CL-225 Cloud & Platform

Analytics Engineering with dbt

Build an analytics codebase that behaves like software rather than a folder of scripts: models with a real dependency graph, materialisations chosen for cost and freshness, and tests that fail a pull request before a dashboard tells someone the wrong number. Learners construct a layered dbt project over raw sources, add freshness and assertion tests, snapshot a slowly changing dimension, and wire CI that builds only what changed.

B3Practitioner

6modules

42skill atoms

2role journeys

Curriculum

What this course covers.

6 modules, 42 named skill atoms. Expand any module to see them.

1Models, Refs and the DAG7 skill atoms

SQL models compiled into the target warehouseref and source building the dependency graphstaging, intermediate and mart layersproject structure and naming conventionsgraph operators and node selectorscircular dependency and orphan model detectioncompiled SQL as the debugging artefact

2Materialisations and Cost7 skill atoms

view vs table trade-offsincremental models and is_incremental blocksunique_key and merge behaviourfull refresh triggers and their costephemeral models inlined as CTEslate-arriving data breaking an incremental windowwarehouse-specific incremental strategies

3Sources, Freshness and Seeds7 skill atoms

declaring sources over raw tablesfreshness with warn_after and error_aftersource tests as the first quality gateseeds for small reference datachoosing the loaded_at_fielda stale source stopping a run before it spreadssource ownership recorded in the project

4Tests and Assertions7 skill atoms

unique, not_null, accepted_values and relationshipssingular tests as SQL returning zero rowsdbt-utils and dbt-expectations packageswarn against error severity thresholdsstore_failures for triagetest coverage tracked per modeltests that only assert the obvious

5Snapshots, Macros and Packages7 skill atoms

snapshots for type 2 slowly changing dimensionstimestamp vs check strategyJinja macros for repeated SQLcustom generic tests written as macrospackages.yml with pinned versionsdispatch for cross-warehouse macrosmacro overuse making SQL unreadable

6Documentation, Lineage and CI7 skill atoms

schema.yml model and column descriptionsdbt docs generate and the lineage graphexposures linking models to dashboardsslim CI with state:modified plus childrendeferring to the production manifestpull request builds limited to changed modelsmanifest and run_results consumed by observability

Where it fits

CL-225 in the role journeys.

This course appears in 2 of our 45 role journeys. Here is what a learner takes immediately before and after it in each.

Data Engineer

Practitioner stage

CL-224→CL-225→CL-228

Data / BI Analyst

Practitioner stage

CL-226→CL-225→AI-112

Roles this course serves

Data / BI Analyst Data Engineer

The capability ladder

This course is authored to band B3.

Every course we run is written to one rung of the CASI ladder, so a plan can be assembled to take a team from where they are to where they need to be.

What do B1–B6 mean?The CASI Capability Ladder — click to expand

Every course targets a band on the CASI Capability Ladder — our six-band proficiency scale, anchored to open standards (O*NET, ESCO, NICE, NIST AI RMF, Bloom's). A band tells you how deep a course goes, and what evidence proves it.

What the learner can doTypical evidence

AwareUnderstands concepts and vocabulary; uses tools with guidance

Knowledge checks

FoundationPerforms standard tasks correctly in familiar contexts

Guided labs, autograded exercises

PractitionerDelivers complete pieces of work independently

Scenario labs, proctored hands-on exams

ProfessionalHandles production-grade complexity, trade-offs and failure modes

Break-fix drills, design defenses

AdvancedEngineers systems end-to-end under constraints; leads others

Rubric-scored capstones, vivas

ExpertSets direction; recognised authority across teams

Portfolio + panel evaluation

A note on B6. Courses in this catalog target B1–B5. B6 is not taught — it is recognised, through a portfolio and a panel, once someone is setting direction for others. Every journey here is built to land a learner at B5.

Other Cloud courses at this level.

CL-107

Run CL-225 for your team.

This course runs at several lengths depending on how deep you need to go and how much of it your people already have. Tell us who is being trained and we will scope it.

Add it to a training plan Talk to our team Check your team’s level free

Analytics Engineering with dbt

What this course covers.

CL-225 in the role journeys.

Data Engineer

Data / BI Analyst

Roles this course serves

This course is authored to band B3.

Other Cloud courses at this level.

PostgreSQL for Cloud Engineers

Serverless Engineering on AWS (Lambda · DynamoDB)

Snowflake Core Engineering

Enterprise BI with Power BI & Tableau

Workflow Orchestration with Airflow

Kubernetes Administration

Run CL-225 for your team.