DATA STREAMING AND ANALYSIS
DOI:https://doi.org/10.68325/lp.book.007
About This Textbook
This textbook offers an in-depth exploration of real-time data streaming architectures, processing engines, and advanced analytics methods essential for modern data-driven ecosystems. It covers foundational stream processing concepts, distributed messaging systems, event-driven architectures, and scalable analytics algorithms.
Data Streaming and Analysis provides cutting-edge insights into real-time stream processing frameworks, Apache Kafka, Apache Flink, distributed event streams, and scalable stream analytics for big data applications.
Table of Contents
- Chapter 1: Fundamentals of Real-Time Data Streaming
- Chapter 2: Distributed Event Messaging Systems & Architecture
- Chapter 3: Stream Processing Frameworks (Kafka, Flink, Spark Streaming)
- Chapter 4: Windowing, Event Time & Stateful Stream Computation
- Chapter 5: Real-Time Stream Analytics & Machine Learning on Streams
- Chapter 6: Scalability, Fault Tolerance & Enterprise Streaming Systems
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