Most of us learned data modeling via a waterfall-driven methodology lens. Yet Agile and other modern development methods have for the most part assumed that data governance is an anti-pattern to just getting things (software) done. Well look at questions such as: •Are Agile and Data Governance Enemies? •How can we get stuff done AND get systems delivered? •And what do we do about existing systems delivered without data governance attention? We'll also look at how data modeling fits in the answers to these questions.

1. Karen Lopez @datachick #HeartData
Heart of Data Modeling
Data Governance in an Agile SCRUM Lean MVP World

2. @datachick
#heartdata
Please
share/tweet

3. Karen López
Karen has 20+ years of data and information architecture
experience on large, multi-project programs.
She is a frequent speaker on data modeling, data-driven
methodologies and pattern data models.
She wants you to love your data.

4. Tamera Clark, T & K Creative Solutions Group
Tamera Clark has been involved in the IT industry for greater
than ten years, with experiences ranging from systems
analysis/engineering to SQL Server and SSRS
administration/development.
She is an active member of the SQL Server community,
participating in the Women in Technology Virtual Chapter,
Co-leading the Nashville BI Chapter, assisting the Nashville
PASS Chapter and serving as a Regional Mentor.
Tamera is also the event chair of SQLSaturday Nashville.
She loves data, too.Twitter - @tameraclark
Linkedin - /tameraclark
Email – tamera.clark@gmail.com
Website - Tameraclark.com

5. You are the panelist
...so let’s get to know you….

6. POLL: Who Are
You?

7. DG at your company?
Aug 2014

8. Agile/SCRUM/Lean/MVP
at your company?
Aug 2014

9. Be engaging….
Use Q&A
for formal
questions
Use chat
to discuss
with each
other

10. Data Governance
An Overview

11. Data Governance: Bob Seiner
Data governance is the formal
execution and enforcement of
authority over the management of
data and data related assets.

12. Data Governance: Gwen Thomas, DGI
Data Governance is 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.
http://www.datagovernance.com/wp-content/uploads/2014/11/dgi_framework.pdf

13. Data Governance: DGPO
A discipline that provides
clear-cut policies; procedures;
standards; roles;
responsibilities; and
accountabilities to ensure that
data is well-managed as an
enterprise resource.
http://dgpo.org/uploads/2015_DGPO_Overview.pdf

14. Ihavenoideawhywehavetogivethisstuffanother
name. Governanceissortofthedefinitionof
“professionalpractice”.
Wedon’thaveEngineeringorArchitectureGovernance.
It’sjustbakedintothoseprofessions.
It’s good we
have Data
Governance
now.

15. Why Data Governance is Important
Massively
complex
architectures
•Tools
•Vendor Applications
•The CLOUD
Complex Data
•Feeds, external data
•Redundant internal
data
•Conflicting data
•Poor data quality
•Missing data
•Unused data
Methods
•Infrastructure
•DevOps
•Development
•Data
•Financial

16. Many facets of data governance..
Data Quality Data
Stewardship
Compliance Infrastructure
and architecture
Business Standards Monitoring and
Correction

17. Where Data Governance Helps
Saving money
Satisfying
customers
Retaining
customers
ROI
Keeping CEO/CIO
out of jail
Innovating
Data & Business
analytics Reducing costs
Responsiveness

18. Establishing Data
Governance
How do we do this?

19. Where are you now?
Development
processes
Staffing
Tools Models
Business and
Customer pain
points
IT pain points
Regulatory
findings/penalties Audit findings

20. Key Data Governance Deliverables
Strategy
Policies
Tools/Processes
Roles & responsibilities
Data Quality rules & methods
Data Modeling, including extended metadata
Monitoring, reporting and analysis of results

21. Establishing a Data Governance Program
http://www.datagovernance.com/wp-content/uploads/2014/11/dgi_framework.pdf

22. Agile Methods
What are they? What else are they?
Plus at little bit of SCRUM

23. IloveworkingonAgile
projects

24. It’sFRAGILE
projectsIhate.

25. Principles Behind the Agile Manifesto
1. Our highest priority is to satisfy the
customer through early and
continuous delivery of valuable
software.
2. Welcome changing requirements,
even late in development. Agile
processes harness change for the
customer's competitive advantage.
3. Deliver working software frequently,
from a couple of weeks to a couple of
months, with preference to the
shorter timescale.
4. Business people and developers must
work together daily throughout the
project.
5. Build projects around motivated
individuals. Give them the
environment and support they
need, and trust them to get the job
done.
6. The most efficient and effective
method of conveying information to
and within a development team is
face-to-face conversation.

26. Principles Behind the Agile Manifesto
7. Working software is the primary
measure of progress.
8. Agile processes promote sustainable
development. The sponsors,
developers, and users should be
able to maintain a constant pace
indefinitely.
9. Continuous attention to technical
excellence and good design enhances
agility.
10. Simplicity--the art of maximizing the
amount of work not done--is
essential.
11. The best architectures,
requirements, and designs emerge
from self-organizing teams.
12. At regular intervals, the team
reflects on how to become more
effective, then tunes and adjusts its
behavior accordingly.

27. Manifesto for Agile Software Development

28. Agile/Scrum development project
28

29. Typical Sprint
Sprint Planning
Backlog Stories
START
READING DEVELOPMENT DELIVER
END
Wherethehellisour
database?

30. Managing Data Wrong - One
Expecting data modeling & database design
tobe completed in an instantat the
beginning of a sprint

31. Managing Data – Fix it
Sprint Planning
Backlog Stories
START
READING DEVELOPMENT DELIVER
END

32. Managing Data – Fix it Better
Sprint Planning
Backlog Stories
SART
READING DEVELOPMENT
START
READING DEVELOPMENT DELIVER
END
Sprint Planning
START
READING

33. https://www.scrumalliance.org/why-scrum

34. Scrum Values
Focus
• Because we focus on only a few things at a
time, we work well together and produce
excellent work. We deliver valuable items
sooner.
Courage
• Because we work as a team, we feel
supported and have more resources at our
disposal. This gives us the courage to
undertake greater challenges.
Openness
• As we work together, we express how we're
doing, what's in our way, and our concerns
so they can be addressed.
Commitment
• Because we have great control over our own
destiny, we are more committed to success.
Respect
• As we work together, sharing successes and
failures, we come to respect each other and
to help each other become worthy of
respect.
- https://www.scrumalliance.org/why-scrum/core-scrum-values-roles#sthash.RgaO3uIK.dpuf
All work performed in Scrum needs a set of values as the foundation for the team's processes and
interactions. And by embracing these five values, the team makes them even more instrumental to its
health and success.

35. Lean Software Methods
What are they? What else are they?

36. Lean Software Methods
Eliminate waste
Amplify learning
Decide as late as possible
Deliver as fast as possible
Empower the team
Build integrity in
See the whole

37. What is waste? Partially done work
Extra processes
Extra features
Task switching
Waiting
Motion
Defects
Management activities

38. Lean Processes
What are they? What else are they?

39. Lean Software Methods
Eliminate waste
Amplify learning
Decide as late as possible
Deliver as fast as possible
Empower the team
Build integrity in
See the whole

40. What is waste? Partially done work
Extra processes
Extra features
Task switching
Waiting
Motion
Defects
Management activities

41. Minimum Viable Product
What is it?

42. Minimum Viable Product
The most pared down version of a product that can still be released. An MVP has
three key characteristics:
• It has enough value that people are willing to use it or buy it initially
• It demonstrates enough future benefit to retain early adopters
• It provides a feedback loop to guide future development
The catch to this development technique is that it assumes that early adopters can
see the vision or promise the final product and provide the valuable feedback
needed to guide developers forward.
This suggests that technically orientated products used by technical users may be
most appropriate for this type of development technique.
https://www.techopedia.com/definition/27809/minimum-viable-product-mvp

43. Focus of MVP
Early
Feedback
Feedback
And…
Feedback

44. Where Data Governance and
Development Methods
Intersect
…Integrate…Collaborate…build a wall…find peace…

45. Data Governance and Agile/SCRUM
ProgramPlanningandDesign Governing MakingHappier

46. Where DG and Agile Intersect
Sprint planning MUST take
into account data governance
But no Agile pro is going to
like those words
So we need the right context
and the right vocabulary

47. Where DG and Agile Intersect
“Working software is the primary measure of
progress.”
“Continuous attention to technical
excellence and good design enhances
agility.”
At regular intervals, the team reflects on
how to become more effective, then tunes
and adjusts its behavior accordingly.

48. Youwillfind
obstaclesalong
theway….

49. Agile “Extensions”…
Everyone is a generalist
Agile Blocking
Excluded titles
•Administrators
•Architects
•Managers
Test Driven Development
No BMUF/BDUF
Paired programming
Did I say Blocking?

50. Agile Blocking & Data Modeling
The blockers effectively implement a “process façade” around your
team that makes it appear to the rest of the organization that your team
is following their existing procedures. This satisfies the bureaucrats, yet
prevents them from meddling with the people that are doing the real
work. Although it sounds like a wasted overhead, and it is because it
would be far more effective to divert both the blockers and bureaucrats
to efforts that produce something of value, the advantage is that it
enables the rest of the team to get the job done. The role of blocker is
often taken on by your team’s project manager or coach, although in
the past I have let this be a revolving role on the project so as to spread
out the pain of dealing with the paper pushers.
http://www.agiledata.org/essays/adopting.html#sthash.gvFL7Hd4.dpuf

51. Data Governance and Lean
Bringing models to the table is Lean
Bringing metadata to the project is Lean
Forcing Lean projects to implement the
entire data model may not be Lean
The goal of Lean fast and efficient, much
like agile.

52. Data Governance and Lean
The Data Governance program Deployment
could follow a Lean Process itself
Finding the right metrics are key
Lean isn’t just an excuse for sloppiness or
lack of compliance

53. Data Governance and MVP
Depends upon what minimal ends up
being
Some MVP projects have only a handful of
data items
It might be best to have a consulting role
on the project for compliance monitoring
MVP is not typically an enterprise method.

54. 10 Tips for Data Modelers
1. Learn about these methods – don’t avoid them
2. Get Agile/Scrum/Lean/MVP training. Get certified
even
3. Learn the lingo.
4. Use the lingo
5. Be able to describe data modeling and data
governance to the context of these methods

55. 10 Tips for Data Modelers
6. Get data models and DDL tasks moved sprints
ahead
7. Bring data models (and other models) to the team.
8. Don’t back off from Agile/SCRUM/Lean teams,
even if they are hostile.
9. Don’t be a roadbock. Get ahead of the sprints

56. 10 Tips for Data Modelers
10. Practice Agile techniques on your own deliverables
• Policies, procedures
• Test driven development
• Backlogging
• Parkinglotting
• Continuous delivery
• Lean
• MVP

57. http://edw2016.dataversity.net
http://nosql2016.dataversity.net
Half Day: 7 Databases in 170 Minutes
SIG: ER/Studio and Data Modeling Special Interest Group
Panel: Data Modeling & NoSQL Moderator
Session: The Tricky Part of Doing Tricky Things in your
Data Model
…and likely some other fun things!

58. ThankYou! www.datamodel.com
Karen@InfoAdvisors.com