DAMA-DMBOK Database Governance and Metadata Training Course

Course overview

Database teams often inherit conflicting definitions, undocumented tables, unreliable lineage and unclear ownership. The result is not merely a documentation gap: analysts report different figures from the same database, schema changes break downstream reports, retention rules are applied inconsistently, and data incidents take longer to investigate. This DAMA-DMBOK Database Governance and Metadata Training Course gives professionals a practical method for establishing accountable governance around database assets, business definitions, technical metadata and data quality controls.

Participants apply DAMA-DMBOK principles across Data Governance, Metadata Management, Data Quality, Data Architecture, Data Modelling and Data Security. They learn to define data domains and critical data elements, assign data owners and stewards, build a business glossary and data dictionary, capture technical and operational metadata, map source-to-target lineage, and establish governance policies, issue workflows and quality measures. The course also addresses metadata repository design, catalogue operating models, approval workflows and the evidence needed to demonstrate policy compliance.

Teaching combines focused instructor-led sessions with database governance scenarios, catalogue design workshops and team reviews of realistic artefacts. Participants work from a case database containing customer, product and transaction data, then create a governance charter, RACI matrix, critical data element register, metadata standards and lineage specification. They leave with a reusable Database Governance and Metadata Operating Pack that can be adapted for their own platform, whether using a commercial catalogue, cloud data platform or structured spreadsheet repository.

The programme suits data professionals who already work with database structures, reporting data or data controls and now need a recognised framework for making definitions, ownership and metadata management operational across teams.

Course objectives

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

• Apply DAMA-DMBOK Data Governance and Metadata Management principles to a database operating model
• Define data domains, critical data elements and accountable owner-steward roles
• Produce a database governance charter with decision rights, escalation routes and RACI assignments
• Build a controlled business glossary and data dictionary using approved metadata attributes
• Document conceptual, logical and physical metadata for tables, columns, keys and reference data
• Map source-to-target data lineage and identify control points for change-impact assessment
• Design data quality rules, issue workflows and scorecard measures for critical database data
• Create a phased metadata catalogue implementation roadmap with adoption metrics

Benefits of attending

Target competencies

Who should attend

• Data Governance Managers — who need to establish accountable governance across database domains
• Data Stewards — who maintain business definitions, ownership records and data issue evidence
• Database Administrators — who must connect schema metadata and change controls to business governance
• Data Architects — who design data platforms and require consistent metadata and lineage standards
• Data Quality Managers — who need to link critical data elements to measurable quality controls
• Business Intelligence and Analytics Managers — who need trusted definitions and traceable reporting data

Requirements and prerequisites

Participants should understand relational database basics, including tables, columns, primary and foreign keys, schemas, SQL query purpose and the difference between operational and reporting data. Experience working with a database, data warehouse, BI report, data catalogue or data quality process is strongly recommended. Familiarity with governance terms such as data owner, steward, policy and data lineage is useful but not essential; these are established during the course. No DAMA certification, programming expertise, database administration authority or prior use of Collibra or Microsoft Purview is required. Participants should be ready to examine sample metadata and discuss their organisation's data accountabilities.

Training methodology

The instructor uses short DAMA-DMBOK-led briefings to establish each discipline, followed by guided analysis of a realistic database estate. Participants inspect table and column metadata, resolve conflicting business definitions, assign governance roles, map lineage and draft quality controls in small groups. Case reviews test decisions against audit, reporting and change-management scenarios. Each day adds artefacts to an integrated governance pack, and the final session includes peer review and a 90-day application plan for the participant's own database environment.

Course outline

Day 1: DAMA-DMBOK governance foundations for databases

• DAMA-DMBOK knowledge areas and their database governance implications
• Data governance principles, scope statements and operating-model choices
• Data domains, data products and database asset boundaries
• Data owner, data steward, custodian and consumer accountabilities
• Governance decision rights and escalation pathways
• RACI matrix construction for database lifecycle activities
• Critical data element identification and business-risk prioritisation

Workshop: Participants create a governance charter, role matrix and initial critical data element register for the case database.

Day 2: Business and technical metadata standards

• DAMA-DMBOK metadata categories: business, technical, operational and administrative
• Business glossary term structure, naming conventions and approval status
• Data dictionary attributes for tables, columns, keys and code values
• Conceptual, logical and physical data model metadata alignment
• ISO/IEC 11179 metadata registry principles and data element identification
• Metadata quality dimensions: completeness, consistency, currency and usability
• Reference data, master data and controlled value-set documentation

Workshop: Participants define glossary entries and complete a governed data dictionary for a selected customer and transaction schema.

Day 3: Lineage, catalogue and change control

• Source-to-target lineage levels and lineage notation
• Data flow mapping across operational databases, warehouses and reports
• Column-level transformation rules and derivation metadata
• Impact analysis for schema changes, report changes and data defects
• Metadata catalogue operating model and repository selection criteria
• Collibra and Microsoft Purview catalogue capabilities
• Metadata harvesting, curation workflows and certification statuses

Workshop: Participants map end-to-end lineage for a revenue measure and identify affected assets in a simulated schema-change request.

Day 4: Data quality, policy and control evidence

• DAMA-DMBOK data quality management roles and control lifecycle
• Critical data element quality rules and acceptance thresholds
• Validity, completeness, uniqueness, timeliness and reconciliation measures
• Data quality issue logging, root-cause analysis and remediation ownership
• Database governance policies for access, retention and classification
• Control evidence, exception approval and audit-trail requirements
• Data quality scorecards and governance performance indicators

Workshop: Participants design quality rules, an issue workflow and a scorecard for three high-risk critical data elements.

Day 5: Implementing the database governance operating model

• Database governance maturity assessment against DAMA-DMBOK practices
• Prioritising metadata backlog items by risk, value and dependency
• Catalogue adoption measures and stewardship service-level measures
• Stakeholder engagement for database, analytics, risk and business teams
• Governance council agendas, decision logs and review cadence
• Phased implementation roadmap for people, process, metadata and technology
• Ninety-day action planning and benefits measurement

Workshop: Participants assemble and present their Database Governance and Metadata Operating Pack with a prioritised 90-day implementation roadmap.

Tools & standards covered

DAMA-DMBOK2, ISO/IEC 11179, Collibra Data Intelligence Cloud, Microsoft Purview

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions