Metaplane: Data Observability v2

We're so excited to announce the next evolution in data observability here on PH today!

Metaplane began its journey as an observability tool for data teams who wanted to be the first to know about data quality issues. Hundreds of teams like those at Reforge, Sigma, Sotheby's, and Honeywell use every day to ensure data can be trusted in their organizations. We've stood by our mission to alert data teams before they’re caught off-guard by a broken dashboard or an executive's urgent message.

Today, we’re presenting not just a feature, but what we think is the next evolution in data observability. Traditionally, tools in this space required a significant time investment to determine what should be monitored, and then set up each individual test. We're flipping the script — using inherent usage and lineage data to automatically suggest what should be monitored, while auto-tracking as much table row count and freshness stats as possible, too.

What's exciting now and in the pipeline?

- Auto-tracked metrics like table row counts and freshness, ensuring your data is always up-to-date and accurate. - Suggested monitors that take the guesswork out of what you should be keeping an eye on. - A keen eye on your Snowflake spend, so you always know where your money's going. - And our grand vision: an observability tool where anything that should be monitored will be monitored. While we're sharing a taste of this now, with a lot more coming soon down the pipeline :)

As a technical team, we've always taken a self-serve, ease of setup approach to data observability, but with Metaplane's latest iteration, it's not just easy—it feels magical. We take as much of the work out of monitoring as possible, so that it doesn't have to be a quarterly objective. You can add the world's most powerful data observability to your stack in under an hour.

We've been testing this with our customers for the past couple of weeks and the feedback has been great, but I'm eager to hear from the PH community. Do you run into data quality issues? How do you find out about them today? If you could spend an hour to ensure that your data could be trusted — would you? Let me know what you think!

Read more about this Metaplane launch here: https://www.metaplane.dev/blog/l...