1. DATA GOVERNANCE

2. Definition

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.

22. Vasanthi Nagappan