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Business Analysis Professional Development Day – Sep 2015
Data Governance and Cross-Functional Needs
Neelam Mohanty
Agenda
2
Agenda What is Data Governance
Goals of Data Governance
- Eliciting definitions from a cross-functional group of stakeholders- Non-invasive data governance- Building a change coalition of data stewards
Impact on Data Quality
3
Examples of data governance
Single Version of the Truth600 individuals whose only role is Faculty300 individuals whose only role is Staff25 individuals are Staff but also are adjunct Faculty75 individuals are faculty but also have a Staff role
Total Faculty & Staff : 1000675 counted as Faculty325 counted as Staff
1,000 <> 1,100
Total Faculty 1,000
Total Staff400
Source: University of Notre Dame Presentation HEDW 2013
How You Ask is as Important as What You Ask
4
Context Matters
Clarity Matters
The question matters
Governance is as much about how you use the terms as it is about the terms themselves
Counting Problem
5
6
Active Student
Definition
An individual who has been confirmed by an admitting office ( or other admitting authority), as recorded by the University Registrar, is considered an active student until he or she:
Graduates ( if degree-seeking)
Completes the academic term ( If non-degree seeking) Withdraws or is dismissed by the University
Fails to enroll for a spring or fall academic term ( unless granted a leave of absence by a Dean)
Counting Problem
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8
Business Impact of Low Data Governance
Distrust of data coming from BI/DW system
No on-going responsibility for quality of a project after go-live
Continuous cleaning of data without putting in place preventive measures
Why does this challenge occur ?
9
Data is a “lateral” asset spanning multiple functional areas
• Each household brings their own ways of living, preferences, attitudes. A different level of cooperation and coordination is required to live together ( productively/peacefully) in the same house
• The problem is that our applications and business needs for information are integrated, but our behavior has not changed to work effectively in this world
Source: SF DAMA Day 2006
Definition of data governance
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Data governance (DG) refers to the overall management of the availability, usability, integrity, and
security of the data employed in an enterprise.
Source: searchdatamanagement.techtarget.com/Definition/0…
Data governance is the practice of organizing and implementing policies, procedures and standards
for the effective use of an organization’s structured/unstructured information assets.
Source: www.sdn.sap.com…
Data Governance: The execution and enforcement of authority over the management of data assets
and the performance of data functions.
Source: www.tdan.com/view-articles/5037
Data governance is the decision-making process that prioritizes investments, allocates resources,
and measures results to ensure that data is managed and deployed to support business needs.
Source: www.b-eye-network.com/view/8393
Multiple Definitions: pick the one that you like
Definition of data governance
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Data governance recognizes that data is an important enterprise data asset and applies the same
rigor to managing this asset as it does for any other asset
Source: Jonathan Geiger
A program for defining information policies that relate to the constraints of the business
Source: David Loushin
Execution and enforcement of authority over the management of data and data-related processes
Source: Gwen Thomas
A process focused on managing the quality, consistency, usability, security, and availability of
information
Source: Alex Berson and Larry Dubov
Definition of data governance
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Data Governance ensures that accurate information gets to the
right person , for the
right reason, at the
right time to make the
right decisions
Here’s the one that I like : The 4 “R”s
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How do you justify a data governance program?
Make your business caseIs it compliance related?
Health Care - HIPAA (Health Information portability and accountability act)
Financial Reporting - SOX(Sarbanes Oxley Act of 2002)
Federal Information - FISMA (Federal Information Security Management Act of 2002)
Financial Institutions - GLBA (Gramm-Leach-Bliley Act)
Payment Card Processing - PCI DSS (Payment Card Industry Data Security Standard)
Higher Education - FERPA (Family Educational Rights and Privacy Act)
National Data Privacy Law
Data Quality Act
Patriot Act
Corporate Information Security Accountability Act of 2003
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How do you justify a data governance program?
Make your business case
Reliable management reporting
Optimized business processes
Timely mergers and acquisitions
Reduced risk in customer and business data retention when stored per a defined data lifecycle
Master Data Management – Providing the golden record for customers, employees, products, members, providers etc. allowing for better customer service, ability to cross sell and upsell , visibility across multiple domains ( E.g. providers who are also members), correct addresses to mail campaigns, discount on CASS certified postal mail etc.
Process of data governance
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Scope
Who has input
Who makes the decisions
Enforcement
Five dimensions to scope
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Data
System
Business Process
Organization
Policy Type
Governance Model
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Data DefinersData UsersData Producers
Tactical Data Stewards(Cross Department/Business-Unit)
Data Steward Coordinators
Information Governance Council(Enterprise)
ExecutivesSenior Managers
Data Stewards/Trustees/Custodians/Guardians(Department or Business Unit Specific)
ExecutiveSponsor(s)
Strategic
Tactical
Operational
EIM Council
Business Unit
Enterprise
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Executive Leadership
Governance Managers /Process Owners
Stewardship / Quality Management & Data Architecture
Data Users
Executive Sponsor & Strategic Level– Sponsors the Governance program– Provides support leadership and funds– Provides guidance and sets direction
Program Level– Leads the governance program at a tactical level – Responsible for ensuring data governance process compliance at
business entity level
Execution Level – Does the actual Data governance activities– Works with the data owners and users to ensure data standards and
quality– Works with Data architecture manager, data architects and data
analysts for preparation of artifacts for governance
Exec
ution
Pla
n
Com
mun
icati
on P
ath
& V
enue
s fo
r Int
erac
tions
Feedback Loop &Issue Resolution
Enterprise Data Management – Data Governance Components
Example RACI MATRIX
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