Telling the story of our data governance journey at UNSW Sydney at the DAMA Sydney meeting 13 March 2018

1. Data Governance
A Work in Progress
Kate Carruthers
Version 1.0
March 2018
Classification: PUBLIC

2. Fast facts
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Source: 2016 UNSW Annual Report

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2025 Strategy focus areas

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Ensure that the
institution has the right
information to support
key initiatives for the
2025 Strategy

6. Definition
"Data governance is the organization and implementation
of policies, procedures, structure, roles, and responsibilities
which outline an enforce rules of engagement, decision
rights, and accountabilities for the effective management of
information assets."
(John Ladley, Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program, 2012)
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7. Baseline Principles
Data & information governance
• is a business driven activity
• is a framework to enable the business to better
manage information and data quality
No data or information governance activities will be undertaken
without business buy-in and leadership​
Decision making rights need to be determined
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8. 3 realms of data
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Learning
&
Teaching
Research
Admin
Enterprise systems
Local Faculty-based
systems
Systems of record
Learning Management
Lecture recording
MOOCs
Research data
Publications

9. Cultural issues
Academic freedom
Inventing the future
“We know what we’re doing”
“I’ve got a PhD and you don’t”
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Cybersecurity and enterprise risk
management are a key focus for
Council and Management
Data & information governance are a
key foundation for cybersecurity
Cybersecurity and enterprise risk
management are a key focus for
Council and Management

11. Data & information governance
is a key foundational capability
for cybersecurity Management
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Data & information governance are a
key foundation for cybersecurity

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15. Responses to the hack
War room
Perimeter defences
Visibility at Council level
Risk register
Appointment of dedicated Info Sec resources
including a new CISO
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16. Alignment – DIGO, Legal, Risk, Privacy, IT &
Cyber
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Information literacy
Data driven improvements
Policies &
Standards
Information
Quality
Privacy, Risk
Compliance,
Security
Architecture,
Integration
Establish
Decision Rights
Stewardship
Assess Risk &
Define Controls
Consistent Data
Definitions
Adapted from University of Wisconsin Data Governance Framework

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The 5
Knows
Value
Access
LocationSecurity
Protection
Source: Mike Burgess
https://www.cio.com.au/article/5
83438/telstra-five-knows-cyber-
security/

18. Do you know who has
access to your data?
Do you know the value
of your data?
Do you know the
where your data is?
Do you know who is
protecting your data?
Do you know how well
your data is protected?
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The 5
Knows
Value
Access
LocationSecurity
Protection

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Data Quality
Management
Data Warehouse,
Business Intelligence
& Big Data
Reference & Master
Data Management
Data Architecture,
Data Dictionary &
Modelling
Data
Governance
DATA & INFORMATION GOVERNANCE
• Appropriate use
• Business value
• Information meaning
• Data transparency
• Data lineage
• Data Quality
Information Governance Data Governance
• Data Security
• Change Impact
• Service Levels
• Information Life–cycle
• Information Ownership
• Privacy

20. Fundamentals
Data ownership
Data classification
Data handling guidelines
ISMS Standards
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Boundaries between
Data Governance,
Risk & Cyber teams
– collaboration is
critical

21. The 4 dimensions Framework:
• provides enterprise wide roles and responsibilities to be accountable for decisions related to data assets
• establishes policies & procedures to manage the data assets
• provides diverse tools for managing operational data tasks
UNSW Data Governance Framework focuses on the oversight, guidance and
quality of enterprise data assets enabled through People, Policies, Procedures
and Tools
1
Policies are high level statements
that provide context for strategic
decisions relating to the data assets
People can be members of UNSW
governance bodies, which hold the
authority for decision relating to data
assets
Tools are pre-prepared objects that
support people carrying out procedures
Procedures are specific instructions
designed to ensure policy is followed
and outcomes are measurable
Data
Governance
Centre
Checklists
Data Dictionary
Data Profiling
Data Sharing
Data Reporting
Regulatory
Compliance
Data Asset
Prioritisation
Data Exchange
Agreements
Data Process Flow
Data Integration
Data Security
Strategic Drivers
Dimensions
Enterprise
Oversight of Data
Enterprise
Guidance on Data
Enterprise
Quality of Data
Performance
Metrics
Policies Procedures Tools
Data Executives
Data Owners
Data Stewards
People
Data Creators/
Data Specialists
1 2 3 4
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22. Data & Information Governance Model
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Policy
Framework
Coordinating
Committees
Data Ownership
& Management
• Data Areas
• Data Executives
• Data Owners
• Data Stewards
• Data Governance Policy
• Data Classification Standard
• Data Handling Guidelines
• Information Security Management System
• Data Governance Steering Committee
• Data & Information Governance Group
• Business Intelligence Governance Group
• Information Security Steering Group

23. Data Creator / Data SpecialistsSupport
Strategic
Tactical
Operational
Data
Executive
Data Owner
Data Stewards
• Provides leadership in data quality and in resolving conflict regarding
data assets
• Provides direction and priorities in specific Data Area
• Takes leadership support for the data quality principles, policies and
standards across the Data Area
• Ownership of the Data Area on day-to-day basis – accountable for
checking the Data Quality
• Provide managerial support to the data governance program and develop
data management artefacts
• Provide operational help around planning and issues resolution
• Represent functional areas across the University
• Identify and fix data issues within their respective business areas
• Document and log data quality issues for resolution in source systems
• Provide defined processes for conformance of data to acceptable levels
• Business SMEs
• IT /source System/Application SMEs
• Database Admin, System Admin, Application specialist, Developers,
• Business Analysts, etc.
• Researchers and Academics
Data Ownership and Management
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Role High Level Definition
These roles are aligned to provide
strategic leadership, tactical and
operational excellence to manage the
Data Assets

24. Work plan 2016 - 2018
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Setup policy
framework
Re-establish Data
Governance
Committees
Establish Data
Ownership structure
Identify ‘Crown
Jewels’
Research Data
Governance Policy
& Framework
Data Dictionary
Project
Implement changes
to Project
Methodology
Implement changes
to SDLC
Methodology
Implement Data
Quality Process
Implement Internal
Data Sharing
Agreements
Implement
Reference Data
Management
Implement Master
Data Management
Done PlannedKey: In progress
Implement Data
Classification
Implement System
Classification
Implement ISMS
Implement Business
Glossary Tool

25. But Universities are special…
Research data is special and different
So now we are undertaking a specific Research Data
Governance project together with Pro Vice Chancellor
Research Infrastructure
Providing world leading research data management
solutions with data governance, data management and
ethics
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26. Future directions
• Enable data driven decision making at all levels
• Provide state of the art support for research data management
▪ Code management
▪ Storage, archival and retention in conformance to legislation &
funding agreements
• Integrate ethics, research data management into a seamless
platform
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27. Future directions
• Transition from legacy data warehouse to new analytics
platforms
▪ Predictive analytics
▪ Realtime analytics
▪ Data lakes
• Emerging roles
▪ Data science
▪ Data wrangling & data engineering
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What we’ve learned so far
Build
slowly –
don’t rush

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What we’ve learned so far
Bring the
stakeholders
along too

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What we’ve learned so far
Culture drives
strategy

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What we’ve learned so far
Agile approaches
work

32. This Photo by Unknown Author is licensed under CC BY-SA
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What we’ve learned so far
Cloud makes
everything
easier

33. Thank you
Kate Carruthers
k.carruthers@unsw.edu.au
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