Led by Coatue, the latest round follows on four consecutive quarters of doubling usage and new customers like Clubhouse, Recharge, and Udacity.
SAN FRANCISCO, September 23, 2021--(BUSINESS WIRE)--Bigeye, the provider of the leading data observability platform, today announced $45 million in Series B funding to further its leadership in the emerging category. Bigeye has doubled usage each of the last four quarters and added to its existing roster of customers, like Instacart, with new customers, including Clubhouse, Recharge, and Udacity. Led by Coatue and with participation from existing investors, Sequoia Capital and Costanoa Ventures, the latest round follows on a $17 million Series A from just 6 months earlier and brings total funding to $66 million.
With the funding, Bigeye will scale its team to address the rising demand for data observability, continue building on its product leadership, and help more data teams prevent customer-facing data outages, save expensive engineering hours, and build greater trust in the data.
"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 Board. "We are looking forward to partnering with Kyle, Egor, and the entire team as they continue to scale."
Helping modern data teams move faster with confidence
Bigeye’s customer roster covers a growing range of industries, including food delivery, financial services, machine learning providers, ed-tech, and more. Data teams use the platform to quantify and improve data quality and ensure reliable data pipelines for business-critical applications, including:
Self-service analytics: Bigeye customers like Instacart and Udacity make data-driven decisions an integral part of the way they grow their customer bases. Their data teams leverage Bigeye to monitor the data behind crucial analytics tools and ensure that strategic growth decisions are made on high-quality data.
ML and AI initiatives: Bigeye customers like Clubhouse and Rev are innovating with ML and AI to improve service and better engage their users. With Bigeye, data engineers can proactively prevent disruptive data pipeline problems from reaching their data scientists, who can then spend more time on high-value modeling activities.
Third-party data: Bigeye customers like Coatue and SignalFire ingest data from a huge variety of sources. They need to know that the data arrives on schedule and meets their quality standards at all times. With Bigeye, customers are able to automate that monitoring, giving them broader and more comprehensive visibility and ensuring that their data team workflows are never disrupted.
"Ensuring data quality doesn’t mean you have to go slow. In fact, if you address data quality with Bigeye, your team can actually move faster because they have trust in the data," said Dustin Pearce, VP of Infrastructure at Instacart.
"We're a small team, and we serve a massive community. Bigeye's monitoring tools help us know that our data is accurate and up to date, no matter how fast we're shipping," said Kenny D'Amica, head of data science at Clubhouse.
"We have a strong data-driven culture. Our business analysts, data scientists, and data-savvy business users rely on key data sets on a daily basis to better serve our millions of students. It’s imperative that we prevent anomalies from slipping through and negatively affecting their analysis. With Bigeye, we have an integrated one-stop solution for monitoring the health of our data — the ultimate answer as to whether our data is good or not," said Simon Dong, head of data engineering at Udacity.
"With the complexity of our data and the rate of change our business is undergoing, we needed a different approach to data quality. Bigeye provides an accessible, powerful, and agile data observability platform that benefits our entire organization. On day two of using Bigeye, we were putting checks in place to prevent issues that could have otherwise negatively impacted our business. By week three, we had elevated trust in our critical datasets and empowered the SMEs on our analytics teams to measure new context about what good data quality is," said Yuda Borochov, CDO of Zip Co.
Read more on the Series B announcement to learn more about Bigeye customers.
The leading data observability platform
With Bigeye, data teams prevent data quality issues from damaging the business and proactively detect the "unknown, unknowns" that wreak havoc on data pipelines. The platform automatically recommends and monitors the data quality metrics that matter — with more pre-built metrics than any other platform. As a result, data teams save countless hours, prevent costly data outages, and build greater trust in their data.
Under the hood, Bigeye reduces the toil that comes with manual data quality checks while providing data engineers with the ability to customize the platform to their needs. Sophisticated anomaly detection algorithms automatically adapt to changes in the business without requiring manual tuning. At the same time, complete API access and pre-built integrations with solutions like Airflow allow customers to integrate Bigeye seamlessly with the rest of their data stack. And because Bigeye is designed by former data lake and data warehouse engineers, the platform is highly performant, minimizing the performance tax associated with most observability systems and eliminating load spikes.
"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. Data people need better tools if they’re going to rise to the challenge. My co-founder Egor and I bonded over building these types of tools, and Bigeye allows us to do that at an industry-wide scale. Working with so many great teams of different sizes from a wide range of industries has been an amazing experience. We’re excited about what we can do with this new round of funding. We can scale the team, build our platform faster, and serve more customers than we normally would at such an early stage," said Kyle Kirwan, CEO and co-founder of Bigeye.
Bigeye is the leading data observability platform designed to help data teams build trust in data. Data teams use Bigeye to instrument their data with monitoring, detect anomalies, and publish SLAs for their stakeholders to know the health of the data at all times and ensure reliable data pipelines. Complete API access, a user-friendly interface, and flexible customization options help data teams work the way they want to. Bigeye can be deployed in as little as 15 minutes and uses automation and anomaly detection to help teams monitor all aspects of their data quality, proactively detect and resolve issues, and ensure that every user can trust the data. www.bigeye.com
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