Data Analysis (Apache Spark With Scala)

Description

This eBook provides a practical introduction to big data analytics using Apache Spark and Scala. Readers will learn the fundamentals of distributed computing, Spark architecture, resilient distributed datasets (RDDs), DataFrames, Spark SQL, machine learning pipelines, and real-time data processing. Step-by-step tutorials guide learners through data ingestion, transformation, visualization, and performance optimization using Scala programming. Practical case studies demonstrate how Apache Spark is used in finance, healthcare, retail, manufacturing, and scientific research to process massive datasets efficiently. The guide also covers cluster computing, fault tolerance, cloud deployment, and best practices for scalable data analytics. Suitable for students, software developers, data engineers, researchers, and IT professionals, this eBook equips readers with the knowledge required to build high-performance data processing applications and prepare for careers in big data and data engineering.