Learn the craft behind
AI-ready data
A free, open knowledge base for the people who build and govern modern data platforms. Five learning tracks — from data governance to agentic AI — each covering what it is, how to do it, industry best practice, hands-on labs, career paths and a skill matrix. Written for developers, business analysts and the leaders who guide them.
Great platforms need fluent people
Tools change every quarter; the fundamentals compound for a career. The Data Academy teaches the durable concepts and the current practice side by side, so your team can reason from first principles and ship with today's stack.
Concept-first
Every track starts from what it is and why it matters — the mental model before the tool.
Learning-outcome driven
Each page opens with what you'll be able to do by the end — not just what you'll read.
Hands-on for both sides
Parallel labs for developers and business analysts — real exercises, real tools.
Career & skills mapped
A ladder from entry to leadership plus a beginner-to-advanced skill matrix for every track.
Seven tracks, one learning path
Follow them in order for a full grounding in the modern data-to-AI stack, or jump straight to the one you need. Each is a self-contained wiki you can bookmark and return to.
Data Governance
Policies, metadata, catalogues, lineage, quality, stewardship and compliance — the foundation that makes data trustworthy and AI safe.
Start the trackSemantic Modelling
The semantic layer, metrics, ontologies and knowledge graphs — one shared meaning of your data for consistent BI and grounded AI.
Start the trackData Modelling
Conceptual to physical, normalisation, dimensional design, Data Vault and the medallion architecture — structure data for meaning and speed.
Start the trackData Integration
ETL vs ELT, batch and streaming, CDC, orchestration and the lakehouse — move and unify data reliably from every source.
Start the trackAgentic AI
AI agents that reason, plan and act — tools, memory, RAG, MCP and multi-agent orchestration, grounded on governed enterprise data.
Start the trackSee it in the platform
Everything you learn here, SCIKIQ automates — governance, semantics, modelling, integration and agents in one unified data platform.
Explore SCIKIQData Security, Privacy & Compliance
Classification, personal-data discovery, entitlement, masking, residency, retention and purpose limitation — mapped to what GDPR, DPDP, HIPAA, PCI DSS and BCBS 239 actually require of data.
Start the trackAI Governance
Use-case register, risk tiering, data provenance, evaluation, human oversight, monitoring and rollback — the controls that get an AI system out of the pilot and keep it there.
Start the trackBeyond the five tracks
Standalone modules on the business side of the same problem — the models your governed data is ultimately built to serve. Take them in any order; they assume no data background.
Enterprise Value Tree
How value decomposes into profit and cash efficiency, revenue into price and quantity, and where STP, 3C and 4P attach — then how to instrument every node as a governed metric.
Start the moduleMetric Dictionary
Formula, worked example, source system and common mistakes for 58 business metrics — finance, pricing, supply chain, customer, workforce and data.
Open the dictionaryCash Release Calculator
Six inputs, and you see how much cash is trapped in your cash conversion cycle and what a single day of DSO is worth. Runs in the browser.
Run the calculatorData & AI Readiness
Twelve questions across connect, define, govern and activate. Instant score, a band, and the specific next step for where you actually are.
Score yourselfEvaluating a platform
The buyer’s guide: which category of platform your problem needs, 30 questions worth asking, a scoring sheet, the proof to demand and the red flags.
Read the guideGlossary
Every term used across the Academy in one A–Z — business metrics, modelling, governance and AI — with links to the full definitions.
Browse the glossarySystem Dictionary
{{SYSTEMS_N}} enterprise systems — ERP, CRM, MES, WMS, TMS, core banking, EMR and more: what each holds, the records inside it, how the data comes out and which joins silently return nothing.
Open the dictionaryEntity Dictionary
The {{ENTITIES_N}} records every enterprise holds more than once — customer, supplier, item, asset, patient — with the match keys that work, the survivorship rules, and the metrics each one breaks.
Open the dictionaryThe value tree, sector by sector
Same structure, different drivers — and different systems holding them. {{VT_N}} sectors, each naming the six systems that matter in it, the records the tree depends on, and where value leaks between two of them.
Checklists for the people who own the numbers
{{ROLE_N}} checklists. Five numbers you should be able to defend, six questions to ask your own team, a 90-day plan that finishes something, and the systems each figure comes from.
Selling data and AI
The rest of the Academy teaches the buyer. These modules teach the people who have to find them, open the conversation and build a case that survives the room they are not in — on exactly the same definitions.
Three doors into every track
The same knowledge, framed for how you work. Pick your lane on any page — the concepts stay shared, the exercises get specific.
Build it hands-on
- Runnable labs with real tools — dbt, Airflow, Neo4j, LangGraph
- Code snippets and reference architectures
- Patterns you can lift straight into production
Translate & define
- Glossaries, metric definitions and source-to-target mapping
- Data-quality rules, scorecards and requirements
- Facilitation, RACI and stakeholder alignment
Set direction
- Operating models, frameworks and maturity paths
- Best practices and 2026 trends to plan against
- Skill matrices to build and hire your team
Want this knowledge running as a platform, not a project?
SCIKIQ turns these disciplines into one governed, AI-ready data foundation — in weeks, not multi-year programmes.