Case Study: Sisense achieves self-service, agile analytics on S3 streaming data with Upsolver

Sisense Drives New Analytical Insights from S3 by Leveraging a Data Lake Platform

Sisense, a leading business intelligence and analytics software provider, needed to build a data lake on AWS S3 to better analyze product usage (over 70 billion records and roughly 120 GB of new event data daily) and enable self-service analytics without creating a dedicated engineering silo. Following an AWS recommendation, Sisense evaluated and adopted Upsolver’s Data Lake Platform to ingest, clean, enrich and structure streaming product logs for ad-hoc analysis.

Using Upsolver, a single engineer turned raw streams into production-ready tables in a few weeks — ingesting, transforming and streaming datasets to Sisense and Amazon Athena without additional hires or infrastructure. The Upsolver-powered data lake gave analysts the ability to run new queries on streaming data, greatly improved visibility into product usage, and unlocked real-time and machine-learning use cases across product, sales and data science teams.

Sisense

Guy Boyangu

Co-founder and CTO