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
Website: www.prudenza.nl
R.D.Damhof – Oktober 2014 – Norske
I am an opinionated kind a guy….
R.D.Damhof
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- 22 mei 2014
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OktoberBV
2014
– Norske
Who am I - My Data Manifesto
The X commandments of data management
I. Thou shall always respect
& consider the context.
Context is leading
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- 22 mei 2014
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2014
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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
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- 22 mei 2014
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“Most companies manage their
parking lot better than their data” —
Gartner, Frank Buytendijk (paraphrased)
Who am I - My Data Manifesto
The X commandments of data management
III.Thou shall stop centering
apps over data:data first
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- 22 mei 2014
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OktoberBV
2014
– Norske
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
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- 22 mei 2014
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2014
– Norske
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."
Who am I - My Data Manifesto
The X commandments of data management
V. Thou shall abstract
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- 22 mei 2014
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2014
– Norske
Who am I - My Data Manifesto
The X commandments of data management
VI.Thou shall make a
‘fundamentalistic’ separation
between facts & context
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- 22 mei 2014
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– Norske
VI.Thou shall not forsake
time
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- 22 mei 2014
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2014
– Norske
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
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- 22 mei 2014
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Who am I - My Data Manifesto
The X commandments of data management
IX.Thou shall Specify,
Standardise, Automate &
Productise
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- 22 mei 2014
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2014
– Norske
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
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- 22 mei 2014
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2014
– Norske
Who am I - My Data Manifesto
The X commandments of data management
‘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…..’
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- 22 mei 2014
R.D.Damhof– –Prudenza
OktoberBV
2014
– Norske
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R.D.Damhof
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- 22 mei 2014
R.D.Damhof– –Prudenza
OktoberBV
2014
– Norske
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Logistics & Manufacturing
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The Data Push Pull Point
Push/Supply/Source driven
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Mass deployment
Control > Agility
Validation of “ingredients”
Repeatable & predictable processes
Standardized processes
High level of automation
Relatively high IT/Data expertise
All facts, fully temporal
R.D.Damhof – Oktober 2014 – Norske
Pull/Demand/Product driven
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Piece deployment
Agility > Control
Plausibility
User-friendliness
Relatively low IT expertise
Domain expertise essential
Truth, Interpretation, Context
Business Rules Downstream
The Development Style
Systematic
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User & developer are separated
Defensive Governance
Focus on non-functionals
Centralised
Proper system development
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User = developer
Offensive governance
Decentralised
“System development” in production
Opportunistic
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A Data Deployment Quadrant
Push/Supply/Source driven
Data
Push/Pull
Point Pull/Demand/Product driven
Systematic
I
Facts
Development
Style
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Context
III
“Shadow IT,
Incubation,
Ad-hoc,
Once off”
Opportunistic
II
IV
Research,
Innovation &
Design
6 Applications of the Quadrant
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(1) How we produce
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How we produce, process variants
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How we produce, production lines
Production-line: Poly Structured
Production-line: Forms orientation
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Information
Products
Data Products
Eg. XBRL/JSON
Production-line: Data orientation
Access to data
Analytical tools
Processing Power
(2) How we automate
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(2) How we automate
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”
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(3) How we organize
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To centralize or to decentralize
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(4) How do people excel
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(5) How about Technology
Storage:
(R)DBMS
Processing: Automation Software
Data Quality: Validation, Profiling
Development: Data Modeling
Accessibility: Data Virtualization
R.D.Damhof – Oktober 2014 – Norske
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) Business-,Information- or
Data Modeling is key
Natural Language
Ontology
Conceptual
Facts
Logical
Relational
At least the Logical Model
drives the technical data
architecture, design and
implementation
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e.g
Data Vault,
Anchor Model
e.g.
Dimensional,
hierarchical,flat
Oh…data warehouse?
• DWH in Netherlands - since 2007 - have increasingly been split-up between
facts (Quadrant 1) and context (Quadrant 2).
• Quadrant 1 is morphing into an ‘Integrated (Meta)Data Environment’. An
holistic view on data. Not only accepting feeds from other apps, but being
the system-of-record for apps.
• At least integrated on the logical level, preferably on the conceptual level.
• The (meta)data(quality) is fiercely managed & governed centrally in orgs.
• Interestingly; quadrant II is becoming the classic - more Kimball style DWH,
but where conformity is implicit and (technically) data virtualisation is key.
• Central Data Competencies, Decentral (close to demand) BI Competencies
R.D.Damhof – Oktober 2014 – Norske