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Data engineering Startup 'Datazip' secures $1 million in Seed Funding round

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Datazip, a Bengaluru-based data engineering startup, has raised $1 million in a seed funding round with the contribution of Equirus InnovateX Fund for about Rs. 6 crore.

This marks EIF’s second deployment its $30 million tech-focused venture capital fund. Datazip has previously gained $ 200k from Anicut Capital and other investors.

The new funding will work on to develop with new data engineering and analytics project in India.

Co-founded in the year 2022, Sandeep Devarapalli, Shubham Baldava, and Rohan Khameshra, Datazip concentrates on constructing a lakehouse platform which designs to magnify data engineer’s productivity by tenfold. The platform majorly works for helping their data works and achieve real-time insights by permitting them to continue to be competitive in a fast changing growing market.

Commenting on the vital investment, Sunder Nookala, General Partner, Equirus InnovateX Fund (EIF), said “We are delighted to partner with Datazip in their mission to make data engineers 10x more productive. Their deep understanding of data engineering challenges, coupled with a clear vision, is what drew us to the founders. We believe their platform will become an essential tool for any data-driven business”.

Shubham Baldava, Co-founder and CTO of Datazip, added “The fundraise will help us create & innovate world class data engineering and analytics products out of India”.

Rohan Khameshra, Co-founder and CPO of Datazip, concluded “We’re grateful for Equirus InnovateX Fund’s confidence in Datazip’s vision. This partnership will accelerate our mission to provide data engineers with the tools they need to thrive in the era of open data and AI”.

The data lakehouse market is at present value $ 11.1 billion and growing at a tremendously CAGR of 22.9% from the year 2023 to 2033 inherently reaching to $ 66.6 billion. Datazip has already taken 15 clients and now focused on climbing its functions significantly in upcoming year focusing to change how firms are managing bigger datasets in actual time.