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Databricks today announced the close of a $1 billion funding round, bringing the company’s valuation to $28 billion after post-money valuation, a company spokesperson told VentureBeat. News of the funding round — the largest to-date for Databricks — was first reported in late January by Newcomer.

This amounts to a series G funding round for the data analysis and AI company. Based in San Francisco, the $1 billion funding round was led by new investor Franklin Templeton, with participation from Amazon Web Services (AWS), the Canada Pension Plan investment board, Fidelity Management & Research, and Salesforce Ventures. Databricks CEO Ali Ghodsi told VentureBeat that part of the impetus behind the funding round was partnerships with cloud companies, which he called a symbiotic relationship of strategic importance for Databricks.

“Basically, we believe the vast majority of the data in the cloud is going to be in these data lakes, and we are building solutions to drive more of that,” he said.

The $1 billion funding will be used in part to fuel a merger and acquisition strategy with a focus on machine learning and data startups, a subject he told VentureBeat currently occupies 10-20% of his time every week. “I think there’s definitely a lot of interesting things happening, especially in natural language processing. There’s a lot of use cases in enterprise. They have a lot of textual data. Being able to sort of make sense of that can be super helpful for them,” he said.


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Ghodsi lists continued advances in machine learning and democratization of data and AI tools to people in business beyond computer scientists major ongoing trends he expects to shape the future of Databricks. “All these other enterprises out there are going to do the same thing: They’re going to be able to use data and AI in a strategic way just like Google did over the past 10 years or they’re going to be replaced. So our job is to democratize that,” he said.

Previous funding rounds have been led by Andreessen Horowitz and New Enterprise Associates (NEA) with participation from investors like Microsoft and Battery Ventures. Previous $250 million and $400 million funding rounds, held in February and October 2019 respectively, focused on development of the Unified Analytics platform, Delta Lake, and optimization of performance with the open source MLFlow platform for performing machine learning experiments and launching models into production. In June 2020, Databricks acquired Redash, the dashboard visualization for data scientists, and turned over control of MLflow to the Linux Foundation.

Databricks was founded in 2013 by the creators of Apache Spark, an open source framework for distributed computation across multiple machines many deep learning projects use today. The group of data and machine learning researchers first met at UC Berkeley.

Alongside companies like and Snowflake that filed IPOs in 2020, Databricks is the latest company focused on data analysis and AI to experience rapid growth. That’s despite a drop in gross domestic product in the U.S. economy in the past year the likes of which, according to the U.S. Department of Commerce, has not been seen since the 1940s.

In an unrelated but relevant matter, Databricks cofounder and UC Berkeley professor Ion Stoica talked about reinforcement learning trends as part of VentureBeat’s Transform conference.

Updated 2:30 p.m. to include comment from Databricks CEO Ali Ghodsi and add funding round details.

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