Episode description

Processing data in real time is a process, as some might say. Angela Chu (Solution Architect, Databricks) and Caio Moreno (Senior Cloud Solution Architect, Microsoft) explain how to integrate Azure, Databricks, and Confluent to build real-time data pipelines that enable you to ingest data, perform analytics, and extract insights from data at hand. They share about where to start within the Apache Kafka® ecosystem and how to maximize the tools and components that it offers using fully managed services like Confluent Cloud for data in motion.

EPISODE LINKS

• Consuming Avro Data from Apache Kafka Topics and Schema Registry with Databricks and Confluent Cloud on Azure 
• Azure Data Lake Storage Gen2 introduction
• Best practices for using Azure Data Lake Storage Gen2
• Join the Confluent Community
• Learn more with Kafka tutorials, resources, and guides at Confluent Developer
• Live demo: Kafka streaming in 10 minutes on Confluent Cloud
• Use 60PDCAST to get an additional $60 of free Confluent Cloud usage (details)