Organisations collect more data every year, but trust in it does not rise at the same pace. Duplicate customers, missing fields, inconsistent codes and untraced spreadsheets cause wrong decisions, failed audits and expensive manual rework. Privacy and data protection duties add pressure to know exactly what data is held, where it sits and who is accountable for it.

This course approaches governance, quality and stewardship through analytics. Participants start by agreeing what good data means for their business and by building a governance model with clear roles, decision rights and policies. They then learn to profile data, define measurable quality dimensions, set rules and tolerances, and monitor results over time. Further sessions cover metadata, business glossaries, catalogues, lineage and master and reference data, followed by issue management, root cause analysis and remediation workflows. The closing sessions deal with measuring programme maturity, reporting value and building a stewardship community that lasts.

The approach is hands-on. Delegates use SQL queries, spreadsheet functions and dashboard software on sample datasets, and finish with a data quality baseline, a stewardship charter and a roadmap suited to their organisation.

By the end of the course, participants will be able to:

• Establish a data governance operating model with defined owners, stewards and decision rights.
• Profile datasets to detect gaps, duplicates, invalid values and inconsistencies.
• Define quality dimensions, rules, thresholds and scorecards aligned to business needs.
• Build dashboards that monitor quality trends and stewardship performance.
• Document metadata, glossaries, lineage and critical data elements.
• Run issue management and root cause analysis to fix problems at their source.
• Assess governance maturity and present the business case for improvement.

The course is designed for people who create, manage, rely on or control organisational data, including:

• Data stewards, data owners and data governance leads
• Business intelligence and reporting analysts
• Database administrators and data engineers
• Records, information and knowledge managers
• Risk, compliance and data protection officers
• Internal and information systems auditors
• Monitoring, evaluation and research data managers
• ICT managers in banks, government, health and utilities

Participants leave with:

• A data quality baseline built from profiling a real-style dataset.
• A rule library covering completeness, validity, uniqueness and consistency.
• A working dashboard design for quality and issue tracking.
• A stewardship charter with roles, responsibilities and escalation paths.
• A starter business glossary and critical data element register.
• A phased roadmap and maturity assessment for their organisation.

The course is lab based and tied to the daily work of data teams. Methods include:

• Short framework briefings followed by immediate application
• SQL and spreadsheet profiling on sample datasets with deliberate defects
• Dashboard building sessions that track quality over simulated months
• Role-play of governance council meetings and steward escalations
• Peer review of each delegate's roadmap and charter

Delegates who complete the labs and attend all sessions receive a CPD-accredited Certificate of Completion from Vision Reach Global Consultancy.