Semantic Layers & Metrics
Start learningBuild a semantic layer
Two teams pull MRR and get two different numbers. Learn to build a semantic layer in Cube, dbt metrics, or Looker, so the business stops fighting about whose definition is right.
Overview
Two teams pull MRR and get two different numbers. Learn to build a semantic layer in Cube, dbt metrics, or Looker, so the business stops fighting about whose definition is right. Octo builds this course around your role, your experience, and what you already know, so the version you get isn't the same one a beginner across the hall is reading.
What you'll learn
By the end, you'll be able to do these, not just have read about them.
Build a metrics layer that BI tools and notebooks share
Apply Cube, dbt metrics, or Looker correctly for your stack
Avoid metric drift across surfaces by design
Operate semantic layers with versioning and governance
Who this is for
You're an analyst, PM, or operator who wants to stop waiting on the data team.
You're an engineer picking up data skills as part of a broader role.
You're a data professional sharpening a specific specialty.
Prerequisites
Working familiarity with the basics of the topic, the kind of thing you'd pick up in a beginner course.
Some real-world reps, even if informal.
Suggested chapters
This is the typical chapter list. Your version is generated against your background and adapts as you go. It may compress, expand, or reorder these.
- 01
Foundations of Semantic Layers & Metrics
The mental model and shared vocabulary you'll lean on for the rest of the course.
- 02
Core building blocks
The handful of moves that show up everywhere, drilled until they feel obvious.
- 03
Working through real examples
Applied patterns on examples close to the kind of work you actually do.
- 04
Edge cases & failure modes
Where the simple version breaks, and how to recognize it before it bites you.
- 05
Putting it together
Combining what you've learned into something end-to-end and defensible.
- 06
Capstone
A small project tied to your real work that proves you can use the material, not just recall it.
Real-world projects
- 01Apply semantic layers & metrics to a small problem from your actual work or studies.
- 02Produce one written or built artifact you can put on your resume, portfolio, or in a review packet.
- 03Run a self-graded capstone against an Octo-provided rubric.
Tools & concepts
Real tools and ideas covered. Octo brings them in when they fit your stack.
- SQL
- Python
- Dashboards
- A/B testing
- Cohorts & funnels
- Statistical reasoning
Where this leads
- 01
Analyst- and DS-grade fluency
- 02
Self-service for product, marketing, and ops decisions
- 03
Foundation for advanced data specialties
Common questions
Is this a fixed course, or is it built for me?
Built for you. The chapter list below is a typical outline. Your actual course is generated against your role, experience, and what you already know, then adapts as you go.
How long does it take?
Most learners finish in 2–6 weeks at a normal pace, depending on the topic. Octo compresses where you're strong and slows down where you're weak.
Is there a fixed schedule or cohort?
No. You start when you start. There's no live session, no calendar, no deadline.
Can I ask questions while I'm learning?
Yes, every module has an AI Sidekick in the margin. Ask for a different example, push back, or get a clarifying analogy without leaving the page.
What do I get at the end?
A verifiable, HMAC-signed certificate with a public verify page. It records the modules passed, scores, and capstone, not just attendance.
How much does it cost?
Octo is in research preview, courses are open. We'll be transparent before pricing changes.
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