A Live Data Analytics Course built for the AI era
You won't just learn to query data. You'll learn to build the stack that produces it.
Six live sessions covering BigQuery, dbt, and Looker Studio: the full Modern Data Stack.
₱5,000 per seat · introductory pricing · application is free
Revenue
$48.2K
↑ 8.4%
Users
12,384
↑ 3.1%
Sessions
98.2K
↑ 14.2%
Monthly Revenue
What you'll build
Not exercises. Real artifacts built on real tools, using real data. Yours to keep, share, and build on.
01
A working dbt project
Staging, intermediate, and reporting models built on the Olist e-commerce dataset in BigQuery, structured the way real analytics engineering teams work.
02
A Looker Studio dashboard
Connected directly to your own BigQuery models. Not a template, not a sample. Your data, your design, your story.
03
A merged GitHub PR
A real pull request reviewed and merged into the shared dataready-warehouse repository. You will have done the full git workflow: branch, commit, push, review.
04
A capstone presentation
A 5-minute live presentation to peers and the instructor. You pick the business question, you define the metrics, you present the answer.
05
A written data document
A structured written summary of your findings, in the format analysts use to communicate async with stakeholders who weren't in the room.
6 sessions. 3 weeks.
Every session builds on one shared dataset and one evolving project.
Week 1
Understanding the Landscape
Session 1
What Is This Job, Actually?
The analytics team, roles, and what a real day looks like. First queries against the Olist dataset in BigQuery. Preview of the final project.
Session 2
From Raw Data to Something Trustworthy
Why raw data can't be used directly for reporting. The warehouse mental model: staging, intermediate, marts. Writing and running your first dbt model.
Week 2
Building and Communicating
Session 3
Making It Visible
Connect your dbt models to Looker Studio. What makes a dashboard good vs. noisy. Build a dashboard a non-analyst can actually use.
Session 4
The Stuff Nobody Teaches You
Stakeholder management, asking the right questions before building, writing up findings for async communication, and the most common junior analyst mistakes.
Week 3
Shipping and Presenting
Session 5
How Teams Work on the Same Code
The one git workflow analysts actually use on the job: branch, commit, push, PR, review. You will open and merge a real PR against the shared repo.
Session 6
Ship It
Capstone presentations to peers and the instructor. How to write a resume bullet and a LinkedIn post from the project you just built.
How it runs
Designed around how analysts actually learn and what teams actually hire for.
6 live sessions, 90 min each
Two sessions per week over 3 weeks. Real-time instruction, not recorded lectures. Two optional 45-minute drop-in Q&A hours run between the main sessions for when you get stuck.
Maximum 10 students
Small by design. You get actual feedback on your work, not a forum reply. Every cohort has a dedicated Discord channel for async Q&A, homework feedback, and peer support.
The real stack, from day one
BigQuery, dbt Cloud, Looker Studio, and GitHub. No toy environments, no made-up datasets. You work on the same tools used in modern analytics teams, on real e-commerce data.
Who this is for
You're a good fit if you
- Work in an analytical or operational role: finance, marketing, operations, or similar
- Have some exposure to data or numbers in your day-to-day work
- Are comfortable learning independently when given the right resources
- Want to transition into a data analyst role and need real project experience to do it
You're not ready yet if you
Have never written a SQL query
Complete the free SQL track at learndataready.byconol.com first. It covers everything you need.
Have never opened a terminal or command line
You don't need to be a developer, but you should be able to navigate folders and run a command.
Expect to be walked through every step without exploring on your own
This is a guided course, not a tutorial. Independent effort is expected between sessions.
Cedric Conol
linkedin.com/in/conolcedricCedric is a Senior Data Analyst with 9 years of experience at Remote, HPE, DXC Technology, and Lamudi, where he led analytics teams and owned dashboards used by senior leadership. He has also mentored data science students at Eskwelabs. He built DataReady to teach analytics the way it's actually done on the job.
per cohort seat
- 6 live sessions over 3 weeks
- Access to the shared dataready-warehouse BigQuery project
- Dedicated Discord channel for your cohort
- 2 optional drop-in Q&A sessions
- Instructor feedback on every homework and your capstone
Payment secures your seat. Limited to 10 students per cohort.
Ready to build something real?
The July cohort is now open. 10 spots available.