Our team had the pleasure of speaking to seven leading data practitioners about their data migration experiences—the good, the bad, and the ugly. Learn about their strategical and technical best practices for faster, less stressful data migrations 👇 get.datafold.com/x-dms-ryan

Every data migration has a hero…or a villain 👀 🏆 We talked to practitioners across the industry to learn from real-world successes (& disasters) in The Data Migration Universe—best practices, hard lessons & a readiness check. get.datafold.com/x-dms

🦸‍♂️ Not all data engineers wear cape, but they should. Migrations are high-stakes, high-risk, & full of villains (👋 misaligned timelines). Enter The Data Migration Universe for real stories, best practices & a readiness check. Are you migration-ready? get.datafold.com/x-dms

Data-driven design… in cookie form! 🖤🍪 Our team's holiday baking activity was the perfect mix of innovation and fun with the Datafold logo as a 3D-printed cookie cutter!

We’ve heard the challenges data teams face—ensuring data integrity amidst scaling pipelines & growing complexity. Today, we’re taking a big step to address those pains. Introducing Monitors in Datafold: Data monitoring that starts upstream. get.datafold.com/monitors-bl…

Ensuring high data quality during data deployment is crucial as it sets the foundation for downstream applications. There are 4 common ways that practitioners have approached data quality testing during this stage. Learn more on how they rank: datafold.com/data-quality-gu…

Getting data testing right is a moving target. Codebases grow in complexity over time, code diffs just don’t show the impact, and there are too many “unknown unknowns” that can’t be accounted for in custom tests.

☎ Calling all friends on GCP: Datafold is now available on Google Cloud Marketplace! datafold.com/blog/datafold-i…

With workflows that make sense, checklists against errors, and an automated data quality system orchestrating everything, sit back and watch your developer velocity increase without sacrificing data quality:

A proactive data quality strategy is governed by 3 key principles: 1. Shifting data testing to the left: Test early and often during the development cycle.

#dbt v1.8 is out with new unit testing for dbt projects! Learn from @glebmm about its benefits over traditional assertion tests, when to use it, & implementation tips. datafold.com/blog/dbt-unit-t…

How does Datafold's Data Diffing differ from your standard dbt tests?

It's been a busy month at Datafold! Check out some of our newest product updates, including: - The new @dremio 🐬 integration in Datafold Cloud - Sampling 👪 for cross-database diffs - Consolidated Impact Preview 👀 datafold.com/changelog?utm_s…

🎉 Big news! Datafold + @dremio are teaming up to supercharge your data workflows! 🎉 🚀 Speed up your move to a modern lakehouse with cross-database diffing 🪴 Enhance your dbt project’s data quality with CI testing 🔗 get.datafold.com/dremio-twit…

Then, head to the Actions tab to check on the workflow's status: Success! ✅

It's January, which means: New Year, New Skills. Join Datafold CEO @glebmm on Feb. 7th at @LindsayMurphy4 's Advanced dbt course where he'll cover #dbt testing best practices 💥 PS — Check the 🧵for a discount code to the course!

Announcing Datafold's new code repository integrations with Azure DevOps + Bitbucket, so you can run automatic data diffs for your dbt code changes—wherever your git repo is hosted. get.datafold.com/ado-bitbuck…

2. Tableau assets that are potentially impacted by your dbt/transformation code changes are now visible in the Datafold CI comment. Never let bad code and data into your prod database—or BI tool—again.

1. Tableau assets are now visible in Datafold Cloud's column-level lineage explorer. From raw source data to BI dashboard—access greater visibility (& granularity) into how your data moves its way through your stack & bring order to your Tableau project.

Heeeey #dbtCoalesce London! Not too late to stop by the Datafold booth to talk all things data quality and data diffing 💥