Confused about how to ensure data management activities get accomplished as you organizations transitions from a traditional software development and management methodologies to agile ones? This presentation explains the key differences in integration points between traditional and agile processes, provides tactical approaches to inserting data governance work into the agile flow. It provides an overview of agile organizational structures, enabling you to ensure they account for data governance roles performed in your organization. 3 Key Takeaways 1. An understanding of how traditional checkpoints or gateways leveraged by the data governance community map to new agile processes and workflows 2. How and when to engage agile teams 3. How to ensure your data governance staff and activities are accounted for in agile organizations

1. Agile Data Management
DAMA Philadelphia
March 15, 2018

2. About the Author
• Executive Data Officer – TD Bank
• Senior Director (Digital Wallet Program) – AMEX
• Agile Coach / SCRUM Master – (Capital One)
• Author
Guerrilla Agile – Implementing Agile Practices in the Corporate World

3. What We’ll Discuss
• Agile: What is it about and what does it look like
• Traditional software development and management approach with typical data steward
points of engagement
• Proposed agile software development and management approach with suggested data
steward points of engagement
• Proposed approach to integrating data governance roles into organizations staffed on an
agile basis
• Walk through an example of performing Data Issue Management in an agile fashion
• Q&A / Discussion
• I’ll pause for questions after reviewing some of the more detailed slides

4. What You’ll Take Away
1. An understanding of how traditional checkpoints or gateways
leveraged by the data governance community map to new agile
processes and workflows
2. How and when to engage agile teams
3. How to ensure your data steward staff and activities are accounted
for in agile organizations
4. How you can use agile methods in your data management activities

5. What is Agile All About?
• Iterative Delivery
• Short cycle times
• Working software
• Full Contact Collaboration
• Business – IT daily interaction*
• Face-to-Face wherever possible
• Expect and Welcome Change
• Commitment Based
• Sustainable Yet Adaptive
Time to Market – Refactoring (Architecture / Standards)
Satisfied Customers
Daily “Stand Up Meeting”
Team Collocation
Everyone
Competitive Advantage
What and How (Not When / Who)
It Happens Anyway
Self Organized Teams
Servant Based Leadership
Consistent Pace
Reflect – Fine Tune and Adjust

6. What Does Agile Look Like? (SCRUM Flavor)

7. Traditional Software Development Engagement
Test
Build
Design
Requirements
Deploy
Data Requirements
Identify:
 Stakeholders
 Decision Rights
 Accountabilities
Defining Data Structures
Define Models
Data Storage Design
Update Bus Data Glossary
Populate Metadata
Writing Test Cases
Document Lineage Data Validation
User Acceptance Testing
Formal Sign-Offs
Data Validation
User Validation
Data Quality Profiling
Stewardship

8. Traditional Project Management Engagement

9. Agile Software Development Engagement
Product
Backlog
Sprint Planning
Sprint backlog
4 weeks
Daily
Stand-Up
meeting
Sprint
Potential
Shippable
product
Sprint Review Sprint
Retrospective
Goal: Identify and
prioritize product
features
Goal: Identify
which features
will be developed
In this sprint
Decompose work
into tasks
Team
Commitment
Goal: Completion
of tasks and
acceptance of
features.
Hold daily Scrum
(30 minutes)
Goal: Showcase to
stakeholders
working product
features
Goal: Honest
review of the
team’s
performance with
consensus on
how to improve
Release

10. Agile Software Development Engagement
Product
Backlog
Sprint Planning
Sprint backlog
4 weeks
Daily
Stand-Up
meeting
Sprint
Potential
Shippable
product
Sprint Review Sprint
Retrospective
Release
Data Related Efforts
 Business
 Regulatory
 Enterprise
Identify Data Related Work
 Governance
 Management
Perform Data Related Work
Define/Build data structures Write test cases
Define/Build data models Document lineage
Design/Build data store Data validation
Update Bus data glossary User validation
Present Working System / Features
 User Acceptance Testing
 Formal Signoffs
Production Related Work
 Data Validation
 User Validation
 Data Quality Profiling
 Stewardship

11. Agile Management Engagement
Sprint
Product
Increment
Sprint Review
Sprint
Retrospective
Product
Backlog
Review
Sprint
Planning
Considerations:
Data Governance and Management processes
must evolve to provide flexibility and adaptability
Accountability and commitment work BOTH ways:
 Agile teams must address data governance
and management related work items
 Data Stewards must be committed to team
goals and outcomes, and as such
accountable
Adapt data steward engagement to meet the agile
team needs as well as your own

12. Organizational Design

13. Kanban Board Example

14. Data Issue Management Using Kanban

15. My Challenge to You …
 Engage your executives and community in leading real change in adapting your data
governance and management processes to better aligning with agile methods
 If you are not adequately engaged by agile teams … show up!
 Backlog Reviews
 Sprint Planning
 Daily Stand-Ups
 Sprint Reviews
 Sprint Retrospectives
 Learn more about agile development and management methodologies
 Don’t be afraid to leverage agile methodologies in in evolving how your organizations
deliver data governance and management

16. Questions ? Discussions
Possible
Solutions
Points of
Contention
Shared
Experiences
Comments

17. Appendix A

18. Traditional Method of Capturing / Monitoring Work

19. Agile Method of Capturing / Monitoring Work

20. If You Need Help …