dama webinar: taking information governance to the next level

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 HenderyckxChair Presidents Council DAMA International

Copyright –All Intellectual

Rights Reserved 2015 inpuls cvba ,

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 HenderyckxSince 1986

with data

Working

Inpuls Infochannel

Source images

JanHenderyckx , Inpuls_Info

18-‐08-‐15

2




#NOHADOOP

Creating anInformation Centric

Organisation




Most things have already been invented

Reality checkon “disruptive”

18-‐08-‐15

3




Most things have already been invented

Many of the solutions are notnovel

Why now:Cost value equation has

changedWe 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-‐MemoryUnicom, SolidDB, 1992ENEA AB, Polyhedra, 1993

CCA, Model 204, 1972 (column store)




Explosion of informal events

18-‐08-‐15

4




Explosion of informalevents

The internet of “everything”

Capture many more events:Smart Metering,

Fitbit, “Me”devices,

RFID,…

Selfies …

Data Growth is NOT in invoices and products…




Of Data Lakes, Pools or Puddles

18-‐08-‐15

5




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 fromthe law of preservation of misery.

Don’t move it into area’s it’s notbuild for

Hybrid is the answer




The rise of small data

18-‐08-‐15

6




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 activeinformation governance

and data quality.

It’s a mindset




The Chief Data/Digital/Information?

Officer

18-‐08-‐15

7




The Chief Data/Digital/Information? Officer

Information driven is a mindset thatrequires 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




Make the Data OPEN

18-‐08-‐15

8




Make the Data OPENCrowdsource the insight

Data requires a function to create value

Huge potential if we open up the databut:

beware of semantics (semantic web)beware of privacy (London bike data)

Governmental push:EU Open Data, US since 2013, World Bank, …

Local Initiatives




“Yes we can.” But should we?

18-‐08-‐15

9




Yes we can. But should we?

The banking crisis was linked toungoverned business methods

NSA, Snowden, WikiLeaks have changedthe mindset

Lot’s of compliance drivers related to data

Data Privacy is a core value

Authenticity is key

Stay out of the customer personal zone




Information as a business model

18-‐08-‐15

10




Information as a business model

Lot’s of opportunitiesfor better/smarter/more efficient:

PrivateOmni channel retail

from showroomer to showgroomer

Dropped baskets

GovernmentalFraud detection,

single point of contact, citizen services, …

Lot’s of opportunitiesto go out of business:

your competitor might be more information driven




Beware of the hoarder

18-‐08-‐15

11




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 maintenance of it.

Data only has value if we have a function

otherwise it’s a liability (cfr Target)

Need to capture enough metadatato make sense of it




Metadata for survival

18-‐08-‐15

12




Metadata for survivalStrong need for traceability and lineage

Where did this value come from?Regulatory pressure

Beware of the “Dark Data”

Most IT systems are badly documented

No strong industry standards to facilitate this

Beware of best of breed solutions




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 capabilityvisualisation techniques

But it requires: governance, architecture,

ownership, policy, …., tooling

Data is Power© Kollected

18-‐08-‐15

13




Data and Information Life Cycle

RELATIONAL

Define the schema andnormalise before you get

started

Govern semantics tomake safe decision

Data is Power© Kollected

#NOSQL

Bring the functionto the data

Get the dataset and then

try too make sense of it




Data and Information Life CycleData

GovernanceInformationGovernance

Defined Data

Undefined Data

BusinessDriven

Business & IT

Driven

Semantics

Managed“container”

Policy

18-‐08-‐15

14




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




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




Data Driven?

From: data mart to insight to action

Events

next best action

Measure Understand Act

ANALYTICS

ObjectObject

Even

ts

Even

ts

Even

ts




The bigger picture

RISK

Ope

ratio

nal

Insight

Governance

INFORMATION READINESS

Steer This Information is safe to take decisions

This Information is safe to run processes

Information

Data

Info

rmat

ion

Anal

ysis

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




Act now to get a consistent approach

Monthy Python Silly Olympics

100 m for orientation challenged people




InpulsDuwijckstraat 17

2500 LierBelgium

T +32 3 443 17 43M +32 475 94 14 51

Email: [email protected]: www.inpuls.eu

Inpuls Infochannel

Thank you

An Information Management and Data Insight company32

18-‐08-‐15

17



An Information Management and Data Insight company 33

dama webinar: taking information governance to the next level

Business

data quality

data fishing

information governance

selfies data growth

data mining ibm tpf

rise of small data think

dama internationaliccpliaison

adept events