Great Expectations

Adding #dataquality testing to your pipeline is essential to fully trust your data. When you’re ready to make it happen, here’s how GX supports you 👉 hubs.li/Q0325LxW0

Dial in on your data’s distribution, and you can catch bad data before it has a chance to cause problems. Here’s the latest in our series on different dimensions of #dataquality ➡️ hubs.li/Q031XDfW0

The complete Q&A from our “Top data quality tactics…” webinar is now available on the blog! Read it here ➡️ hubs.li/Q031VfqP0

⚡Detect changes to your data’s schema faster and easier in GX Cloud! Here’s how our auto-generated Expectations accelerate your schema monitoring: hubs.li/Q0306tlQ0

Get data quality monitoring that’s actionable 🎬& informative ℹ️: download our beginner’s guide to data quality tests and learn how to get started! 👉hubs.li/Q02_RJy20

Custom SQL Expectations, dynamic parameters, MS Teams notifications, and more: catch up on what’s new in the GX platform in our latest product update ➡️hubs.li/Q02_1mGg0

New case study alert! 🚨See how GX Cloud helps a small data team keep its #dataquality under control with proactive testing and information-rich alerts—so THINKMD can support healthcare workers in underserved communities: hubs.li/Q02-fRXg0

Knowing that you have data quality issues isn’t enough. With limited time and resources, you need to be able to triage what’s going on and then act. Here are 5 tests that help you do that: hubs.li/Q02Z5M2R0 #dataquality #dataengineering

Expressive Expectations, example ♾️: use conditions to include (or exclude!) just a subset of your data from a particular Expectation. It’s super simple to get started: hubs.li/Q02Zd-x80 #dataquality #dataengineering

❄️ Our December workshop schedule has been posted and you can sign up today! Join us for Getting started with GX Cloud and Databricks SQL, Tuesday, Dec 3 9am PT 🌟 Register: hubs.li/Q02Zfn4q0

Our new article has four keys to building a great data quality process that produces great results. Give it a read! hubs.li/Q02YgG620 #dataquality #dataqualitytests #datateams

Do you need data validation that can handle those tricky exceptions and exclusions? Try out Expectation conditions! 👉 hubs.li/Q02Zf1100 #dataquality #dataengineering

How can you catch data that’s not unique enough and that’s too unique, all in a single test? There’s an Expectation for that. Learn about it (and 4 other great ones) here: hubs.li/Q02Z62Pk0 #dataquality #dataengineering

Good data starts with a good data quality process. Read our new article to learn how to build one at your company. hubs.li/Q02YgCLk0 #dataquality #dataqualitytests #datateams

Our SVP of engineering, Lawrence Bruhmuller, was featured on the Engineering Leadership Podcast discussing hiring best practices, ensuring candidates maintain your org’s engineering culture, and more. Give it a listen! hubs.li/Q02XChHN0

Check out the new custom SQL and dynamic parameter features for Expectations in GX Cloud, and build a #dataquality testing process that’s informative and actionable 👉 hubs.li/Q02XpYS80

Our new blog dives into some of the top data quality challenges that we hear about from our customers & community: hubs.li/Q02VmC1c0 #dataquality #dataanalyst #GXCloud

Don’t be snowed under by data volume issues—GX Cloud can help! The third entry in our series on the dimensions of #dataquality is here 👉 hubs.li/Q02W2bpc0

Some data issues are hard to miss. But when they’re more subtle or occur upstream and out of sight, they can be more insidious. More in our new article: hubs.li/Q02Vn6XJ0 #dataquality #dataanalyst #GXCloud

Our new article has 4 expert tips for deploying bare-bones data quality that puts you in a good position for later—and explains how GX Cloud can help: hubs.li/Q02TycQg0 #dataquality #SaaS #datateams