Data analytics startup Gigasheet closes $7m Series A to democratize big data analysis
Gigasheet, a startup that brings data science and big data analytics capabilities to anyone who can use a spreadsheet, announced it has closed $7 million in a Series A funding round. The no-code analytics platform helps organizations investigate massive data sets without the need for a database, an IT team, or knowledge of any query language like SQL.
VCs backing the company include Accomplice, Argon, Founder Collective, and REV. Other notable participants in the round are Crowdstrike co-founder Dmitri Alperovitch and Android Co-founder Rich Miner. The company was founded in 2020 and initially focused on cybersecurity but has rapidly grown to support thousands of users from a variety of industries.
Jason Hines, CEO and Co-founder, Gigasheet,: "We've been amazed at the broad range of people using Gigasheet in ways that we couldn't have imagined. We are seeing people work on everything from COVID research to Ukraine cyber intelligence analysis, and even voter data. In the same way Shopify makes it easy for anyone to sell online, or iMovie enables anyone to make short films, Gigasheet helps anyone get into big data analysis. If you can use a spreadsheet, you can use Gigasheet."
Despite the rise and growing popularity of enterprise big data platforms, most users still resort to flexible, commonly available applications like Microsoft Excel for quick data analysis and triage. Excel's long-standing row limitations make it inadequate in today's world where files containing millions of rows of data are commonplace. While more advanced programmatic approaches like Python Pandas and R libraries are powerful, they are out of reach for many entry-level professionals due to the substantial learning curve.
Gigasheet estimates around 750 million Excel users globally, but only about 3 million data scientists and big data engineers. They see an opportunity to help with easier-to-use products that offer the power and scale of an enterprise big data platform without complex technical setup, training, or maintenance.
Garth Griffin, CTO, Gigasheet: ''Often, the hardest part of big data analysis is getting the information into a platform where you can see it and work with it, and after that it's just a few data transformations to get the answers you need. Data scientists or engineers can do that work, but with the right technology, we can empower any analyst with spreadsheet skills to take on big data themselves. Gigasheet is that technology. Gigasheet's users are now doing just that.''
The company has processed more than 12 billion rows of user data over the last quarter.