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Data Strategy Overview

Address fragmentation through strategic changes that enable scalable, trusted data and analytics.

Data vision
To become a data-driven organisation, treat connected data as a strategic asset and manage it responsibly across products, markets and domains.
Key
strategic
changes

Unified data
platform
architecture

Integrated data platforms and AI-enabled capabilities

Data
governance
and ownership
model

Governance Board and appointed Data Domain Owners

Service and
process model

Clear service roles and repeatable processes across domains

Data product
framework

A standard framework for reusable data products

Data
transparency
and quality

Standard processes for visible, trustworthy data

Privacy and
data usage
controls

Defined privacy, sharing and data-use controls

Current
challenges
Fragmented data
landscape
Unclear ownership
and governance
Inconsistent service
and process delivery
Limited reuse of
data assets
Low visibility and
trust in data
Manual data sharing
and compliance

One connected framework

The five pillars express data strategy priorities.
Four data management foundations organise the work needed to deliver them.

Business outcomes and Data Strategy

Five strategic data pillars, supported by four data management foundations

ONE Connected
Data

Link assets and
business context together

Data
Language

Agree meaning
and definitions

Data
Quality

Make data fit
for purpose

End-to-End
Transparency

See dependencies
and impacts

Data
Culture

Build ownership
and daily habits

Data Governance

Data Quality

Data Operations

Data Protection

Data Management Fundamentals

The four foundations work together throughout the Data Journey, with clear responsibilities at each step.

Data Governance

Who decides?

Agree meaning, ownership, decision
rights and shared rules.

Catalogue and metadata

Data Quality

Can we trust it?

Define fitness for purpose, check data
and resolve root causes.

Quality and observability

Data Operations

How does it work?

Model, connect, transform and trace
information across systems.

Architecture, integration and lineage

Data Protection

Can we use it responsibly?

Apply classification, privacy, access,
retention and disposal requirements.

Classification and retention

Data Governance Dimensions

Connect business goals, governance outcomes and the capabilities that enable the Data Journey.

Business
dimension
Business goals & strategy
Governance
dimensions
1 Data
transparency
2 Data
availability
3 Data
quality
4 Data
coherence
5 Data security
& compliance
Core
capabilities
Data documentation
& cataloguing
Data Lineage
Data sourcing
Data platform
Data products
Data quality
management
Master data
management
Data Privacy & Security
Regulatory compliance
management
Foundational
dimensions
6 Standards & policies
7 Roles & responsibilities
8 Business processes
9 Technology
Music