Data scientists often need to transform gigabytes or terabytes of data, collected from trillions of sources, into useful insights by finding new ways that can improve their data performance. Spatial analysis has become an important component of the scientific toolbox that enriches all forms of data with geographic context. Analysts can discover patterns, make predictions, and optimize workflows to create operational efficiencies. To support the needs of these professionals, Esri, the world leader in location intelligence, is collaborating with Databricks, the data and AI company. This collaboration will provide users with advanced spatial analytics capabilities of Esri’s ArcGIS solution readily available on Databricks’ big data platform, Databricks Lakehouse.
“The Databricks Lakehouse platform brings together data engineering, data science, machine learning and analytics in one platform and, in many cases. In addition, customers also need an efficient spatial component,” said Roger Murff, VP of Product Partnerships at Databricks. “By running geo-analytical tools directly on Databricks, it encourages users to perform spatial analysis at a scale that Databricks can provide. »
Esri’s offerings that integrate with the Databricks Lakehouse platform include ArcGIS GeoAnalytics Engine and Big Data Toolkit, which are built primarily to allow users to perform spatial analysis on large datasets.
“Organizations and data practitioners using Databricks need spatial tools everywhere they work every day,” said Richard Cooke, director of global business development at Esri. “Esri’s solutions provide data scientists with native access to the most comprehensive set of spatial analysis tools available within the Databricks environment.
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