Semantic Layer Implementation for Your Business
Semantic layer implementation defines your key metrics once, in code, so Revenue and Active User mean the same thing in every dashboard, spreadsheet and AI query. Omeiro engineers the layer in Cube.js or the dbt Semantic Layer and connects your BI tools to it.
What semantic layer implementation looks at
The main areas we work through. The exact scope depends on your package and is agreed before we start.
The question
- What to predict
- How it will be used
- What good enough means
Data prep
- Missing values
- Outliers
- Features
Model
- Simple baseline first
- Honest test results
- Limits explained
Use
- Export or API
- Refresh plan
- Watching for drift
What we cover The exact scope depends on your package and your data, and is agreed before work starts.
What you get with semantic layer implementation
Universal enterprise metrics definition. Engineering Cube.js and dbt Semantic Layers ensuring every dashboard and AI query defines 'Revenue' and 'Active User' identically.
Basic Package
10 core metrics defined in dbt Semantic Layer or Cube. 4-day delivery, 2 revisions.
Standard Package
30 metrics, 5 entities, BI tool connection, metric docs. 8-day delivery, 2 revisions.
Premium Package
60 metrics, caching, access rules, AI/BI query layer; 30 days support. 14-day delivery, 2 revisions.
Clear brief first
We confirm what you need before work starts, so the scope is clear on both sides.
Revisions listed
Each package shows its revision rounds. A round is one list of changes sent together.
Yours once paid
Copyright of the final work passes to you once the order is paid in full.
Your data stays in your own accounts and tools wherever possible, and access is removed when the work is done.
How our semantic layer implementation works
Inventory the metrics
We collect current definitions and find conflicts.
Agree the definitions
Each metric gets one written formula.
Build the layer
Metrics and entities are coded in dbt or Cube.
Connect and document
BI tools are linked, with docs explaining each metric.
Semantic layer implementation: one definition per metric
A semantic layer implementation starts with a metrics glossary. Gather the numbers executives argue about, such as revenue, active users and churn, and write the single definition each should have. Share your warehouse, your dbt project if one exists and the BI tools in use. Disagreements found at this stage are the point of the project, so involve finance and product owners in the sign-off.
A common mistake is encoding metrics inside each dashboard, so three tools show three answers. A semantic layer implementation here puts metric logic in one place, in dbt or Cube, with entities, dimensions and access rules, and connects BI tools to it. Documentation lists each metric, its definition and its owner. On the top tier the same layer serves AI query tools, so natural-language questions use approved definitions.
In short
- Delivery in 4 to 14 days, by package.
- Fixed price, shown before you order.
- Analytics leads fielding questions about why numbers differ across tools.
- Data teams evaluating cube js consulting for a headless BI setup.
- Copyright yours after full payment.
Semantic Layer Implementation: common questions
How much does semantic layer implementation cost?
Prices are fixed and shown by package on our Semantic Layer Implementation pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does cube js consulting take?
Delivery depends on the package: Basic 4-day delivery; Standard 8-day delivery; Premium 14-day delivery.
What is included in the Basic Package?
The Basic Package includes: 10 core metrics defined in dbt Semantic Layer or Cube. Higher packages add more scope, revisions and support.
Can I get a custom metrics layer setup package?
Yes. If none of the packages fits, use the custom package form on our pricing page to describe what you need, and our team sends you a fixed price.
dbt Semantic Layer or Cube, which is better?
If you already use dbt, its semantic layer is a natural fit. Cube suits teams wanting a flexible API layer.
Do I need a warehouse first?
Yes, the layer sits on top of one.
How does it help AI queries?
Premium builds a layer that AI tools can query using your defined metrics instead of guessing.
Which BI tools connect?
Standard connects one BI tool. Tell us yours before ordering.
What is a metrics layer?
A metrics layer is a shared place where business measures are defined once and served to every tool. Dashboards, notebooks and AI assistants then pull the same numbers.
Who owns the final work?
Copyright of the final work passes to you once the order is paid in full. Paid fonts, stock files or licences, if used, are licensed in your name.
Ready to start your semantic layer implementation?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.