Community roundup: October 2023

At this month’s meetup, we: 

• Shared the latest accomplishments of the community

• Got the latest on product updates

• Learned about using GX with SAS Studio from Lavanya Ganesh (SAS)

• Heard about using GX with synthetic data from Miriam Santos (YData)

We had two great speakers this month—check out the recording if you missed it:

Sign up here to join us in November.

Thanks and kudos

Thank you to all of our contributors this month, who put in their own time and effort to make Great Expectations better!

This month, our featured contributors are:

• A new Expectation, expect_multicolumn_sum_values_to_be_equal_to_single_column, is now available for Spark, Pandas, and SQLAlchemy courtesy of calvingdu.

• GX now allows you to separate out

  unexpected_index_list
  values from other
  unexpected_values
  , which lets you see which rows failed while minimizing potential PII exposure, thanks to Mouad Moussabbih.

The GX Slack community has more than 11,000 members, and our Slack supporters are a cornerstone of that community. Kudos to the top Slack supporters this month:

Roadmap update

Recent work on the GX platform has included:

• Cleaning up the codebase

• Renaming the default directory for file-backed projects to prevent namespace collisions with the package

• Adding a new overview page for Data Assets in GX Cloud, with descriptive column metrics

• GX Cloud also got a new way to generate missingness-centered Expectations automatically

Coming up next are several updates to GX Cloud, including splitting and batching and Expectation history!

Great Expectations unleashed in SAS Studio

Lavanya Ganesh, at SAS Studio, gave a great talk about how SAS Studio uses GX to automate data quality:

In addition to a live demo, Lavanya also shared some of the upcoming plans SAS has for this product as well as links to their GitHub repo for their open source integrations.

Creating synthetic data that meets Expectations

Miriam Santos, a data science advocate at YData, delivered a excellent explanation of how pairing GX’s data quality with YData-generated synthetic data can augment your datasets to get better machine learning outcomes:

YData has a community event coming up next week, so if this topic piqued your interest then check it out! And don’t miss the blog about this that Miriam wrote with Haebichan Jung, a senior developer advocate at GX. 

Additional updates

• Next month, we’re meeting on Tuesday, November 21 at noon ET: get your invite here.

• Check out our exploration of the Execution Engine on the blog.

• We’re hiring in product and engineering! Check out our open roles.

Have you done something cool with Great Expectations that you'd like to share? If you're interested in demoing or have a piece of data quality content that you'd like us to feature, DM @Mollie Pettit on our Slack.