Mozart Data, the all-in-one modern data platform, was selected as a finalist in the Enterprise & Smart Data Technology category for the 14th annual SXSW Pitch® (formerly SXSW Accelerator). Mozart Data was selected out of ~700 applicants to showcase its technology to a panel of judges and a live audience on Saturday, March 12 at the Hilton Austin Downtown, Salon D/E.
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Mozart Data is the quickest way to set up the infrastructure needed to centralize, organize, and prepare data for analysis. Building a data stack has historically been out of reach for start-ups, who have limited engineering resources, capital, and time. Mozart Data makes it possible for anyone, from founders to marketers, to set up a data stack in an hour without having to rely on engineering.
“Most start-ups only set up their data stack after they start feeling the pain of exporting data, managing large amounts of data on spreadsheets, and being reliant on engineering to pull data. We’re making modern data stacks more accessible so start-ups can deeply understand their customers, answer complex questions, and create a data-driven business early on,” said Peter Fishman, CEO and Co-Founder of Mozart Data. “We’re honored to be a part of SXSW Pitch, and we look forward to joining other innovators there.”
SXSW Pitch will be held the first weekend of SXSW Conference & Festivals, Saturday, March 12 and Sunday, March 13, on the fourth floor of the Downtown Hilton Austin, Salon D/E. The event will then culminate with the 2022 SXSW Pitch Awards Ceremony on Sunday evening, March 13, where winning start-ups from each category and a Best in Show winner will be announced and honored.
About Mozart Data
Mozart Data is the all-in-one modern data platform that gives anyone the tools to centralize, organize, and analyze data. Mozart Data is on a mission to empower anyone to get the most out of their data without engineering or technical knowledge. Businesses of all sizes, from start-ups to Fortune 100 companies, use Mozart Data to power their data infrastructure and free up their teams to focus on the data engineering and analysis that’s unique to them.