Glean raises $7 million to democratize data insights – TechCrunch

You would think data visualization and exploration is a bit of a problem solved thanks to Tableau, Sisense, Looker, Microsoft Power BI and their competitors. But for the most part, these tools were developed before every business had a data lake and warehouse, let alone a lake house. Of course, that means there’s room for more startups in this space to provide a modern experience for building dashboards on top of all that data. One of them is Glean, which is now sneaking out and announcing a $7 million seed funding round led by Matrix Partners’ Ilya Sukhar. A number of angel investors including Elad Gil, Shana Fisher, Dylan Field, Scott Belsky, Cristina Cordova, Akshay Kothari, DJ Patil and Anthony Goldbloom also participated in this round.

Glean co-founder Carlos Aguilar was an early systems engineer at Kiva Systems, where he got to work with large datasets from the company’s warehouse robots. It was there that he realized that many teams wanted to access this data, but writing a new SQL query for each query was not scalable in the long term. “Even back then, I developed this passion for not having to do this,” he told me. “I could create these data apps, and then a whole subset of questions would disappear. But more than that, people were super empowered and now they could do all kinds of things that they couldn’t do before. […] I loved this idea of ​​taking complexity, simplifying it, and building tools from there.

After Kiva was acquired by Amazon, Aguilar worked there for a few years and then joined Flatiron Health as the first data hire there and while the team was able to build tools to manage data there Also, the bottleneck has now shifted to building data applications to help the rest of the business get insights from their data as quickly as possible. That meant a lot of time building dashboards in old BI tools and helping others use them.

Glean’s mission, Aguilar said, is not just to democratize data, but to democratize ideas. Being able to dig into data and not just look at a dashboard is what most users want, he argued, and it’s something a lot of legacy tools do quite well. “There are a bunch of startups and upstarts, but nothing really gives you the powerful kind of interactivity that you still get with a lot of these legacy tools,” he said.

Glean wants to combine this interactivity without the barrier to entry of the likes of Tableau. You still need someone in a company who knows a bit of SQL and someone who can model the data, but once that’s done, Glean will automatically try to find the best defaults to visualize that data. The service currently supports Snowflake, BigQuery, and PostgreSQL. As Aguilar noted, the company’s current focus is on data warehouses, in part because that data is usually already cleansed and ready to be queried.

Picture credits: Glean

Once these first steps are taken, even non-technical users should be able to easily browse connected data and remix a given view for their own use cases as well. As of now, Glean supports all standard visualizations (think pivot tables, line charts, bar charts, etc.). And while it may be trying to democratize this data analysis workflow and many of its users aren’t techies, the company also builds a lot of tools for engineers, including git integrations, a CLI , native build tools, etc.

“We have seen a massive revolution in data infrastructure over the past few years. Organizations of all kinds now have access to more data than ever before. But there has been little innovation in the way data teams present information to their colleagues. They are struggling to keep pace and deliver the business impact expected of them,” said Sukhar of Matrix Partners. “Carlos and his team at Glean are redesigning the BI layer to solve this problem. The idea is to empower everyone in an organization to dive into the data and make sense of it. The team has deep experience building data products at Flatiron Health and we are excited to work with them to seize this huge opportunity.

Going forward, the team wants to build more collaboration features to bring an almost Google Docs-like experience to these dashboards — and that’s part of what the team will use the new funding for. “The focus is really on creating an amazing experience with a very high level of fit and finish that just feels amazing to use,” Aguilar said. “It turns out that doing this in the context of data and with lots of different people is a very difficult problem. So investing in those basic analytics workflows and making it an amazing experience is top of the list. The team is also looking to build more systems and automation tools to automatically build models from various points in a company’s data pipeline.

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