This article explains how to enable business users to analyze large datasets in data lakes using Amazon QuickSight, featuring Imperva's implementation approach.

• Imperva uses QuickSight to democratize data access across marketing, product, sales teams
• Data lake built on Amazon S3 with petabytes of security data continuously updated
• Solution 1: Query data with Athena and import incrementally into QuickSight SPICE cache
• Solution 2: Load data into Redshift Serverless for greater control and scalability
• SPICE provides fast interactive exploration without querying underlying data sources
• Redshift Serverless enables data editing, repair, and access for multiple clients
• No one-size-fits-all approach; choice depends on complexity and control requirements
• Both solutions are scalable, flexible, with similar costs for typical workloads

The article provides practical guidance for implementing data lake analytics pipelines that balance performance, cost, and engineering efficiency.