RWDG Slides: Using Agile to Justify Data Governance

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Copyright © 2016 Robert S. Seiner – KIK Consulting & Educational Services / TDAN.com
Non-Invasive Data Governance™ is a trademark of Robert S. Seiner & KIK Consulting
#RWDG @RSeiner
Real World Data Governance
Using Agile to Justify Data Governance
Monthly Webinar Series Hosted by Dataversity
Robert S. Seiner – KIK Consulting / TDAN.com
December 15, 2016 – 2:00 p.m. EST

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• Real-World Data Governance – Monthly Webinar Series
– January 19, 2017 – Three Approaches to Data Stewardship
– February 16, 2017 – The New Non-Invasive Data Governance Framework
– March 16, 2017 – Apply Data Governance to Agile Efforts
– Monthly on the Third Thursday at 2 pm EST
– Register On-Line at DATAVERSITY.net or TDAN.com or KIKConsulting.com
Real-World Data Governance
2017 Upcoming Webinars

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• Non-Invasive Data Governance:
The Path of Least Resistance and Greatest Success
ISBN 9781935504856 / Technics Publishing / Amazon.com
• KIKConsulting.com
Home of Non-Invasive Data Governance™
• DATAVERSITY Events
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Virtual Conference – January 25, 2017
Kick Off Session – Selecting the Right Approach to Data Governance
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Atlanta, Georgia – April 2, 2017
Tutorial – Comparing Approaches to Data Governance
In the News

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• The Data Administration Newsletter (TDAN.com)
– Bi-Monthly Publication
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In the News

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• The Agile development methodology is here to stay.
• Data Governance is not going away any time soon.
• These two discipline share some common ground but often compete when it
comes to the “right” thing to do when it comes to managing the data.
• The disciplines need to learn to play well together.
• The old mantra of “do unto others” applies here in a big way.
Abstract

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• This webinar will cover:
– The audience of both Agile and Data Governance
– The governance aspects of Agile
– Why Data Governance Practitioners Should Embrace Agile
– Agile considerations for Data Governance
– How to Use Agile to Justify Data Governance
Abstract

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• Data Governance
– Data Governance is the Execution and Enforcement of Authority
Over the Management of Data and Data-Related Resources.
• Data Stewardship
– Data Stewardship is the Formalization of Accountability
Over the Management of Data and Data-Related Resources.
Data Governance Definition

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#RWDG @RSeiner
• Non-Invasive Data Governance™
– The practice of:
• applying formal accountability & behavior
• through non-invasive roles & responsibilities
• to existing and / or new processes
• to assure that the definition, production & usage of data
• assures regulatory compliance, security, privacy, protection & quality.
– Non-Invasive describes how governance is applied to assure
non-threatening management of valuable data assets.
– The goal is to be
• Transparent
• Supportive
• Collaborative.
Data Governance Definition

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• The Agile Manifesto – Development Methodology Leading to Good Design
– People / Interaction
– Speed / Effectiveness
– Software / Working Products
– Requirements / Collaboration
– Response / Evolvement
Agile Definition

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• The Waterfall Approach
– A linear and sequential approach to software development, each waterfall stage is
assigned to a separate team to ensure greater project and deadline control,
important for on-time project delivery. A linear approach means a stage by stage
approach for product building, e.g.
1. Analyze and Prioritize Business Requirements / Needs
2. Design Business Requirements Translated into IT Solution
3. Processes Defined, Layouts Built, Code Implementation
4. Evolves into Tested Solution for Implementation
5. Testing for Evaluation by End-User
6. Evaluation and Maintenance
Agile vs. Waterfall

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• What Does Senior Leadership Want from Data Governance?
– Understood Data – Govern Data Definition
– Quality Data – Govern Data Production
– Protected Data – Govern Data Usage
The Audience of Both Agile and Data Governance

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• What Does Senior Leadership Want from Agile?
– Speedy Delivery
– Incremental Delivery
– High Quality Delivery
Mr. McFeely
of Mister Roger’s Fame
“Speedy
Delivery”

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• What Does Senior Leadership Think About Data Governance?
– The reason why they are implementing Data Governance:
• Data must be managed as an asset.
• The data must be protected.
• The data drives analytics and decision-making so it must be high quality.
• The auditors are telling them they must have formal governance.
• Other organizations are governing their data.

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• What Does Senior Leadership Think About Data Governance?
– The reasons why they are not implementing Data Governance:
• They do not understand all of the approaches that are available.
• They have the perception that …
– DG is very complex based on the organization.
– DG moves very slowly.
– DG can be quite expensive.
– DG requires a lot of resources.
– DG will change the culture.
– DG is not a project.

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• What Does Senior Leadership Think About Agile?
– The reason why they are implementing Agile:
• Large projects take too long and they cost way too much.
• Large projects must be managed to be delivered quickly and accurately.
• The project must be delivered early and continuously.
• The project communications must be face-to-face and constant.
• High Quality and Timely Delivery are Critical.

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• What Does Senior Leadership Think About Agile?
– The reason why they are not implementing Agile:
• The fact is that they are attempting to deliver projects using Agile.
• Sold on the virtues of Agile. Not sold on the virtues of Data Governance.
• And … Agile is only being used for large and complex projects.

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• What does Senior Leadership know about relating the two?
– Very Little
• How much effort has been made to relate the two?
– Very Little
• What effort has been made to get the Program and Projects aligned?
– Very Little
• How well are Data Governance Programs acting Agile?
– Very Little

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• Agile is a Development Methodology
– Who does what, when and how when it comes to the development effort.
– Very structured.
– Very disciplined.
– Very timely.
The Governance Aspects of Agile

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• Governance is Execution and Enforcement of Authority.
– Who does what, when and how when it comes to the data discipline.
– Very structured.
– Very disciplined.
– Very timely.

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• Governance Bill of “Rights”.
– Getting the “right” people
– Involved at the “right” time
– In the “right” process
– Using the “right” data
– To do the “right” thing
– To get the “right” result
… at least most of the time.

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• If Governance is what we say it is …
--- Governance is theoretically built into …
– Develop Functionality
– Integrate and Test
– Demo Release
– Client Feedback
– Make Changes
– System Testing
– Next Iteration

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• Development Bill of “Rights”
– Getting the “right” development people
– Involved at the “right” development time
– In the “right” development process
– Using the “right” development data
– To do the “right” development thing
– To get the “right” development result
… at least most of the time.

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• The focus of Agile is …
– People / Interaction
Why Data Governance Practitioners Should Embrace Agile

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– People / Interaction – Data Governance Practitioners Want This!

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– Speed / Effectiveness – Data Governance Practitioners Want This!

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– Software / Working Products – Data Governance Practitioners Want This!

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– Requirements / Collaboration – Data Governance Practitioners Want This!

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– Requirements / Collaboration – Data Governance Practitioners Want This!
– Response / Evolvement – Data Governance Practitioners Want This!

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• The focus of Data Governance is:
– Manage Data as an Asset
– Formalize Accountability
– Follow the Rules
– Govern Consistently
Agile Considerations for Data Governance

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• How do you begin to bring together approaches that are different?
• Begin by looking at what they have in common.
• Strengthen that.
• Build on that.
• Rinse & Repeat.

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• Agile Principles:
– Complete Feature Before Moving
– Testing – Early and Often
– Active User Participation
– Timing – Quickly, Incrementally
– Requirements at a High Level
– Manage Technical Debt
– Lightweight & Visual
– Requirements Evolve / Timescale Fixed
– Software as Progress Measure
– Develop Small, Incremental Releases
– Good Design, Technical Excellence
– Simplicity is Essential
– Maximizing the Amount of Work

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#RWDG @RSeiner
• Agile Principles (where Data Governance can justifiably have an impact):
– Complete Feature Before Moving
– Testing – Early and Often
– Active User Participation
– Timing – Quickly, Incrementally
– Requirements at a High Level
– Manage Technical Debt
– Lightweight & Visual
– Requirements Evolve / Timescale Fixed
– Software as Progress Measure
– Develop Small, Incremental Releases
– Good Design, Technical Excellence
– Simplicity is Essential
– Maximizing the Amount of Work

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#RWDG @RSeiner
• Agile Principles to be Targeted to Justify Governance
1. Active User Participation
2. Requirements at a High Level
3. Technical Debt to be Paid
4. Requirements Evolve / Timescale Fixed
How to Use Agile to Justify Data Governance

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1. Active User Participation
‒ Data Governance Speaks this Same Language
‒ Essence of being non-invasive is to:
‒ Users follow a governed process
‒ Formalize user accountability
‒ Users escalate issues to formalize decision making

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2. Requirements at a High Level
– This is where there is the greatest potential to justify Data Governance for Agile.
– DG practitioners pride themselves on capturing required metadata.
– Agile practitioners pride themselves on being structured and with speed.
• WoW: Both practitioners must agree on requirements level.

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• Requirements at a High Level
– This is where there is the greatest potential to justify Data Governance for Agile.
– Can Data Governance practitioners limit requirements?
• Vocabulary Metadata – Business Terminology
• Business Metadata – Data Standards & Dictionaries
• Technical Metadata – Database, File and Model
• Lineage Metadata – Data Movement, ETL
• Linkage Metadata – Standards, Policies, Procedures, Between Levels

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– Logical & Physical Modeling of Data
• Models require questions … about cardinality, retention, growth, etc.
• Models promote a common understanding
• Models require the participation of a Data Analyst / Data Architect.
• WoW: Without detailed requirements – projects create their own
understanding which in turn can result in ambiguity, replication, etc.

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– Questions for Data People:
• Too much documentation?
• Not enough documentation?
• Do we use it all?
• How do we use it?
• Can we work out an agreement with the Agile people?
• Isn’t making no decision on requirement a decision itself?
• WoW: Consider the value you get from the metadata you require.

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• Requirements at a High Level – Summary
• Limit Data Demand for Requirements
• Achieve an Agreed Upon Level of Requirements
• Provide Tools to Effectively Capture Essential Requirements
• Provide Resource(s) Focused on Data Governance / Agile Alignment
• WoW: Incrementally Apply Agreed Level of Data Requirements to Agile

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3. Technical Debt to be Paid
– Requirements that will eventually need to be addressed / Parking Lot List
– Also referred to as design debt or code debt
– Metaphor referring to the eventual consequences of poor system design
The debt can be thought of as work that needs to be done before a particular job can
be considered complete or proper. If the debt is not repaid, then it will keep on
accumulating interest, making it hard to implement changes later on. Wikipedia
– Debt can be accumulated in each step of the methodology – Agile or Waterfall
• WoW: This is the biggest reason why Data People are skeptical about Agile.

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• Technical Debt to be Paid
– Reasons why Technical Debt accumulates
• Business pressures - where the business considers getting something released
sooner before all of the necessary changes are complete, builds up technical debt
comprising those uncompleted changes.
• Lack of process or understanding - where businesses are blind to the concept of
technical debt, and make decisions without considering the implications.
• Lack of test suite - which encourages quick and risky Band-Aids to fix bugs.
• Lack of documentation - where code is created without necessary supporting
documentation. That work to create the supporting documentation represents a
debt that must be paid.

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– Reasons why Technical Debt accumulates
• Lack of collaboration - where knowledge isn't shared around the organization and
business efficiency suffers, or junior developers are not properly mentored
• Parallel development at the same time on two or more branches - can cause the
buildup of technical debt because of the work that will eventually be required to
merge the changes into a single source base. The more changes that are done in
isolation, the more debt that is piled up.
• Delayed refactoring – As the requirements for a project evolve, it may become
clear that parts of the code have become unwieldy and must be refactored in
order to support future requirements.
• Lack of knowledge - When developer simply doesn't know how to write code.

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– Apply Governance So That Technical Debt Does Not Accumulates
• Formal Accountability for Managing Technical Debt
• Formal Escalation of Issues Associated with Technical Debt
• Formal Reporting of Technical Debt Status

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4. Requirements Evolve / Timescale Fixed
– This is the biggest challenge when justifying Data Governance for Agile.
– From both perspectives
• Evolving Requirements
• Fixed Period of Time.
– Shooting at a moving target.

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• Requirements Evolve / Timescale Fixed
– Requirements evolve means a gradual process in which the requirement (including
data requirements) change into a different usually more complex or better form.
– Let’s break this down:
• Gradual process – not all at once – requires constant governance
• Changes into something different – requires constant governance
• Usually more complex or better form – requires constant governance

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• Requirements Evolve / Timescale Fixed
– Management of Requirements requires Governance of Requirements.
– Provide 2 of 3 – Time, Resources, Effort
– Agile is a form of Project Governance – Just not Data Governance.
• WoW: Bottom line – Governance is the Execution & Enforcement of Authority

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• Requirements Evolve / Timescale Fixed – Summary
– The challenge is to gather the:
• Most valuable requirements / documentation – and use them effectively
• Most effective requirements – and make them available
• Most available requirements – and make certain essentials are covered
• Most essential requirements – in a short period of time.

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#RWDG @RSeiner
• This webinar covered:
– The audience of both Agile and Data Governance
– The governance aspects of Agile
– Why Data Governance Practitioners Should Embrace Agile
– Agile considerations for Data Governance
– How to Use Agile to Justify Data Governance
Summary

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#RWDG @RSeiner
• Real-World Data Governance – Monthly Webinar Series
– January 19, 2017 – Three Approaches to Data Stewardship
– February 16, 2017 – The New Non-Invasive Data Governance Framework
– March 16, 2017 – Apply Data Governance to Agile Efforts
• Questions and Answers
Conclusion

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#RWDG @RSeiner
• Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
Post Office Box 112571, Upper St. Clair, Pennsylvania 15241
412.220.9643, 412.220.9644 (Fax)
rseiner@kikconsulting.com
rseiner@tdan.com
@RSeiner #RWDG
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RWDG Slides: Using Agile to Justify Data Governance

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RWDG Slides: Using Agile to Justify Data Governance