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Data quality alerts before users ping you
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Guru Mahendran
Data Observability v2 by Metaplane — Intelligent auto-monitoring for your data warehouse
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Automatically track warehouse table volume and freshness, get suggestions for deeper monitoring on your most used data, and understand warehouse spend—with Metaplane's new monitoring platform you can ensure trust in your most critical data in 15 minutes.
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Guru Mahendran
Maker
📌
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 metrics 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...
Dan Wolchonok
Love it! Metaplane is my secret weapon of finding out about issues before anyone else.
Guru Mahendran
Maker
@danwolch Metaplane couldn't be great without amazing customers like you and the team at Reforge!
Thomson Nguyen
Congrats on the launch!
Guru Mahendran
Maker
@itsthomson thanks for your support!
André J
What does your typical user look like? We use google analytics for observability atm. But trying to learn more of what's out there. We have about 100 data points to track and expect 11m users in a year. With about 50 interactions per user per day.
Guru Mahendran
Maker
@sentry_co Great question André — any team that stores data in a warehouse like Snowflake/BigQuery/Redshift/Clickhouse/Databricks or even Postgres/MySQL + relies on that data to be accurate will find that they run into frequent data quality issues. These issues could be due to upstream jobs failing silently, engineers making changes without telling you, or input errors, for example. The way you'd find out about these types of issues is that a stakeholder/executive looking at a Tableau dashboard sees a number they don't expect, and pings you (the data team) about it. Most of our customers use Google Analytics for web analytics, but have that data piped into a warehouse like Snowflake so that it can be combined with sales, marketing, and product data. We have startups with a single data person as users, all the way up to massive companies like Sotheby's and Bose, who have sprawling data teams.
André J
@gurubavan Right. BigQuery is next step for us. Have not got to that level yet. Thanks for the clarification.
Greg Karelitz
Love it! Metaplane is top-notch.
Gaurav Kotak
Congratulations on the launch. Good work! 'Auto'-anything is great! .... Auto-tracked metrics + automated lineage. Can you elaborate more on how the lineage works differently to the prior version?
Guru Mahendran
Maker
Agreed on auto-anything @gkotak, the less work we have to do, the better :). We now use the auto-identified lineage in order to determine which tables/columns are most used, and suggest the right monitors to be used on them. We want to make sure you always have eyes on the most critical data.
Philipp John
Congrats on the launch! 💯
Guru Mahendran
Maker
Appreciate it @philipp_john!
Johannes Pittgens
Congrats on the launch! 🚀 Super cool to see the spend monitoring for Snowflake as a part of this release. Based on this, do you also give recommendations how I can optimize my cloud spend?
Guru Mahendran
Maker
Great question @johannes_pittgens and definitely where we're being pulled :). Look forward to more on this soon! We currently solve for the most urgent problem: knowing that a spend spike is occurring and having visibility into where that is coming from
Ted Bennett
The first week after this broader release, I was on a call with a customer that found a table being used by a dozen analysts that they didn't know about; a table they weren't keeping track of and monitoring. Metaplane showed them not only exactly what it was being used for but also let them see that the data in that table hadn't been updated in almost 6 months. The data team was immediately able to message the group of analysts on slack to support their use cases/queries. It's major!
Gabriela Lanza
It's been amazing to see the impact the new platform has had on customers. They're more informed than ever about the state of their data, and everyone loves using the new montioring UI, both for its functionality/clarity and for its polish. The team really outdid themselves with this one. Onward and upward!
Matt Cubillos
Thrilled about the launch! Particularly the monitor suggestions. Tailored, smart suggestions based off lineage and usage make setting up a breeze and ensures nothing important goes unnoticed.