Financial Crime · Data Architecture
Build the knowledge.
Practise the craft.
A practical learning programme for analysts moving into financial crime data architecture and business analysis. Start with the learning path, then use the modules as a daily reference.
weeks · a guided learning path
modules · foundations to practice
official text references
worked SQL exercises
The programme
Three phases. One craft.
The curriculum forms a 12-week programme at roughly 6 to 8 hours per week. Every module follows the same loop: read the lesson, apply it in the exercise, capture your evidence.
Phase 01
Foundation
Four modules that build the working vocabulary of data architecture: grain and keys, a first financial crime model, eleven worked SQL exercises, and a safe map of the legacy estate.
View modulesPhase 02
Architecture
Five modules connecting platforms into a dependable design: a proposed cloud architecture, daily work in the modern warehouse, identity and effective-date history, data contracts and quality gates, and a migration playbook with rollback.
View modulesPhase 03
Application
Four modules that turn knowledge into professional practice: financial crime governance and control testing, advising stakeholder teams with templates, building and evaluating a knowledge agent, and a reviewed capstone.
View modulesCourse library
Thirteen modules, foundations to practice.
Every module links official text documentation. All labs use fictional data — internal standards and approved platform configurations take precedence over illustrative design choices.
Foundation
Modules 01–04Learn the vocabulary, understand the estate and develop SQL fluency.
Start here: role, 12-week plan and first 30 days
What success looks like, and how to spend your first month.
Data foundations and financial crime modelling
Grain, keys, relationships and a first financial crime model.
SQL workbook: from first query to reconciliation
Eleven worked exercises, from SELECT to null-safe reconciliation.
Hadoop, CDP and Hue: understand the current estate
Name every component, query it safely, inventory what matters.
Architecture
Modules 05–09Connect cloud platforms, model history and plan dependable migrations.
AWS and a proposed financial crime cloud architecture
Where data lives, where it is processed, and who can touch it.
Snowflake: architecture, daily work and platform translation
Core concepts, safe habits and the traps that catch migrations.
GUID, DataHash, DeltaHash and effective-date history
The five questions hidden in the identity and history fields.
Reliable pipelines, data contracts and quality controls
A successful job is not necessarily correct data.
Migration playbook: legacy estate to cloud and Snowflake
Five phases, two tracks, and rollback as a first-class design.
Application
Modules 10–13Assess controls, advise teams and demonstrate your skills.
Financial crime context, governance and control testing
Why data architecture decides who gets assessed at all.
Advising financial crime teams: meetings, requirements and templates
Turn a team's need into a decision others can evaluate.
Knowledge agent: source collection, instructions and evaluation
Build a reference assistant you can actually trust.
Capstone, assessment and reusable daily checklist
Design the product, defend the design, record the evidence.
The 12-week path
A guided learning sequence.
Suggested weekly pattern: two hours reading, three hours exercises, one hour explaining your work to someone, and up to two hours revising. Extend the programme if SQL is entirely new to you.
| Week | Study and practice | Evidence to produce |
|---|---|---|
| 01 | Module 02: systems, tables, grain, keys | Explain one dataset and draw its source-to-consumer flow |
| 02 | Module 03: SELECT, filtering, grouping, NULL | Complete SQL exercises 1 to 4 |
| 03 | Joins, windows, reconciliation; Module 04 estate | Explain and fix a duplicated transaction total |
| 04 | Module 05: cloud architecture and boundaries | Annotated architecture with access boundaries |
| 05 | Module 06: the modern analytics platform | Source-to-target mapping and dialect checklist |
| 06 | Module 07: identifiers, hashes, valid-time history | History timeline and boundary test results |
| 07 | Module 08: pipeline reliability and quality | Data contract and exception report |
| 08 | Module 09: the two migration tracks | Migration wave plan and rollback conditions |
| 09 | Module 10: financial crime controls | Evidence-backed control assessment |
| 10 | Module 11: advising other teams | Architecture decision record and review pack |
| 11 | Module 12: knowledge agent and sources | Approved source collection and evaluation results |
| 12 | Module 13: capstone | Defend the complete design to a colleague |
Your learning desk
Four ways in.
New to the programme? Start at the top. Returning for reference? Jump straight to the workbook, the agent or the capstone.
Free to use · No account needed
Ready when you are. Begin with Module 01.
Role, the 12-week plan and your first 30 days. Read the lesson, apply it in the exercise, then capture your evidence.
Start Module 01