Data engineering shouldn't be detective work 🔬. Introducing AI analysis for code review: . ✨ Automated PR summaries .⚡️ Root cause analysis for data diffs .💻 Context-aware chat investigation.

🚀 Data migrations taking forever? AI is changing the game. On the latest Data Engineering Podcast epsiode, @glebmm dives deep into AI-powered automation, LLMs in data workflows, and the future of data engineering. Don't miss it! 🎧👇.

Data migrations are slow, expensive + risky—until now. 🚀 Introducing Automatic End-to-End Data Validation. 🔹 AI-powered code conversion.🔹 100% data parity before go-live, no manual checks needed. Migrate with confidence.

Data migrations have long been painful & manual. ❌ SQL mismatches .❌ Hidden business logic .❌ Endless validation headaches. But AI has caught up. Learn how Datafold’s Migration Agent automates legacy code translation, refactoring & validation. 🔗

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 👇.

So you’ve migrated your data…but can you prove it’s right? ✅. Manual validation is slow & incomplete. In high-stakes migrations, that’s not an option. Learn how to validate like a superhero. 🔗

🚨 "If your migration takes too long, the new platform might become legacy before you finish. A double disaster." – @glebmm . Migrations can make or break a company. Our new guide has best practices, horror stories & a readiness check. Check it out 👇!.

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.

🦸‍♂️ 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?.

What’s worse: comparing non-relational data or comparing data across files? 😥. With Datafold, neither has to be painful. Watch us walk through the new file diffing & MongoDB integration, enabling data teams to automate comparisons—no matter the format.

🚀 NEW FEATURE: Diffing is expanding to files & NoSQL!. 📁 Diff an Excel/CSV/Parquet file against a database table or compare two files. 🍃 Diff MongoDB collections within or across MongoDB. Data quality for every data format! . Learn more 👇.

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!

The modern data stack is here. But migrations are stuck in the past. Here’s why AI can (finally) change that:

In October, we launched Datafold Monitors to help data teams catch and resolve data quality issues faster. Today, we have some big updates to the Datafold Monitor experience: REST API, recovery alerts, failed records CSVs, & more. 💡 Learn more:

🚀 New Datafold x Power BI integration!. Track data lineage &assess impact on Power BI assets with ease. Proactively prevent data quality issues before they reach your dashboards. Learn more 👇.

Data migrations shouldn’t take years. Meet the Datafold Migration Agent: AI-powered translation & validation that works across any SQL dialect, orchestration framework, or GUI platform. Plus, it refines until you reach full parity.

🎙️ New Episode! Datafold's CEO @glebmm dives deep into data migrations with @DataEngPodcast. Hear his insights on:. - Tackling migration pitfalls 🤯.- Achieving data parity 🎯.- Using AI & LLMs for faster migrations 🚀.

Data teams deserve scalable, unified tools. We support:.- CI/CD Testing: Catch issues early with automated testing. - Data Monitoring: Spot anomalies & resolve data quality issues fast. - Migration Automation: AI-powered code conversion & validation.

Monitors are a powerful way to help you automatically track and manage data quality across your stack. From schema changes to anomaly detection, Datafold’s Monitors catch issues before they impact your business.

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.