The Next Stage of Metaplane
Why is this number weird? Why is the dashboard down? Can I trust this data?
If you’ve been asked these questions before, you’re not alone. Every day, as data teams do the hard work of helping companies succeed, they get cut by a double-edged sword: when data is used in critical paths, the stakes for data quality are raised. Because while there are great tools like Datadog for observing software, there haven’t been good tools for observing data itself.
While it’s hard to predict what data work will look like, I’m confident that in ten years, future data teams will have full visibility into the state of their data. We are building Metaplane towards that future where all organizations can trust their data.
We’re lucky to work with customers that already live in that future. The hundreds of data teams using Metaplane since our launch a bit over a year ago are the first to know of data issues, including the teams at Vendr, Mux, SpotOn, Reforge, and Drift. And in spite of the uncertain economic condition, we’ve been growing month over month with happy customers that have integrated Metaplane into their core data workflows.
Today I’m proud to announce that we’ve raised a $8.4M funding round led by Khosla Ventures to take Metaplane to the next level. We are turning this money into two things: product and growth.
The core Metaplane product addresses the problem of “being the first to know of data issues” by continuously monitoring metadata (like row counts, freshness, distribution of metrics) then alerting on anomalies. Of course, the problem doesn’t stop there. Metaplane also supports triaging issues by using lineage to analyze downstream impact of issues and helping surface upstream root causes. With incidents, Metaplane bundles together related issues, analogous to traces in software observability.
This process of identifying, triaging, and remediating data issues is what we call “incident management”. And we’re laser focused on bringing that to more data teams through expanding our set of integrations, continuing to refine our machine learning models, and perfecting Metaplane workflows.
But the problem of data quality is expansive. While early detection is critical, issues that can be prevented should be prevented. Today, Metaplane customers can access the beta version of our GitHub pull request integration that analyzes how your data would change, and which downstream dependencies would be affected, before you merge code changes. In tandem, we’re investing in upstream, downstream, and transformation integrations that help teams stop issues at the source before they enter the warehouse.
Lastly, data observability expands beyond data quality. Data quality is a problem while data observability is a technology. Our customers already use Metaplane monitoring to help analyze spend and understand how data is being used. Stay tuned as we roll out first-class support for gaining awareness into every piece of metadata relevant to your data teams. After all, the name Metaplane comes from “metadata plane.”
We start with product because that’s our obsession as a team. But ultimately to bring data observability to as many teams as possible, we also have to focus on growth. While our focus on enabling anyone to self-serve and adopt Metaplane has worked out, there’s still a huge amount of work to be done in order to help data leaders understand data observability. What is it? What problem does it solve for me? How should I implement it? How do I measure the return on investment? These are questions that we’re helping answer both at scale and via 1-1 relationships by growing our team.
There’s a Chinese fable of a farmer who was impatient for his rice to grow, so he pulled the sprouts out of the ground. We have been deliberate to raise money at the right time with the right partners that understand how to build and scale product and go-to-market teams. With a strong technical and cultural foundation in place, now is the time to grow to help the many data teams that are underwater today because trust is lost by the second.
Time and trust are two things that are easy to lose and hard to regain. And we work hard to help others preserve trust because that’s the standard we hold ourselves to.
A long time ago, my co-founder Guru told me a quote from HubSpot co-founder Dharmesh Shah: “Success is making those who believed in you look brilliant.” I think of this quote often. Because while we in technology talk about belief in ideas of the future, this future couldn’t be built without believing in each other.
Thank you to our new investors like Kanu and Nikita at Khosla and the Stage 2 capital team for trusting us with your time and resources, as well as to our existing investors at Flybridge, Y Combinator, and SNR for doubling down. We’re also lucky to have the support of wonderful angel investors, including the founders of Okta, HubSpot, Vercel, Brooklyn Data Co, Airbyte, Lookout, and more.
Thank you to our customers who took a bet on an emerging category – you’re the people who we look up to every day. A special shoutout to our very first customers like Andy, Peter, (Data) Dan, Jaime, and Etoma who took the additional bet on an emerging company.
Thank you to the team: Jen, Colby, Todd, Gus, David, Ted, Gab, and Laura. You don’t have to have a short name to work at Metaplane but it is highly preferred. I am grateful to spend every day working with people at the top of their craft.
Thank you to our peers and partners in the data ecosystem, from the Snowflake and dbt and Sigma teams, to data consultancies, to our advocates in the space.
Many of the people above are also friends, but thank you most of all to friends and family for being on this journey with us. You know who you are. Building an enduring company is taxing and wouldn’t be possible without your support.
To everyone above: we want to make you proud.
If you work on a data team and would like to see how Metaplane can help your team ensure trust in data, we’d love to chat. If you’re looking to hone your craft by building or growing a world-class product, please reach out too. Cheers to a bright future where data is the lifeblood of companies without the teams behind that data getting paged at 3am!