data Individual IT Project Requirements Design Implement Requests Results Individual IT Project Requirements Design Implement Requests Results Individual IT Project Requirements Design Implement Requests Organized, shared data Organized, shared data Organized, shared data Shared Data preceding completed software !63Copyright 2018 by Data Blueprint Slide # • Over time the: – Number of requests increase – Utility of the results increase – Data's contribution increases – and is recognized! Shared data structures cannot exist without programmatic development and evaluation theDataDoctrine.com We are uncovering better ways of developing IT systems by doing it and helping others do it. Through this work we have come to value: Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !64Copyright 2018 by Data Blueprint Slide # That is, while there is value in the items on the right, we value the items on the left more.
- 33. Program F Program E Program H Program I domain 2Application domain 3 Data reuse preceding reusable code • Reusable software has been valued more than reusable data • Who makes decisions about the range and scope of common data usage? • Change a program – 9 max changes • Change data – Worst case – (N * (N - 1)) / 2 – (9 * 8)/2 = 36 !65Copyright 2018 by Data Blueprint Slide # Program D Program G Application theDataDoctrine.com We are uncovering better ways of developing IT systems by doing it and helping others do it. Through this work we have come to value: Data programmes preceding software development Stable data structures preceding stable code Shared data preceding completed software Data reuse preceding reusable code !66Copyright 2018 by Data Blueprint Slide # That is, while there is value in the items on the right, we value the items on the left more.
- 34. Introducing The Data Doctrine Copyright 2018 by Data Blueprint Slide # !67 http://www.thedatadoctrine.com Not Understanding Data-Centric Thinking Lacking Qualified Data Leadership Not implementing a Robust, Programmatic Means of Developing Shared Data Not Aligning The Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Failing To Address Cultural And Change Management Challenges Exorcising the Seven Deadly Data Sins !68Copyright 2018 by Data Blueprint Slide # g Data- ng Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ailing to Adequately anage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7t Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 acking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects ately tions Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 2 3 4 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7 Not Understanding Data- Centric Thinking Lacking Qualified Data Leadership Failing to Implement a Programmatic Way to Share Data Not Aligning the Data Program with IT Projects Failing to Adequately Manage Expectations Not Sequencing Data Strategy Implementation Not Addressing Cultural and Change Management Challenges 1 2 3 4 5 6 7
- 35. IT Business Data Perceived State of Data !69Copyright 2018 by Data Blueprint Slide # Data Desired To Be State of Data !70Copyright 2018 by Data Blueprint Slide # IT Business
- 36. The Real State of Data !71Copyright 2018 by Data Blueprint Slide # Data IT Business It’s your turn! Use the chat feature or Twitter (#dataed) to submit your questions now! Questions? + = !72Copyright 2018 by Data Blueprint Slide #
- 37. Upcoming Events January Webinar: Data Strategy-Best Practices January 8, 2019 @ 2:00 PM ET February Webinar: Data Architecture versus Data Modeling February 12, 2019 @ 2:00 PM ET Enterprise Data World How I Learned to Stop Worrying & Love My Data Warehouse Sunday, 3/17/2019 @ 1:30 PM ET Data Management Brain Drain Thursday, 3/21/2019 @ 8:30 AM ET Sign up for webinars at: www.datablueprint.com/webinar-schedule or www.dataversity.net !73Copyright 2018 by Data Blueprint Slide # Brought to you by: 10124 W. Broad Street, Suite C Glen Allen, Virginia 23060 804.521.4056 Copyright 2018 by Data Blueprint Slide # !74