How we handle sensitive data in BigQuery
We take handling sensitive customer data seriously. This blog explains how we manage PII and confidential data in BigQuery through default masking, automated tagging, and strict access controls.
Lambert Le Manh
How we model our data warehouse
Curious about the inner workings of our data warehouse? We’ve shared a lot about our data stack, but this time we’re diving into the design principles behind our warehouse. This blog breaks down how we structure our data, from staging to marts layers, and how we use it all in our BI tool. It’s a quick look into how we keep things flexible, efficient, and built to scale.
Jack Colsey
Data quality testing
Our data observability workflow uses data quality testing to ensure data meets accuracy, consistency, and reliability standards, enabling confident, data-driven decisions. See how we built it, the common challenges we encountered, and the solutions.
Lambert Le Manh
Data stack 2024
It's been nearly 2 years since our last update on our data stack—and we have a lot to share! Read about improvements to our local dev setup, why we switched key platforms, and some other cool things. 👀
Jack Colsey
How our data team handles incidents
Data incidents are just like any other type of incident, and having a well defined data incident management process in place makes it a lot less stressful when things inevitably break. Here's how our team does it.
Navo Das
The Tasty Data Morsel: Data delight as company culture
Feeling hungry? We love to spice up our weekly all-hands meetings with the Tasty Data Morsel: a bite-sized insight covering everything from our sales velocity to the most popular Christmas party dishes. These data treats make numbers not just digestible but downright delicious.
Matilda Hultgren
