Real-time data analytics is no longer a luxury—it's a necessity. Understanding and acting on data as it flows can be the difference between staying ahead or falling behind.
In my latest video, I explained real-time analytics using Apache Spark Structured Streaming.
This session covers:
The fundamentals of real-time analytics and its significance
Contrasting batch processing with stream processing
An in-depth look at Spark Structured Streaming mechanics
Integrating Spark with data sources like Kafka and socket streams
Real-world applications including fraud detection, system monitoring, and alerting
Whether you're a data engineer, backend developer, or a cloud enthusiast, this video offers valuable insights into building scalable, real-time data pipelines.
Watch the full video here: Real-Time Analytics with Apache Spark | Stream Processing Explained
Let's explore how to harness the power of real-time data for smarter decision-making.
Thanks for watching!
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