Building Trustworthy Data Products
The data landed and nobody built anything with it. Define the answer before you query, profile what you were handed, shape it so it reruns identically, prove it before you publish, and own it once people depend on it.
6 modules · 22 lessons · ~6.9 hours · Analysts, domain experts, data stewards, and the engineers who support them
Chapter 5 in the Meridian sequence · 9 live so far · builds on Cloud Modernization Patterns and Modern DevSecOps Foundations · continues in Grounded Answers From Documents
Meridian Utilities finished the migration two years ago. The data landed, reconciled, and cut over clean — and then sat there. The estate got zero-trusted, pipelined, and made deliverable into a federal environment, and in all that time nobody turned the data into a single answer anyone acted on. The people who understand that data are rate analysts, outage planners, and field supervisors, not data engineers. This training is for them: decide what answer is needed and what it means before touching a query, profile what the platform team actually handed you, build a table that returns the same result every time it runs, prove it before anyone sees a number, serve it to the consumer who asked, and own it once people depend on it. Every lesson uses AI CLI tools to do the real work — and every lesson ends by finding what the agent got wrong. No prior Meridian knowledge needed.
The Curriculum
Decide What to Build
Name the answer first
The decision that needs an answer, who consumes it, what the number actually means, and the acceptance test written before the first query
Know What You Were Given
Profile before you promise
What the zones guarantee and what they do not, reading the inherited contract as a consumer, and profiling that finds what the catalog never recorded
Build the Table
Same input, same answer
Joins that hold their grain, derivation that reruns without doubling, and the orchestration that decides whether your build becomes someone else's incident
Prove It
Reconcile, then publish
Reconciliation against something real, tests that run on every load, the review pass that catches what the agent got wrong, and a number you can regenerate
Serve It
Choose by consumer
One primary delivery path chosen by who consumes it, the contract that comes with serving, and getting derived answers out of the boundary
Own It
Keep it true
Service levels somebody is actually paged for, the cost of being right, and the stewardship record that survives you leaving the team
New to AI CLI tools?
This training assumes you can drive an AI CLI (Claude Code, Codex CLI, Antigravity CLI, or Copilot CLI). If that's new, these modules from our AI-Powered Development training are the fastest preparation — most students need only the first one: