Data Observability Startup Bigeye Scores $45 Million In Funding

Company will use the Series B financing to accelerate development of its platform that helps businesses identify, monitor and correct data quality issues.

Data observability tech developer Bigeye has raised $45 million in a Series B round of funding announced Thursday, financing that the startup will apply toward accelerating development of its software and expanding its employee roster.

The new funding comes as Bigeye, founded in 2019 and based in San Francisco, reports that customer usage of its data observability software has doubled every quarter for each of the last four quarters. The company’s employee count has grown from 10 people to 30 in just six months, co-founder and CEO Kyle Kirwan said in an interview with CRN.

The new round of capitalization, which brings the company’s total funding to $66 million, comes just five months after a $17 million Series A round in April. The latest round was led by Coatue with participation from existing investors Sequoia Capital and Costanoa Ventures.

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Delayed, missing, duplicated and damaged data can hinder big data initiatives. But detecting problems using manual data engineering approaches is no longer feasible given the increasing volumes of data businesses are generating today.

“Data teams are incredibly resource-constrained these days, and they’re under more pressure than ever to ensure that the data products they provide to their stakeholders are reliable,” Kirwan said. “Data people need better tools if they’re going to rise to the challenge.”

Bigeye’s data observability platform is used to monitor the quality of data as it flows between systems, helping data management teams identify and fix data quality problems and maintain data integrity for self-service business analytics, AI and machine learning projects, and working with third-party data.

The Bigeye system, offered as a fully managed SaaS service as well as for on-premises/private cloud use, instruments data sets and data pipelines, applying metrics to monitor and measure data quality, detects data anomalies, and alerts data managers when issues occur.

The software works with a number of big data source systems such as Snowflake, Google BigQuery and Amazon Redshift and databases including Microsoft SQL Server, MySQL and PostgreSQL.

Kirwan said much of the new funding will go toward Bigeye’s product development efforts.

“We continue to push on the anomaly detection front,” he said, referring to one of the platform’s core functions. Going forward Bigeye will extend and automate the software’s data migration, workflow and problem resolution capabilities, helping data engineers to go beyond just identifying data issues to helping engineers fix them.

“In order to get there, we really have to grow the product team significantly,” the CEO said. “That’s where a lot of the money is going to go, engineering and design. I really can’t overstate that it’s product development,” he said of the company’s spending priorities.

Some funding will go toward sales and marketing initiatives, including hiring sales engineers who work closely with customers and customer prospects to demonstrate the Bigeye system’s functionality and value.

“We’re in an early stage and this is a new product for a lot of companies,” Kirwan said. “It’s important that we get pretty hands-on with them.” Bigeye now has a customer list that includes Instacart, Mindstrong and Udacity.

Bigeye has begun engaging with several systems integrators that are involved in larger cloud migration and business transformation projects where the Bigeye technology can play a role, Kirwan said. But the startup isn’t ready yet to identify partners until those projects are further along.

“We started our journey with Bigeye as a customer. We were impressed by the strength of the platform, their unique approach, and how that approach directly related to the potential size of Bigeye’s opportunity,” said Caryn Marooney, General Partner at Coatue, who is joining the Bigeye board, in a statement.