Refers to the exercise of decision making and authority of data
related matters.
It is not a hardware/software/manpower solution.
It mainly brings together cross functional teams to identify
data issues that affect the company as a whole.
Requires communication between business and IT.
3.
In simple words, data is one of the most important intangible
assets of an organisation.
If lost, it becomes irreplaceable
Information Week study found that the average companys data
volumes nearly double every 12 to 18 months
According to the latest statistics, data breaches in 2008
increased 47% from 2007.
4.
Imagine a situation where you lose all your data due to a virus
attack .
Imagine the loss of reputation of your company due to data
loss
These potential disasters necessitate the inclusion of Data
governance
5. Data Experts
Data Owner
Data Steward
Data Architect
Data Modeler
Data Analyst
6. The Beginning
Data gov. gained importance since Sept 9/11 attacks.
The Enron fraud scandal of Nov 2001 along with Worldcom &
other fraudulent accounting practices, led to a number of
governmental regulations and requirements.
These new rules mandated financial reporting of public
companies and required auditing firms to be objective &
independent of their clients.
7. Initial Struggles
Data gov. has been around for quite some time, but without its
present terms.
Companies tried to align & formulate data policies around
cross-functional databases in 1970s, but to no avail
Premature abandonment of attempts at data gov., along with a
disillusioned viewing of data governance only as data resulted in
its failure.
8. Reasons for its Initial Failure
Lack of data stewards result in their unlikeness to single
handedly carry out a data governance effort.
Data gov. councils simply fade away start with a bang & end
with a whimper
Executive involvement recedes soon.
Enlisting people before proper definition of processes &
outcomes of governance.
9. Organizational Challenges
Vague authority and accountability
Ineffective planning
Poor expectations management
Unclear or ineffective communications
Absence of decision-making protocols
Lack of perceived value
10. When does the need arise for DG?
When the organisation gets too large
When the organisation gets too complicated
When the Data Architects and other related groups need a
cross-functional program to support them
When Regulation, contractual or compliance requirements call
for formal Data gov.
11. Goals of a Data Gov Program
Ensure transparency of process
Protect needs of stakeholders
Reduce Operational friction
Reduce Costs & Increase Effectiveness
Enable better decision making
Train management & staff
Build standard, repeatable processes
12. Principles
Integrity
Transparency
Auditability
Accountability
Stewardship
Checks & Balances
Standardization
Change Management
13. Focus Areas of Data Gov
Data governance with a focus on:
Policy, Standards & Strategy
Data Quality
Privacy, Compliance & Security
Architecture Integration & Analysis
Data Warehouse & BI
Management Alignment
14. Data Governance Process 15. Benefits..
Improved business-IT alignment
Balanced decision-making and authority
Consistent and open processes
Value realization
16. New Best Practices In Data Gov.
Begin with a Key initiative get buy in from executives for
critical data governance support
Make the (better-qualified) Data steward the Change agent
Data governance & data Management are bi-directional
17. Contd.. 4. Change the influencers, not the leaders. Also,
the chair is not the executive sponsor 5. Manage the Data Lifecycle
& Maintian transparency 6. Engage the Right Vendors can help
streamline data governance policies better. 18. Case Study 1 -
World Health & Relief Organization
Collects data from its own efforts and conditions from 98
countries
WHRO realised structuring the data needed
WHRO built a KM system based on MS Sharepoint
System had strong ROI
19.
Expected to generate tens of millions of dollars and
man-hours
Promise of actionable & shareable information on the health
and economic conditions of the worlds poor
Challenge was to make experts, field workers, stakeholders to
agree to these standards.
(according to the Data Governance Institute)
20. References
http://www.datagovernance.com/
http://www.datagovernancematters.com/
http://datagovernanceblog.com/
Data Governance Conference Europe, 2009
Data Governance Annual Conference, 2009
21. Contd.
Moseley, Marty Keys to Data Governance Success: Teamwork and an
Iterative Approach, Information Systems Control Journal, 2008.
Dyche, Jill A Data Governance Manifesto: Designing &
Deploying Sustainable Data Governance, 2007.