Today we're releasing Data Test Previews — a way to give busy data teams a hand by automatically testing any changes made to their data in a development branch. Data teams can find out if they’re about to introduce breaking data changes to their environment in minutes, rather than hours.
In modern companies, the data team acts as a switchboard operator for critical business insights, helping the marketing, sales, finance, product (and other) teams make smarter decisions. But data practitioners don’t just operate the switchboard — they’re building the switchboard themselves, out of tools and systems they’ve often cobbled together over time.
Despite the explosion of tools in the marketplace, data practitioners have long been underserved when it comes to being able to use engineering best practices, such as automatic CI checks that give data teams confidence when merging their code. Such confidence is important, because — as many data practitioners know — making code changes to data models can result in any number of data quality issues. Downstream models can break. Dashboards can look funky. Bugs can be inadvertently introduced in transformation logic, wreaking havoc on your metrics.
Imagine that the CMO of Howl’s Moving Castles wanted a slightly different report for her dashboard, necessitating an adjustment to how the marketing model is transformed — and she needs it soon. How can the data team understand not just how that change will impact their data’s dependencies, but how it will impact the data itself? And how can the data team confirm they’re not introducing breaking changes into their data in seconds, rather than hours or days?