Spark 3 Real-Time Stream Processing with Scala

Modern businesses rely on instant data insights to stay competitive. Learning to process data as it arrives is a critical skill for any modern data professional. This course takes you from foundational concepts to building robust, real-time streaming solutions. You will learn how to handle continuous data flows, manage state, and integrate with external systems using the Scala programming language. What you'll learn: - Understand the core architecture of Spark Structured Streaming and the micro-batch processing model - Apply Scala functional programming principles to transform and aggregate real-time data streams - Integrate Spark with external messaging systems like Kafka to ingest high-velocity event data - Manage stateful operations and windowing to analyze data over specific time intervals - Implement modern data lake patterns using Delta Lake for reliable and ACID-compliant streaming sinks - Practice writing unit tests for streaming logic to ensure pipeline reliability and data quality The curriculum begins with essential terminology and the Spark execution model before moving into written exercises for building end-to-end streaming pipelines. You will progress from simple data transformations to complex multi-source integrations. Designed for beginners to streaming, this course is ideal for software engineers and data professionals with a basic understanding of programming. Start your journey into real-time data engineering today.