Unravel Data, a DataOps observability platform, has closed a $50 million Series D round of funding to accelerate the next generation of DataOps observability.
The round was led by Third Point Ventures, with participation from Bridge Bank and existing investors that include Menlo Ventures, Point 72, GGV Capital, and Harmony Capital, bringing the total amount of funding raised by Unravel Data to $107 million.
The company plans to use the investment to extend the Unravel Platform to help connect the dots from every system in the modern data stack within and across the most popular data ecosystems, including Databricks, Snowflake, Amazon EMR, BigQuery, and Dataproc. As the number of systems and data pipelines escalate, an entirely new way to manage and optimise the data pipelines that support the real-time analytics ambitions of the data-driven enterprise is needed.
Unravel Data announced the opening of its Hyderabad office last week, its second location in India after Bangalore. It also said it plans to accelerate tech talent hiring in India, and will be tripling its workforce with an emphasis on artificial intelligence, big data, and cloud DevOps skills.
“The DataOps observability market is poised to explode as enterprises invest in building data products that increase customers, revenue, and efficiencies. We’re excited to partner with Unravel Data, as the company has paved the way and established a proven track record of success helping some of the world’s most recognised brands simplify their data operations so they can bring new data-driven innovations to market,” said Curtis McKee, partner at Third Point Ventures.
As part of the new funding, McKee will be joining Unravel Data’s board of directors.
The investment comes as large enterprises face the challenge of operating an overwhelming number of data pipelines that are being used for data products, advanced modeling, and business-critical reporting, and at a time where the complexity of data systems is heightened by the shift to multi-cloud strategies and burdened by over-provisioned environments. As a result, data teams are struggling to deliver data outcomes in the time-efficient manner required and effectively manage the limitless rise in cloud compute and storage costs.
“Data engineers and data scientists currently spend more than half their day debugging and troubleshooting issues on the thousands of data pipelines in their environment. Just as the DevOps market united the practice of software development and operations a decade ago to transform the application lifecycle, data teams require the same kind of full-stack visibility, automation, and actionable intelligence that meet their needs around data pipeline performance, cost, and quality,” said Kunal Agarwal, CEO of Unravel Data.
Image: (L-R) Shivnath Babu, cofounder & CTO, Kunal Agarwal, cofounder & CEO, Unravel Data