Back when Bigeye cofounders Kyle Kirwan and Egor Gryaznov worked at Uber, they had to make sure the data they dealt with was reliable. It was a tough problem.
When they left the ride-hailing giant, Kirwan and Gryaznov, some of the earliest employees in Uber's data organization, decided they wanted to solve this problem not just for Uber, but for the entire industry. In 2018, they launched Bigeye, which lets users easily monitor and analyze data, and make sure it's reliable.
Bigeye on Thursday unveiled a $45 million in Series B round led by Coatue, bringing total capital raised to $66 million. It plans to use the some of the money to hire more staff, particularly on the produce side. The startup currently has 25 employees, and wants to expand to 40 by the end of the year.
"It helps us go after the best talent," Kirwan, the CEO, told Insider. "Growing the team fast enough to keep up with what customers want is the #1 thing on my mind. All these things we want to do, we can only build so fast."
Bigeye sought out VCs who believe that data is an "increasingly important part of modern business" and understand that making sure data is reliable is a challenge, Kirwan said. In early 2019, not many VCs realized this was a challenge.
"Over the last couple of years, they've spoken to more and more data engineers," Kirwan said. "There's been more attention in the space. Many of them have come to realize this is an unsolved problem. I think that swayed the opinion a lot."
Uber data challenges
At Uber, Kirwan and Gryaznov worked on A/B testing, where developers send out 2 versions of an app to different groups of users and track how they respond. New Uber features like mobile cash validation would be trialed this way, via a team of 10 to 12 employees dedicated to data quality.
In addition to the cost of such a big team, Kirwan and Gryaznov noticed that data were sometimes recorded wrong, or the information got mixed up with other types of data. A mistake made in one place might cascade down and cause problems for other teams. A lot of time was spent cleaning up data, too.
Kirwan started interviewing data engineers and scientists and kept hearing the same thing over and over again: this was still a mostly unsolved problem. That's when he and Gryaznov set out to create a self-service tool to tackle the issue, and that grew into Bigeye.
When they worked at Uber, they used PostgreSQL, an open-source database. Today, data engineers and scientists now use services from Snowflake, Databricks, and Facebook's Presto. Bigeye tools connect to this software, helping customers monitor their information more easily.
