This is a presentation I gave May 19th, 2015 at the SAS Insight session 'A Data Driven Reality' which announced the new SAS magazine dedicated to data management. It featured an interview with me about the Data Quadrant Model

1. © Ronald D. Damhof – May 19, 2015 – SAS Insight
It’s all about the data: A Managerial Perspective
By Ronald Damhof
Email: ronald.damhof@prudenza.nl
Linkedin:
nl.linkedin.com/in/ronalddam
hof/
Twitter: RonaldDamhof
Blog: prudenza.typepad.com

2. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
I am an opinionated kind a guy….

3. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
Who am I - My Data Manifesto
The X commandments of data management
I. Thou shall always respect
& consider the context.
Context is leading
Cynafin: D.Snowden (cognitive-edge)

4. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
Who am I - My Data Manifesto
The X commandments of data management
II. Thou shall love your
(meta)data. Data is the
ultimate proprietary
asset:
- Manage it
- Govern it
- Utilise it
But do it ethically
“Most companies manage their
parking lot better than their data” —
Gartner, Frank Buytendijk (paraphrased)

5. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
Who am I - My Data Manifesto
The X commandments of data management
III.Thou shall stop centering
apps over data: data first

6. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
Who am I - My Data Manifesto
The X commandments of data management
IV.Thou shall strive for
accurate, relevant, timely,
reliable and accessible data:
It is all about the quality of
the product
Deming’s point 3 of 14:
”Cease dependence on inspection to
achieve quality. Eliminate the need for
massive inspection by building quality
into the product in the first place."

7. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
Who am I - My Data Manifesto
The X commandments of data management
V. Thou shall abstract

8. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
Who am I - My Data Manifesto
The X commandments of data management
VI.Thou shall make a
‘fundamentalistic’ separation
between facts & context

9. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
VI. Thou shall not forsake ‘TIME’

10. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
Who am I - My Data Manifesto
The X commandments of data management
VIII.Thou shall uphold, improve
and teach the science and
practice of Information- &
data modeling

11. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
Who am I - My Data Manifesto
The X commandments of data management
IX.Thou shall Specify,
Standardise, Automate &
Productise

12. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
Who am I - My Data Manifesto
The X commandments of data management
X. Thou can not buy your
way out of the data
misery you are in

13. R.D.Damhof – Prudenza BV - Copyright - 22 mei 2014© Ronald D. Damhof – May 19, 2015 – SAS Insight
‘XI’
There is a new saviour in town. Its name is Hadoop
and it calls to us from its mountain:
‘we got a lake and thou shall throw all your data in
it. The water will be clean so you can drink it, the
water will flow so it will irrigate your lands, grow
your stock, feed your kids and of course bring you
world peace…..’
Who am I - My Data Manifesto
The X commandments of data management

14. © Ronald D. Damhof – May 19, 2015 – SAS Insight
A Framework for a Managerial
Perspective on Data

15. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Logistics & Manufacturing

16. © Ronald D. Damhof – May 19, 2015 – SAS Insight

17. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Push/Supply/Source driven Pull/Demand/Product driven
 Mass deployment
 Control > Agility
 Validation of “ingredients”
 Repeatable & predictable proces
 Standardized processes
 High level of automation
 Relatively high IT/Data expertise
 Piece deployment
 Agility > Control
 Plausibility
 User-friendliness
 Relatively low IT expertise
 Domain expertise essential
All facts, fully temporal Truth, Interpretation, Context
Business Rules Downstream
The Data Push Pull Point

18. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Systematic
Opportunistic
 User & developer are separated
 Defensive Governance
 Focus on non-functionals
 Centralised
 Proper system development
 User = developer
 Offensive governance
 Decentralised
 “System development” in production
The Development Style

19. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Development
Style
Systematic
Opportunistic
I II
III IV
Research,
Innovation &
Design
“Shadow IT,
Incubation,
Ad-hoc,
Once off”
Push/Supply/Source driven Pull/Demand/Product driven
Data
Push/Pull
Point
ContextFacts
A Data Deployment Quadrant

20. © Ronald D. Damhof – May 19, 2015 – SAS Insight
7 Applications of the Quadrant
How 2 produce
How 2 automate
How 2 organize
How 2 govern
How about people
How about technology
How 2 model

21. © Ronald D. Damhof – May 19, 2015 – SAS Insight
(1) How we produce

22. © Ronald D. Damhof – May 19, 2015 – SAS Insight
How we produce, process variants

23. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Production-line: Data orientation
Data Products Information
Products
Access to data
Analytical tools
Processing Power
Production-line: Forms orientation
Eg. XBRL/JSON
How we produce, production lines
Production-line: Poly Structured

24. © Ronald D. Damhof – May 19, 2015 – SAS Insight
(2) How we automate

25. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Rephrased - somewhat more nerdy:
• Model-driven, metadata driven
Or
• Declarative instead of Imperative
Rephrased - somewhat more popular:
“In Data, the developer is the data modeller”
(2) How we automate

26. © Ronald D. Damhof – May 19, 2015 – SAS Insight
(3) How we organize

27. © Ronald D. Damhof – May 19, 2015 – SAS Insight
2nd law of Thermodynamics
Entropy of an isolated system
will always tend to stay the
same or increase – in other
words, the energy in the
universe is gradually moving
towards disorder.
In loose terms; a measure of the
amount of disorder within a
system

28. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Entropy is ever increasing
Simple/
Order
Chaos
Complex/
Un-order
Complicated/
”Order”

29. © Ronald D. Damhof – May 19, 2015 – SAS Insight
To centralize or to decentralize

30. © Ronald D. Damhof – May 19, 2015 – SAS Insight
(4) How we govern

31. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Remember the entropy?
Simple/
Order
Chaos
Complex/
Un-order
Complicated/
“Order”

32. © Ronald D. Damhof – May 19, 2015 – SAS Insight
How we govern, products

33. © Ronald D. Damhof – May 19, 2015 – SAS Insight
I II
III IV
Deliverant is
Accountable
Demandee is
Accountable
Data scientist/Analyst/Researcher accountable
How we govern, accountability
Never, never, never ‘ownership’
In- en outbound
Data Delivery
Agreements
With great power comes great responsibility

34. © Ronald D. Damhof – May 19, 2015 – SAS Insight
(5) How do people excel
Data
Engineer
Application
Developer /
BI professional
Data
Scientist
Infrastructure
Specialist

35. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Storage: (R)DBMS
Processing: Automation Software
Data Quality: Validation, Profiling
Development: Data Modeling
Accessibility: Data Virtualization
Storage: Pattern based
Processing: Automation/limited ETL
Data Quality: DQ rules/dashboards
User tooling: Reporting, dashboards,
Data Visualization
Storage: Analytical
Processing: Preptools for Data Analyst
User tooling: Advanced Analytics,
Data Visualization
(6) How about Technology
Infrastructure-as-service
Datalakes
Fileservers
…

36. © Ronald D. Damhof – May 19, 2015 – SAS Insight
(7) Business-,Information- or
Data Modeling is key
Conceptual
Logical
e.g
Fact based,
Graph,
Key-value
Models that fit
the need
At least the Logical Model
drives the technical data
architecture, design and
implementation
Ontology
Facts
Relational
Natural Language
ORM / FCO-IM

37. © Ronald D. Damhof – May 19, 2015 – SAS Insight
 Please (!) have a holistic view &
strategy of data – it’s a supply
chain.
 Data isn't ‘One size fits all’
 If you have x Euro to invest, what
quadrant would you invest in?
 If you want to be data-driven,
how would you organize
yourselves? What kind of competencies and skills would you need?
 Think before you buy, think hard. Do not follow blindly the
latest tech fad, framework x, method y, best practice z.
 Fight the entropy! It isn't free….

38. © Ronald D. Damhof – May 19, 2015 – SAS Insight
Thank
you