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Building a Versatile Analytics Pipeline on Top of Apache Spark - Mikhail Chernetsov

1,361 views · Published 12 June 2017 · 31:00 · Indexed 12 November 2026

Channel: Databricks · 2017 · Science & Technology

It is common for consumer Internet companies to start off with popular third-party tools for analytics needs. Then, when the user base and the company grows, they end up building their own analytics data pipeline and query engine to cope with their data scale, satisfy custom data enrichment and reporting needs and achieve high quality of their data. That’s exactly the path that was taken at Grammarly, the popular online proofreading service.

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Building a Versatile Analytics Pipeline on Top of Apache Spark - Mikhail Chernetsov

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