Data Governance, like a relationship, requires a strong foundation and commitment to make it work.  This presentation explores the main reasons why Data Governance initiatives fail and the key components that are necessary to build a sustainable program with long-term engagement within your organisation. Learn about the Data Integrity Framework, data governance tools, and how to establish a structured decision tree to drive prioritisation.

1. Data Governance:
From Speed Dating to a
Lifelong Partnership
Cam Ogden | VP Product Management

2. Governance Series
• Session 1: A business-first
approach to governance projects
• Session 2: Core components of
Data Governance programs
that last
• Session 3: Scaling and
automating Data Governance
success
Visit www.precisely.com to access Session 1

3. The Need for Business-First Governance
of governance
initiatives fail to
deliver expected
outcomes
80%
Source: Gartner
Unrealistic
Expectations
Lack of
Leadership
and
Ownership
Overlooking
Cultural
Factors
Regulatory
and
Compliance
Challenges
Insufficient
Resources
and
Support
Poor
Training
and
Education
Resistance
to
Change
Inadequate
Communication
and
Engagement
Lack of
Continuous
Monitoring
and
Improvement
Lack of
Data Quality
and
Management
of companies
believe data
governance is vital
for their business
85%

4. Data Governance continues to evolve
1990s-2000s
Early Days
~2010
Rise of Big Data
~2015
Regulatory Compliance
~2020
Rise of Analytics
~2020+
Rise of AI/ML
Transformative Defensive Offensive Generative
Value
Creation

5. Effective Governance aligns data requirements with business goals
Business / Program Goals
Objectives and Metrics
Governance Framework
& Operating Model
Information (business terminology)
Data

6. Core Components

7. Key Components to a Sustainable Program
Decision Tree to identify
critical data
Business Accountability for
data with ‘fit for purpose’
operating models/processes
Data Integrity Framework
that ensures the availability,
usability, integrity, and
sustainability of our most
critical data
Data Governance tooling
that accelerates the data
integrity lifecycle
Successful
Data
Programs

8. Data Integrity Framework
Policies, processes, standards
• Operating model
• Roles & responsibilities
• Data governance team
• Ownership
• Escalation structure
Structure
• Operating model
• Roles & responsibilities
• Data governance team
• Ownership
• Escalation structure
Strategy
• Vision statement
• Objectives & goals
• Building business case
• Building high level roadmap
• Alignment to data strategy
Technology
• Glossaries
• Metadata repository
• Business & technical lineage
• Workflows
• Enable collaboration
Metrics
• Statistics & analysis
• Progress tracking
• Issues monitoring
• Data governance scores
• Data quality scores
Communication
• Rollout Plan
• Communication Plan
• Training Plan
• Onboarding Data Stewards Plan
• Program Management
Data Integrity

9. Context matters…

10. Strategically Approaching Digital Transformation
Operating Models orchestrate
decision-making processes to be
repeatable, consistent, and scalable
Leading programs establish
a “play book” of Operating
Models for key data
management and
governance processes
10

11. 11
Data360 Connects Data That Matters
Business
Leadership
Data Analytics
Business
Operations
Data Quality
& Stewardship
Enterprise
Architecture
Governance Tools must bring
together the data organizational model

12. Decision Tree Drives Prioritisation
Establishing a structured, repeatable decision tree to
identify and evaluate Critical Data Elements and determine
the appropriate governance strategy, method and
ownership model.
It ensures Critical Data Elements are tied to business value
drivers and dictates impact and prioritisation.
What do we
govern?
How should we
govern?
Governance
Model
Who should
govern?
Where should
we govern?

13. Governance accelerates the data delivery lifecycle
Enrich
Cleanse
Secure
Prevent
Discover
Understand
Discover
data assets and
metadata
Understand
data meaning and
purpose
Cleanse
data to achieve
desired quality
levels
Enrich
with 3rd party data
and location-
derived context
Secure
data to meet
standards for
security/privacy
Monitor
data changes for
impacts/disruption

14. Cloud / VPC / On-Premises
Data
Integration
Data
Observability
Data
Quality
Geo
Addressing
Spatial
Analytics
Data
Governance
Data
Enrichment
APIs and SDKs
Enterprise Business
Systems
• Enterprise apps
• Analytics tools
• Precisely industry
apps
• BI dashboards
• AI/ML
Enterprise Data
Sources
• Business Intelligence
• CRM
• Workforce mgmt.
• Data warehouse
• ERP
• Billing
Data Integrity Services
Data Integrity Foundation Data catalog Intelligence Agents

15. Key Components to a Sustainable Program
Decision Tree to identify
critical data
Business Accountability for
data with ‘fit for purpose’
operating models/processes
Data Integrity Framework
that ensures the availability,
usability, integrity, and
sustainability of our most
critical data
Data Performance
Measures that organises
critical data quality and
governance metrics
Successful
Data
Programs

16. Panama Canal
Keep
Digging…

17. Questions?
precisely.com/solution/data-governance-solutions