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Case Study

Democratising AI and data analytics: Databricks

Databricks started life as a project in academic and open-source communities, growing out of the AMPLab project at the University of California. On its official launch in 2013, it became the world’s first lakehouse platform in the cloud. It remains the only solution of this type today.

By combining the best aspects and capabilities of data warehouses and data lakes, Databricks provides an open and unified platform for analytics and AI. Its web-based solution for working with Apache Spark — a unified analytics engine for big data and machine learning – was transformational in bringing reliability to data lakes for machine learning and other advanced data science uses.

Today, Databricks is trusted by over 7,000 organisations around the world to enable massive-scale data engineering, full-lifecycle machine learning, business analytics and collaboration across data sciences. High-profile customers include ABN AMRO, Condé Nast, Regeneron and Shell.

Along with its headquarters in San Francisco, Databricks has 28 global locations across the US and South America, Asia, Europe and Australia. Its team of over 4,000 employees work with hundreds of partners from Microsoft and Amazon to Capgemini and Booz Allen to simplify and democratise complex technology.

Such is its global success that Databricks has received numerous prestigious accolades over the years. It is a Gartner Leader in both Cloud Database Management and Data Science and Machine Learning. It also features in Forbes’s AI 50 and Cloud 100 lists and was named one of the Most Innovative Companies in the World by Fast Company.

As well as rewards and recognition, Databricks’ phenomenal success is reflected in its financials. Over its ten-year lifespan, the company has raised USD 3.5bn over ten funding rounds, reaching a valuation of USD 38bn in 2022. Annual revenues for the same year topped an incredible USD 1bn, up from USD 600m in 2021.

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