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18-­‐08-­‐15
1
An Information
Management and Data
Insight company
Taking Information Governance
to the Next Level:
Creating an Information Centric Organisation
August 18th 2015
Jan  Henderyckx
Chair  Presidents   Council  DAMA  International
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
• Information  Management  Analyst,  
Consultant  and  Trainer  with  Inpuls  cvba
•Information  Architecture  and  Strategy,  Information  Governance,  
Data  Quality,  Business  Intelligence,  Cross  Platform  And  Cross  Database
• Publications:  Database  Magazine,  IDUG  journal,  CA  journal,  BMC  journal,  Information,
• Seminars  and  workshops:  SAI,  Adept  Events,  IRM
•Involvement  in  non-­‐profit  initiatives:  
•Director  of  DAMA  BeluxChapter                                                          (http://dama-­‐belux.org/)
•Chair  Presidents  Council  DAMA  International                (http://www.dama.org)
•DAMA  International-­‐ICCPLiaison
Your  Presenter:  Jan  Henderyckx
Since 1986
with data
Working
Inpuls Infochannel
Source images
JanHenderyckx , Inpuls_Info
18-­‐08-­‐15
2
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
#NOHADOOP
Creating an
Information Centric
Organisation
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Most things have
already been invented
Reality check
on “disruptive”
18-­‐08-­‐15
3
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Most things have
already been invented
Many of the solutions are not
novel
Why now:
Cost value equation has
changed
We are changing the problem
setting, eg. drop the ACID req’s
Ubiquitous computing,
networking, ..
In  1959,   Arthur   Samuel  
defined   machine  learning
In  the   1960s,  statisticians   used  
terms   like   "Data   Fishing"  or  "Data  
Dredging"
Data  mining  process  
(1999   European   Cross   Industry   Standard   Process   for  
Data  Mining)
IBM   TPF,  1979   In-­‐Memory
Unicom,  SolidDB,  1992
ENEA   AB,   Polyhedra,  1993
CCA,   Model  204,   1972   (column  store)
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Explosion of informal
events
18-­‐08-­‐15
4
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Explosion of informal
events
The internet of “everything”
Capture many more events:
Smart Metering,
Fitbit,
“Me”devices,
RFID,
…
Selfies …
Data Growth is
NOT in invoices and products…
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Of Data Lakes,
Pools or Puddles
18-­‐08-­‐15
5
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Of Data Lakes, Pools or
Puddles
Hadoop is here to stay,
but should it push out all the original
inhabitants? Relational, SQL, …
NOHADOOP
The new kid on the block suffers from
the law of preservation of misery.
Don’t move it into area’s it’s not
build for
Hybrid is the answer
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
The rise of small data
18-­‐08-­‐15
6
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
The rise of small
data
Think weakest link:
A data lake without docking points gives a
lot of insight about something uncertain.
You can’t “statistical relevant”
yourself out of the quality of
master and reference data.
Focus on active
information governance
and data quality.
It’s a mindset
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
The Chief
Data/Digital/Information?
Officer
18-­‐08-­‐15
7
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
The
Chief Data/Digital/Information?
Officer
Information driven is a mindset that
requires a company-wide approach:
Need someone at C-level to keep the
focus on the program (2020+)
Can either be:
value (innovation)
risk (compliance/CFO) driven
Primarily a business challenge (CIO?)
Chief IMPORTANCE Officer
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Make the Data OPEN
18-­‐08-­‐15
8
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Make the Data OPEN
Crowdsource the insight
Data requires a function to create value
Huge potential if we open up the data
but:
beware of semantics (semantic web)
beware of privacy (London bike data)
Governmental push:
EU Open Data, US since 2013, World Bank, …
Local Initiatives
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
“Yes we can.”
But should we?
18-­‐08-­‐15
9
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Yes we can.
But should we?
The banking crisis was linked to
ungoverned business methods
NSA,Snowden,WikiLeaks have changed
the mindset
Lot’s of compliance drivers relatedto data
Data Privacyis a core value
Authenticity is key
Stay out of the customer personalzone
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Information as
a business model
18-­‐08-­‐15
10
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Information as a
business model
Lot’s of opportunities
for better/smarter/more efficient:
Private
Omni channel retail
from showroomer to showgroomer
Dropped baskets
Governmental
Fraud detection,
single point of contact, citizen services, …
Lot’s of opportunities
to go out of business:
your competitor might be more information
driven
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Beware of the hoarder
18-­‐08-­‐15
11
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Beware of the
hoarder
You shouldn't beallowed to get
data unless:
the quality decay rate is consistent
with the effort you are willing to put
in the maintenanceof it.
Data only has value if we have a
function
otherwise it’s a liability (cfr Target)
Need to capture enough metadata
to make sense of it
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Metadata for survival
18-­‐08-­‐15
12
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Metadata for survival
Strong needfor traceabilityand lineage
Where didthis value come from?
Regulatorypressure
Beware of the “Dark Data”
Most IT systems are badly documented
No strong industry standards to facilitate
this
Beware of best of breedsolutions
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
The perfect storm
“We are living in the data age”
reduced:
cost of execution
(hybrid, cloud,storage,network,
processors,…)
increased:
availability of data (sensors,capturing,…)
analytical capability
visualisationtechniques
But it requires:
governance,architecture,
ownership,policy, …., tooling
Data	
   is	
  Power©	
   Kollected
18-­‐08-­‐15
13
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Data and Information Life Cycle
RELATIONAL
Define the schema and
normalise before you get
started
Govern semantics to
make safe decision
Data	
   is	
  Power©	
   Kollected
#NOSQL
Bring the function
to the data
Get the dataset
and then
try too make sense of it
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Data and Information Life Cycle
Data
Governance
Information
Governance
Defined Data
Undefined Data
Business
Driven
Business &
IT
Driven
Semantics
Managed
“container”
Policy
18-­‐08-­‐15
14
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
This Information is
safe to take
decisions
INFORMATION READINESS
Sustainable Information Readiness
Gather Serve Dispose
Maintain
Define Refine
Govern
Validate
Steer
Industrialise
Hypothesis testing
This Information is
safe to run
processes
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
HOV1 DATA  Analysis  models
Manage  the  
effectiveness of  
your investment
Data
Engineer
Data
Scientist
Business Expert Strategic
Steering
Hypothesis
Industrialise
HOV1 aka BIG Data
18-­‐08-­‐15
15
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Data Driven?
From: data mart to insight to action
Events
next best
action
Measure Understand Act
ANALYTICS
Object
Object
Events
Events
Events
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
The bigger picture
RISK
Operational
Insight
Governance
INFORMATION READINESS
Steer This Information is
safe to take
decisions
This Information is
safe to run
processes
Information
Data
Information
Analysis
Strategic
Tactic
Operational
Strategic differentiatio n
Tactic steering
Operational Efficiency
Tactic steering
Operational support
Insight creation
Hypothesis testing
Performance mgt.
Budgeting & forecasting
Metrics & Scorecards
Internal Drivers External Drivers
18-­‐08-­‐15
16
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Act now to get a consistent approach
Monthy Python
Silly Olympics
100 m for orientation
challenged people
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company
Inpuls
Duwijckstraat 17
2500  Lier
Belgium
T  +32  3  443  17  43
M  +32  475  94  14  51
Email:  Jan.Henderyckx@inpuls.eu
Web:  www.inpuls.eu
Inpuls  Infochannel
Thank  you
An  Information  Management  and  Data  Insight  company
32
18-­‐08-­‐15
17
Copyright–AllIntellectualRightsReserved2015inpulscvba,
An   Information   Management   and  
Data  Insight   company 33

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DAMA Webinar: Taking Information Governance to the Next Level

  • 1. 18-­‐08-­‐15 1 An Information Management and Data Insight company Taking Information Governance to the Next Level: Creating an Information Centric Organisation August 18th 2015 Jan  Henderyckx Chair  Presidents   Council  DAMA  International Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company • Information  Management  Analyst,   Consultant  and  Trainer  with  Inpuls  cvba •Information  Architecture  and  Strategy,  Information  Governance,   Data  Quality,  Business  Intelligence,  Cross  Platform  And  Cross  Database • Publications:  Database  Magazine,  IDUG  journal,  CA  journal,  BMC  journal,  Information, • Seminars  and  workshops:  SAI,  Adept  Events,  IRM •Involvement  in  non-­‐profit  initiatives:   •Director  of  DAMA  BeluxChapter                                                          (http://dama-­‐belux.org/) •Chair  Presidents  Council  DAMA  International                (http://www.dama.org) •DAMA  International-­‐ICCPLiaison Your  Presenter:  Jan  Henderyckx Since 1986 with data Working Inpuls Infochannel Source images JanHenderyckx , Inpuls_Info
  • 2. 18-­‐08-­‐15 2 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company #NOHADOOP Creating an Information Centric Organisation Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Most things have already been invented Reality check on “disruptive”
  • 3. 18-­‐08-­‐15 3 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Most things have already been invented Many of the solutions are not novel Why now: Cost value equation has changed We are changing the problem setting, eg. drop the ACID req’s Ubiquitous computing, networking, .. In  1959,   Arthur   Samuel   defined   machine  learning In  the   1960s,  statisticians   used   terms   like   "Data   Fishing"  or  "Data   Dredging" Data  mining  process   (1999   European   Cross   Industry   Standard   Process   for   Data  Mining) IBM   TPF,  1979   In-­‐Memory Unicom,  SolidDB,  1992 ENEA   AB,   Polyhedra,  1993 CCA,   Model  204,   1972   (column  store) Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Explosion of informal events
  • 4. 18-­‐08-­‐15 4 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Explosion of informal events The internet of “everything” Capture many more events: Smart Metering, Fitbit, “Me”devices, RFID, … Selfies … Data Growth is NOT in invoices and products… Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Of Data Lakes, Pools or Puddles
  • 5. 18-­‐08-­‐15 5 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Of Data Lakes, Pools or Puddles Hadoop is here to stay, but should it push out all the original inhabitants? Relational, SQL, … NOHADOOP The new kid on the block suffers from the law of preservation of misery. Don’t move it into area’s it’s not build for Hybrid is the answer Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company The rise of small data
  • 6. 18-­‐08-­‐15 6 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company The rise of small data Think weakest link: A data lake without docking points gives a lot of insight about something uncertain. You can’t “statistical relevant” yourself out of the quality of master and reference data. Focus on active information governance and data quality. It’s a mindset Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company The Chief Data/Digital/Information? Officer
  • 7. 18-­‐08-­‐15 7 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company The Chief Data/Digital/Information? Officer Information driven is a mindset that requires a company-wide approach: Need someone at C-level to keep the focus on the program (2020+) Can either be: value (innovation) risk (compliance/CFO) driven Primarily a business challenge (CIO?) Chief IMPORTANCE Officer Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Make the Data OPEN
  • 8. 18-­‐08-­‐15 8 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Make the Data OPEN Crowdsource the insight Data requires a function to create value Huge potential if we open up the data but: beware of semantics (semantic web) beware of privacy (London bike data) Governmental push: EU Open Data, US since 2013, World Bank, … Local Initiatives Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company “Yes we can.” But should we?
  • 9. 18-­‐08-­‐15 9 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Yes we can. But should we? The banking crisis was linked to ungoverned business methods NSA,Snowden,WikiLeaks have changed the mindset Lot’s of compliance drivers relatedto data Data Privacyis a core value Authenticity is key Stay out of the customer personalzone Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Information as a business model
  • 10. 18-­‐08-­‐15 10 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Information as a business model Lot’s of opportunities for better/smarter/more efficient: Private Omni channel retail from showroomer to showgroomer Dropped baskets Governmental Fraud detection, single point of contact, citizen services, … Lot’s of opportunities to go out of business: your competitor might be more information driven Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Beware of the hoarder
  • 11. 18-­‐08-­‐15 11 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Beware of the hoarder You shouldn't beallowed to get data unless: the quality decay rate is consistent with the effort you are willing to put in the maintenanceof it. Data only has value if we have a function otherwise it’s a liability (cfr Target) Need to capture enough metadata to make sense of it Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Metadata for survival
  • 12. 18-­‐08-­‐15 12 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Metadata for survival Strong needfor traceabilityand lineage Where didthis value come from? Regulatorypressure Beware of the “Dark Data” Most IT systems are badly documented No strong industry standards to facilitate this Beware of best of breedsolutions Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company The perfect storm “We are living in the data age” reduced: cost of execution (hybrid, cloud,storage,network, processors,…) increased: availability of data (sensors,capturing,…) analytical capability visualisationtechniques But it requires: governance,architecture, ownership,policy, …., tooling Data   is  Power©   Kollected
  • 13. 18-­‐08-­‐15 13 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Data and Information Life Cycle RELATIONAL Define the schema and normalise before you get started Govern semantics to make safe decision Data   is  Power©   Kollected #NOSQL Bring the function to the data Get the dataset and then try too make sense of it Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Data and Information Life Cycle Data Governance Information Governance Defined Data Undefined Data Business Driven Business & IT Driven Semantics Managed “container” Policy
  • 14. 18-­‐08-­‐15 14 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company This Information is safe to take decisions INFORMATION READINESS Sustainable Information Readiness Gather Serve Dispose Maintain Define Refine Govern Validate Steer Industrialise Hypothesis testing This Information is safe to run processes Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company HOV1 DATA  Analysis  models Manage  the   effectiveness of   your investment Data Engineer Data Scientist Business Expert Strategic Steering Hypothesis Industrialise HOV1 aka BIG Data
  • 15. 18-­‐08-­‐15 15 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Data Driven? From: data mart to insight to action Events next best action Measure Understand Act ANALYTICS Object Object Events Events Events Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company The bigger picture RISK Operational Insight Governance INFORMATION READINESS Steer This Information is safe to take decisions This Information is safe to run processes Information Data Information Analysis Strategic Tactic Operational Strategic differentiatio n Tactic steering Operational Efficiency Tactic steering Operational support Insight creation Hypothesis testing Performance mgt. Budgeting & forecasting Metrics & Scorecards Internal Drivers External Drivers
  • 16. 18-­‐08-­‐15 16 Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Act now to get a consistent approach Monthy Python Silly Olympics 100 m for orientation challenged people Copyright–AllIntellectualRightsReserved2015inpulscvba, An   Information   Management   and   Data  Insight   company Inpuls Duwijckstraat 17 2500  Lier Belgium T  +32  3  443  17  43 M  +32  475  94  14  51 Email:  Jan.Henderyckx@inpuls.eu Web:  www.inpuls.eu Inpuls  Infochannel Thank  you An  Information  Management  and  Data  Insight  company 32