This document discusses data governance and provides definitions, statistics, and best practices. It notes that while 39% of organizations have little data governance, 72% of CIOs plan to implement enterprise-wide governance in the next three years. Data governance refers to the overall management of data availability, usability, integrity, and security. It involves establishing policies, processes, roles, and technologies to ensure data is used strategically and as a business asset. The five pillars of effective data governance are policies, processes, business rules, people and roles, and technologies.
2. Governance Overview
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Data Governance is an important issue.
CIOs seem to realize the cost of poor data governance and are planning to take action.
• 39% of organizations have little to no focus on data governance
• 45% have pockets of data governance for critical data
• 19% have established enterprise-wide data governance
• 72% of all CIOs surveyed were targeting enterprise-wide data governance within the next three
years
(Accenture’s 2017 CIO Survey)
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– Data is valuable and governance means lots of different things to
lots of different people
– “... a system of decision rights and accountabilities for information-
related processes, executed according to agreed-upon models
which describe who can take what actions with what information,
and when, under what circumstances, using what methods.”
(The Data Governance Institute (DGI)
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“The true function of governance is to actively link integrated
business and technology teams with corporate and strategic
initiatives. Within this context, governance becomes an
integral part of enterprise line management. Executed
properly, the governance function can actively and
effectively reallocate business, technology, reporting and
analytic resources to align with rapidly changing market
demands”
(Duffie Brunson from B-eye-Network)
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Definitions
Data governance refers to the overall management of the
availability, usability, integrity, and security of
the data employed in an enterprise.
Data Governance is a system of decision rights and
accountabilities for information-related processes, executed
according to agreed-upon models which describe who can
take what actions with what information, and when, under
what circumstances, using what methods.
“data needs to be governed as it has neither will nor intent of
its own. Tools and people shape the data and tell it where to
go. Therefore, data governance is the governance of people
and technology” (Thomas, 2016)
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Components
Data Governance for
the purpose of using
data as an asset
driving strategic
objectives.
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Characteristics of Data Governance
The 5 pillars of Data Governance:
1. Policies
2. Processes
3. Business Rules
4. People & Roles
5. Technologies
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Focus Areas
• Policy, Standards, Strategy
• Data Quality
• Privacy, Compliance, Security
• Architecture Integration, Analysis
• Data Warehouse & BI
• Management Alignment
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Critical Success Factors
• Strategic Accountability
• Standards
• Managerial Blind Spot
• Embracing complexity
• Cross-divisional Issue
• Metric
• Partnership
• Choosing Strategic Points of Control
• Compliance Monitoring
• Training and Awareness
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Steps For Success
• Step 1: Get a governor and the right people in place to govern
• Step 2: Survey your situation
• Step 3: Develop a data-governance strategy
• Step 4: Calculate the value of your data
• Step 5: Calculate the probability of risk
• Step 6: Monitor the efficiency of your controls
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Steps For Success
• General consensus being that most data governance programs - if they exist at all
- remain extremely immature and full with risks.
• The most common roadblocks range from:
• Minimal to no executive sponsorship,
• IT-driven efforts with limited to no business participation,
• Lack of business justification
• The ever-present likelihood of "de-prioritization" when a more compelling
initiative or fire drill comes along.
• Increase Focus on Business Process to Build Momentum
13. Rob Cochrane
VP, Solution Delivery
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