A clear breakdown of what Brainforge fixes, how fast, and what it actually delivers.
dbt implementation
Project structure, CI/CD for models, testing, and documentation so dbt is safe to adopt across the team.
dbt consulting that turns raw warehouse tables into tested business entities
dbt is the modern way to model data, but it only pays off when the transformation layer is governed. Brainforge sets up dbt projects, builds tested business entities and marts, wires semantic layers, and migrates legacy SQL so analysts and agents query the same definitions.
In plain terms
What dbt means in practice
Where teams get stuck
dbt implementation, analytics engineering, semantic layers, and legacy migration support.
Our SQL models live in notebooks and dashboards, not in a governed transformation layer.
We started dbt but the project has no structure, tests, or documentation.
Metrics disagree between dashboards because definitions live in each tool.
Our analytics engineers are drowning in maintenance instead of building.
What we deliver
Core dbt
Analytics engineering
Business entities, marts, and metric definitions that make BI and AI agree on what numbers mean.
Semantic layer setup
dbt semantic layer or alternatives wired to BI and AI tools with governed metric definitions.
How deep it goes
Capabilities behind the work
The same delivery primitives (context, controls, and review) show up across every engagement.
dbt project setup
Project structure, naming, packages, CI, and testing so dbt scales past the first sprint.
Project structureTestingCI/CD for models
Analytics engineering
Business entities, marts, and models that turn raw warehouse data into governed definitions.
Business entitiesMartsMetric definitions
Semantic layer
dbt semantic layer or alternatives connected to BI and AI with one source of metric truth.
Semantic layer setupMetric governanceBI integration
Legacy migration
Move SQL from notebooks, stored procedures, and BI tools into a governed dbt transformation layer.
Migration planningRefactoringValidation
What changes
Outcomes you can point to
- Tested, documented models that survive team changes.
- One set of business definitions behind BI and AI.
- A dbt project analysts trust and extend themselves.
- Faster, safer model changes through CI and lineage.
Proof in production
See where this work shows up.
Common questions
dbt, straight answers
How much does dbt consulting cost?
Most teams start with a scoped sprint that sets up a governed dbt project with tests and documentation, or an audit of an existing project that has grown unstructured. Pricing is fixed-scope per sprint, so you know the cost before work starts.
Do you help with dbt Core or dbt Cloud?
Both. We work with the setup that fits your team and budget, and we are equally comfortable migrating projects between them when you outgrow one.
Can you fix a dbt project another vendor left behind?
Yes. Project rescues are common — we restructure, add tests and lineage, and document the models so your team can own it.
Do you implement dbt semantic layers?
We do, including the dbt semantic layer and warehouse-native alternatives, wired so BI tools and AI agents use the same metric definitions.
How is dbt consulting different from hiring a data engineer?
A hire is open-ended. A consulting sprint delivers a bounded outcome — a governed project, tested models, working semantic layer — with your team enabled to run it after.
How we work
A path from pressure to a working system
01
Audit the transformation layer
We map where models, definitions, and documentation live today, and where they break.
02
Build the governed dbt project
We set up structure, tests, lineage, and semantic readiness so models are trustworthy.
03
Hand it to your team
We enable your analytics engineers to extend the project with confidence and clear review paths.
Our Trusted Partners
We only bring the best of the best
READY TO PUT
dbt to work?
dbt to work?
In one working session we'll name what's broken, what's possible, and the first system worth building.
