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Build a Real-Time Recommendation & Customer 360 Application

Workshop overview
Now, we’re going to kickstart the workshop! We’ll walk you through how to connect Kafka to Rockset, and build real-time recommendations and analytical queries based on live Kafka data and data stored in S3. After we have our data APIs on Rockset, we’ll build internal tools on Retool. Our architecture will look like this:
Workshop architecture
  1. 1.
    We’ll send clickstream and CSV data to Kafka and AWS S3.
  2. 2.
    We’ll integrate with Kafka and S3 through Rockset’s data connectors. This allows Rockset to automatically ingest and index JSON i.e.nested semi-structured data without flattening it.
  3. 3.
    In the Rockset Query Editor, we’ll write complex SQL queries that JOIN, aggregate, and search data from Kafka and S3 to build real-time recommendations and customer 360 profiles. From there, we’ll create data APIs that’ll be used on Retool (step 4).
  4. 4.
    Finally, we’ll build a real-time customer 360 app with the internal tools on Retool that’ll execute Rockset’s Query Lambdas. We’ll see the customer’s 360 profile that’ll include their product recommendations.
NOTE: You can find us on the Rockset Community if you have questions or comments about the workshop.