CPD timing
Time estimate (transparent)
I publish time estimates because CPD needs to be defensible. The goal is honesty, not marketing.
Guided learning
11h
Core levels, structured learning
Practice and consolidation
1h
Summary, drills, revisits
Notional range
8 to 18 hours
Quick: essential reading and the flagship exercises. Standard: one full guided pass through the course. Deep: extra drills, revisits, and reflection evidence.
How I estimate time
I use a notional learning hours approach and I keep the assumptions visible. Where modules are content heavy, I add practice so the hours are earned, not claimed.
- Reading: 225 words per minute, multiplied by 1.3 for note taking and checking understanding.
- Labs and practice: about 15 minutes per guided activity, including at least one retry.
- Reflection for CPD: about 8 minutes per module for a short defensible note and evidence link.
- Assessments: about 1.4 minutes per question for reading, thinking, and review.
If you study faster or slower, your hours will differ. What matters is that the method is consistent and the activities are real.
Data contract and glossary
Foundations output
A simple data contract: key fields, meanings, owners, and what 'good data' means in this context.
Quality and trust plan
Applied output
A practical plan: checks, thresholds, monitoring signals, and what you do when quality drops.
Governance and operating model note
Practice & Strategy output
A short governance note: decision rights, controls, evidence, and how you avoid theatre while staying accountable.
Assessment and practice assessment
Data assessment blueprint
Practice assessments are available for each level and are pulled from the published question bank. Timed assessments are not yet published, so the practice route remains the main verification loop.
Advanced systems
mixedArchitecture, governance, and trade-offs at scale.
Questions: 12
Design rules
- Assessment must include at least one artefact output, for example a small schema with constraints and a data quality plan.
Mapping
How this course stays defensible
This links the same four things CPD reviewers care about: what you learn, how you practise, how you are assessed, and what evidence you can show.
Foundations
Practice assessment
Vocabulary, formats, and basic quality reasoning.
Evidence artefact
Data contract and glossary
A simple data contract: key fields, meanings, owners, and what 'good data' means in this context.
Applied
Practice assessment
Schemas, pipelines, and trust signals.
Evidence artefact
Quality and trust plan
A practical plan: checks, thresholds, monitoring signals, and what you do when quality drops.
Advanced systems
Practice assessment
Architecture, governance, and trade-offs at scale.
Evidence artefact
Governance and operating model note
A short governance note: decision rights, controls, evidence, and how you avoid theatre while staying accountable.
Coverage matrix
Module-level coverage
This matrix makes the course defensible: each module is tied to an outcome focus, the anchor standards, and the evidence you can produce.
| Level | Module | Outcome focus | Domains | Alignment | Assessment | Evidence |
|---|---|---|---|---|---|---|
| Foundations | What Is Data data-foundations-what-is-data Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Define what data is in context and what makes it useful for decisions. | contracts | Other: Definitions and shared meaning | Practice assessment | Template + rubric |
| Foundations | Dikw data-foundations-dikw Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Data reasoning, definitions, and reliability | - | - | Practice assessment | Template + rubric |
| Foundations | Units And Notation data-foundations-units-and-notation Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Data reasoning, definitions, and reliability | - | - | Practice assessment | Template + rubric |
| Foundations | Representation And Formats data-foundations-representation-and-formats Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Choose formats and representations that reduce ambiguity and errors. | contracts | Other: Interoperability | Practice assessment | Template + rubric |
| Foundations | Standards And Interoperability data-foundations-standards-and-interoperability Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Data reasoning, definitions, and reliability | - | - | Practice assessment | Template + rubric |
| Foundations | Open Data And Fair data-foundations-open-data-and-fair Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Data reasoning, definitions, and reliability | - | - | Practice assessment | Template + rubric |
| Foundations | Visualisation Basics data-foundations-visualisation-basics Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Data reasoning, definitions, and reliability | - | - | Practice assessment | Template + rubric |
| Foundations | Quality And Meaning data-foundations-quality-and-meaning Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Identify quality risks and define what 'good' means with thresholds and actions. | quality | Other: Quality and trust | Practice assessment | Template + rubric |
| Foundations | Lifecycle And Flow data-foundations-lifecycle-and-flow Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Explain data lifecycle and flow to prevent silent breakage and confusion. | monitoring | Other: Lineage and lifecycle | Practice assessment | Template + rubric |
| Foundations | Roles And Responsibilities data-foundations-roles-and-responsibilities Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Assign ownership and responsibilities to keep data reliable and accountable. | governance | Other: Ownership and stewardship | Practice assessment | Template + rubric |
| Foundations | Ethics And Trust data-foundations-ethics-and-trust Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Handle privacy, bias, and trust risks with clear classification and minimisation. | privacy | Other: Ethics and privacy | Practice assessment | Template + rubric |
| Summary | Recap data-summary-recap Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Recap the core ideas: definitions, quality, ownership, and why trust matters. | contracts, quality | Other: Consolidation and recall | Formative checkpoints | Template + rubric |
| Summary | Scenarios data-summary-scenarios Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Practise scenario judgement on quality failures, governance trade-offs, and reliability. | quality, governance, monitoring | Other: Scenario judgement | Formative checkpoints | Template + rubric |
| Summary | Games And Labs data-summary-games-and-labs Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Reinforce patterns using small labs and drills that create evidence. | evidence | Other: Practice and evidence | Formative checkpoints | Template + rubric |
| Summary | Connections data-summary-connections Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Connect data decisions to adjacent areas (security, architecture, AI) with correct trade-offs. | tradeoffs | Other: Cross-domain reasoning | Formative checkpoints | Template + rubric |
| Summary | Next Steps data-summary-next-steps Anchors: ISO/IEC 11179 metadata registry, ISO/IEC 27701 privacy information management, ICO data protection principles and UK GDPR guidance, GOV.UK Data Quality Issues Framework | Set a next-steps plan that keeps improvements practical and auditable. | governance | Other: Next steps and operating model | Formative checkpoints | Template + rubric |