Near real-time analytics on operational data are critical for modern enterprises. Use cases include Personalization, Fraud detection, Churn prevention, Gaming leader boards, and Product Insights. To gain near-real time analytics, you need data to be refreshed in a matter of seconds. Achieving this in existing solutions can be difficult as it involves expensive and cumbersome data pipelines to keep analytics data stores refreshed with operational data. But now, by using streaming ingestion capability of Redshift, you can enable near real-time data refresh and scale them seamlessly. Veerendra will show you how!
Additional Resources:
Amazon DynamoDB integration with Kinesis: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/kds.html
Amazon Redshift Streaming Ingestion overview: https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-streaming-ingestion.html
Amazon Redshift Streaming Ingestion Blog: https://aws.amazon.com/blogs/big-data/real-time-analytics-with-amazon-redshift-streaming-ingestion/
Check out more resources for architecting in the #AWS cloud:
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