A well-architected data lakehouse provides an open data platform that combines streaming with data warehousing, data engineering, data science and ML. This opens a world beyond streaming to solving business problems in real-time with analytics and AI. See how companies like Albertsons have used Databricks and Confluent together to combine Kafka streaming with Databricks for their digital transformation.
In this talk, you will learn:
- The built-in streaming capabilities of a lakehouse
- Best practices for integrating Kafka with Spark Structured Streaming
- How Albertsons architected their data platform for real-time data processing and real-time analytics
Ram Dhakne works as a solutions engineer at Confluent. He has a wide array of experience in NoSQL databases, filesystems, distributed systems, and Apache Kafka. He has supported industry verticals ranging from large financial services, retail, healthcare, telecom, and utilities companies. His current interests are in helping customers adopt event streaming using Kafka. As a part-time hobby, he has written two children’s books.