Recognition Acknowledges Databricks’ Ability to Execute and Completeness of Vision for Third Year in a Row
Databricks, the leader in unified data analytics, has been named by Gartner as a Leader in the 2020 Magic Quadrant for Data Science and Machine Learning Platforms.
“We see this placement as a Leader in the Gartner Magic Quadrant, along with our other recognition this year, as a clear sign of the growing massive demand for unified data analytics.”
Databricks’ Unified Data Analytics Platform allows organizations access to all of their big data and traditional data for business intelligence and machine learning on one platform. On its journey to help data teams solve the world’s toughest problems, Databricks has lasered in on being customer obsessed, building a strong partner ecosystem and continuing to innovate and contribute to the open source community, including the development of new open source projects, Delta Lake and MLflow.
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“Data science and machine learning is top of mind within every organization. Even traditional, hundred-years old companies are trying to become high-tech companies to keep a competitive advantage over data-driven startups. In order to be successful, organizations require one cohesive platform for data teams to collaborate on business intelligence and machine learning,” said Ali Ghodsi, cofounder and CEO at Databricks. “We see this placement as a Leader in the Gartner Magic Quadrant, along with our other recognition this year, as a clear sign of the growing massive demand for unified data analytics.”
Databricks has contributed significant innovations to the open source community. In addition to being the original creators of Apache Spark, Databricks leads the development of Delta Lake, MLflow and Koalas, which has earned the company a reputation as an innovator within the open source community.
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Databricks continued its momentum by closing its Series F funding, which raised the company’s total funding amount to $900 million. The capital is intended to accelerate innovation and scale across the globe, and values Databricks at $6.2 billion. Thousands of global organizations such as Nielsen, Hotels.com, Overstock, Bechtel, Shell and HP are leveraging Databricks to unify data science and data engineering teams across the end-to-end data and machine learning lifecycle.
Gartner’s report evaluated 16 vendors based on their ability to execute and the completeness of their vision for its Magic Quadrant for Data Science and Machine Learning Platforms. Gartner’s completeness of vision axis comprised eight evaluation criteria: market understanding, marketing strategy, sales strategy, offering (product) strategy, business model, vertical/industry strategy, innovation, and geographic strategy. The ability to execute axis comprised seven criteria: product or service, overall viability, sales execution/pricing, market responsiveness/record, marketing execution, customer experience, and operations.
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