Cambridge
Academy
In London

Introduction

Data Governance helps organizations manage data as an asset—making it reliable, secure, well-defined, and usable for reporting and decision-making. This practical program introduces simple governance structures, stewardship roles, decision rights, and routines for standards, quality, access, and accountability.

 

Course Objectives

• Explain data governance concepts and why they matter

• Define governance roles: owners, stewards, custodians, and users

• Clarify decision rights for data standards, access, and quality

• Establish simple governance processes: policies, issue management, change control

• Create a practical data governance starter toolkit and rollout plan

 

Target Audience

• Data management officers and data governance teams

• Data owners, data stewards, and business analysts

• BI/reporting teams and data platform staff

• Risk, compliance, and information security partners

• Anyone responsible for data quality, access, or definitions

 

Course Outlines

Day 1: Data Governance Foundations

• What data governance is and why it matters (trust, risk, value)

• Key concepts: data domains, critical data elements, lifecycle

• Governance vs data management vs IT operations (clear differences)

• Common frameworks overview (DAMA, DCAM concepts) in simple terms

• Activity: Identify your priority data domains and pain points

 

Day 2: Roles and Stewardship Model

• Role clarity: data owner, data steward, custodian, producer, consumer

• Stewardship responsibilities: definitions, quality, access, issue resolution

• Organizing stewardship: domain vs function, central vs federated

• Skills and routines for stewards (practical checklist)

• Workshop: Build a RACI for one data domain

 

Day 3: Decision Rights and Governance Structures

• Decision types: definitions, standards, access, retention, quality rules

• Decision rights tools: RACI/RAPID basics for data decisions

• Governance forums: data council, domain working groups, architecture review

• Terms of reference, cadence, and escalation paths

• Activity: Draft a decision-rights map and committee ToR outline

 

Day 4: Policies, Standards, and Issue Management

• Core governance artifacts: policies, standards, procedures, guidelines

• Business glossary basics: naming, definitions, owners, approval

• Metadata and lineage: what to capture first (simple approach)

• Data issue management: logging, triage, root cause, remediation tracking

• Case study: Run a data issue through a simple governance workflow

 

Day 5: Data Quality, Access Controls, and Rollout Planning

• Data quality dimensions and practical rules (validity, completeness, timeliness)

• Monitoring: dashboards, exception reports, and thresholds

• Access governance basics: classification, least privilege, approvals, reviews

• Implementation plan: quick wins, communications, training, adoption measures

• Activity: Produce a one-page data governance charter and 90-day plan