Data

Build data expertise from first principles through formats, quality, pipelines, governance, modelling, uncertainty, architecture, and executive-grade strategy.

This is one ordered route for leaders and technical specialists: start with what data means, then work through representation, quality, privacy, interoperability, analytics, platforms, product thinking, and governance. By the end, you should be able to explain where data breaks down, what governance requires, and how to make a data system defensible.

26 hours7 stages, 52 modulesBeginners welcomeFree, no account
Start with Module 1
Analytics dashboard - photo by Carlos Muza on Unsplash

What you will learn

  • Define what a record is, how it is encoded, and what makes a value mean the same thing to two people
  • Model the same business fact three ways and say which questions each model answers cheaply
  • Read and reason about pipelines, orchestration, streaming and the lakehouse as an operating estate
  • Judge what feeding data to AI systems changes about quality, provenance, retrieval and semantics
  • Apply UK and EU data protection, anonymisation and security duties to a described processing activity
  • Choose a data operating model and argue the value of data to a board without the oil metaphor

Single learning path

  • Senior leaders, technical managers, data practitioners, engineers, analysts, and architects who need one shared path from first principles to expert data judgement
  • Professionals accountable for data strategy, governance, platforms, analytics, AI readiness, and regulatory trust
  • Technical specialists who want deeper foundations across data management, statistics, interoperability, architecture, and executive decision-making

Prerequisites: None. Course starts from everyday examples and builds up.

The Data course as one arc, from literacy up to strategy

Each stage hands the next something usable, meanings you can trust, then models you can query, then pipelines you can operate, so the gate at the end tests judgement assembled across all six rather than the stage read most recently.

The Data course runs as one arc from record to strategic asset: each stage hands the next something usable, and the exam gate certifies the judgement rather than the recall. Security, quality and governance are not a stage; they run under all six.

The data course arc: from record to strategic asset Three regions. A serpentine spine of six stage cards: row one reads left to right as Foundations, Modelling and statistics, Engineering and platforms; row two reads right to left as Data and AI, Privacy and protection, Governance and strategy. Red arrows carry handover pills reading meanings you can trust, models you can query, pipelines you can operate, AI you can feed, and data you can defend. A last arrow, judgement you can certify, drops into the exam and certification gate at the bottom left, tinted red, which sends a pass route to a certificate and a resit route back to the weakest stage. A grey band under everything carries three chips: security, quality and governance. THE DATA COURSE ARC · SIX STAGES THEN ONE GATE STAGE 1Foundationsmeaning before machinesSTAGE 2Modelling andstatisticsshape then uncertaintySTAGE 3Engineering andplatformspipelines that surviveSTAGE 4Data and AIfeed the modelSTAGE 5Privacy andprotectionprotect the personSTAGE 6Governance andstrategydecide who answers meanings youcan trustmodels youcan querypipelines youcan operateAI you canfeeddata you candefendjudgement youcan certify GATEExam and certificationJudgement from all six stages is tested once.Two routes leave this gate.Certificate issuedReturn to the weakest stage passresit Security, quality and governance run under every stageSecurityQualityGovernance

Course curriculum

Read the modules in order on the first pass. Use the practice and stage tests when you want a stricter check on what stuck.

1

Stage 1. Foundations

12 modules · 5.75 hours

1What data is30 min2Data, information, knowledge15 min3Units, notation and binary30 min4Representation and formats30 min5Metadata and context30 min6Standards and interoperability30 min7Data quality and meaning30 min8Lifecycle and flow30 min9Visualisation basics30 min10Ethics and trust30 min11Foundations: stage summary30 min12Foundations: scenario practice30 minPracticePractice testUntimed
2

Stage 2. Modelling and statistics

9 modules · 4.5 hours

13Modelling basics30 min14Relational and dimensional modelling30 min15Master data and entity resolution30 min16Mathematical foundations30 min17Probability and distributions30 min18Inference and experiments30 min19Advanced analytics and machine learning30 min20Modelling and statistics: stage summary30 min21Modelling and statistics: scenario practice30 min
3

Stage 3. Engineering and platforms

9 modules · 4.5 hours

22Architectures and pipelines30 min23Orchestration and DataOps30 min24Streaming and change data capture30 min25Databases and storage systems30 min26Platforms and the lakehouse30 min27Quality engineering and observability30 min28Data as a product30 min29Engineering and platforms: stage summary30 min30Engineering and platforms: scenario practice30 min
4

Stage 4. Data and AI

7 modules · 3.5 hours

31Data for AI foundations30 min32Retrieval and RAG pipelines30 min33Training data, synthetic data and provenance30 min34Catalogues, lineage and active metadata30 min35Semantic layer and metrics governance30 min36Data and AI: stage summary30 min37Data and AI: scenario practice30 min
5

Stage 5. Privacy and protection

6 modules · 3 hours

38Data protection law30 min39Anonymisation and PETs30 min40Data security essentials30 min41Retention and defensible deletion30 min42Privacy and protection: stage summary30 min43Privacy and protection: scenario practice30 min
6

Stage 6. Governance and strategy

6 modules · 3 hours

44Governance and operating models30 min45Data sharing law and data spaces30 min46Open data, FAIR and public data30 min47Data as a strategic asset30 min48Governance and strategy: stage summary30 min49Governance and strategy: scenario practice30 min
7

Exam and certification

3 modules · 1.75 hours

50Revision guide45 min51Exam practice30 min52Mock exams and certification30 min

Standards and references

This course is aligned to the following standards, frameworks, and certification objectives.

  1. 1DAMA DMBOK 2 (Data Management Body of Knowledge, 2nd Edition)
  2. 2ISO/IEC 11179 metadata registries
  3. 3ISO/IEC 27701:2025 privacy information management
  4. 4ICO data protection principles and UK GDPR guidance
  5. 5ISO 8000 Data quality
  6. 6FAIR principles (used as a guiding lens for sharing and reuse, not a formal standard)
  7. 7GOV.UK Government Data Quality Framework and Data Quality Issues Framework
  8. 8ISO/IEC 9075 SQL standards
  9. 9Data Mesh principles (used as an architectural lens, not a standard)