Webinar: The FITT Way To Data Products: A New Data Architecture For A Product-Centric World

This webinar unveils the battle-tested FITT (Functional, Idempotent, Tested, Two-stage) data architecture that eliminates endemic burnout, constant firefighting, and hero-driven development that keeps engineers trapped in operational chaos.

Written by Chris Bergh on October 14, 2025

DataOps DataOps Engineering On-Demand Webinar

Webinar: The FITT Way To Data Products: A New Data Architecture For A Product-Centric World

Key points

A data product is a how, not a what. Chris Bergh's objection to the component-list debate is that a product is defined by iterative delivery of value to a customer, measured in cycle time and deployment success — not by an agreed list of parts.
FITT stands for functional, idempotent, tested, and two-stage, and none of the four ideas is new. DataKitchen has run customer delivery on it for over a decade; the point of naming it is to make it easy to copy.
Idempotency's real payoff is psychological. If a rerun always produces the same result, recovery is trivial: rerun after a break, rerun to backfill, rerun on yesterday's data to try a new feature.
Two-stage means the whole thing is built from immutable raw data to final deliverables in one pass, so anything in between can be thrown away. A sub-terabyte full build takes about two hours and ten or twelve dollars, which is money well spent.
SQL is neither functional nor idempotent, so the unit of work is a FITT chunk: create new then replace, cleanup at both ends, tests always inside. A build is just a set of chunks run together, and you can iterate on one chunk without rebuilding the pipeline.
There is no dev and no prod, only parameters — git branch, data version, credentials, infrastructure, historic test results. A canary, an A/B production environment, or running a customer's change in parallel for two weeks is a parameter change.

Transform Your Data Engineer Team from Firefighters to Data Product Builders

Shift your data-architecture-focused thinking to a data-engineering-productivity-focused design. FITT democratizes system ownership, enables junior developers to contribute confidently, and allows senior engineers to concentrate on high-value business logic rather than troubleshooting mysterious failures. Learn why data product teams and their data engineers report their systems becoming “too quiet” (and their customers too happy!)—and why that’s exactly what sustainable, scalable data product development looks like.

Stop Fighting Your Data Architecture and Start Building Products That Scale

Are you tired of 3 AM alerts because your medallion architecture’s bronze data doesn’t match the gold layer? Fed up with spending entire weekends debugging why your pipeline worked yesterday but mysteriously fails today? This webinar unveils the battle-tested FITT (Functional, Idempotent, Tested, Two-stage) data architecture that eliminates endemic burnout, constant firefighting, and hero-driven development that keeps engineers trapped in operational chaos.

Master the FITT Principles That Make Data Engineering “Boring” in the Best Way

You’ll learn how to implement functional transformations that produce consistent results every time, build idempotent pipelines where recovery is simple (“Pipeline broke? Just re-run it”), develop comprehensive testing frameworks that identify issues during development instead of in production, and design straightforward two-stage architectures that remove unnecessary complexity from bronze-silver-gold layers.

Get Practical Implementation Techniques That Work in Your Current Stack

Beyond theory, you’ll learn specific SQL and ELT strategies, including Functional-Idempotent (FI) chunks that work with modern tools like dbt, Snowflake, and BigQuery. Understand the “complete rebuild from raw” pattern, master parameterization techniques for real environment parity, and apply improved Write-Audit-Publish patterns that ensure reliable data quality without extra operational effort