Scaling Analytics with a Consolidated Data Lake and Data Warehouse, Featuring Metromile

As the leading pay-per-mile car insurance company in the U.S, Metromile relies on data to drive its business, but it faced significant challenges, including data silos, complex and slow data pipelines, slow queries, and a difficult data management platform. Metromile turned to Stitch, a Talend company, and Snowflake for help. With Stitch, the cloud-native platform for rapidly moving data, and Snowflake, the leading cloud data platform, it has achieved simplified, streamlined, and scalable data and analytics. 

Join Metromile VP of Data, Sathish Koteshwar, as he discusses how he and his team:

• Minimize the number of data stores and data processing tools in their environment to lower overall complexity and cost
• Rely on Stitch for simple and fast data extraction from a wide range of data sources, with reliable timestamps
• Use Stitch to simply and easily add new datasets into the analysis ecosystem
• Leverage Snowflake as a consolidated, low-maintenance data lake and data warehouse to store all structured and semi-structured data in a single location, and enable all users to perform fast queries and analytics on all the data with standard SQL
• Use the powerful architecture of Snowflake and its separation of storage and compute to perform data transformation jobs in under five minutes that used to take up to seven hours

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