By completing this course, learners will be able to explain the fundamentals of Apache Pig, apply Pig Latin scripts for big data processing, analyze and transform datasets using operators and functions, and design advanced workflows with UDFs and Piggy Bank.

This comprehensive program takes learners from beginner to advanced concepts in a structured way. Starting with the foundations of Pig and its role in the Hadoop ecosystem, learners will explore execution modes, data types, and essential commands for managing and displaying data. The course then progresses into mastering Pig operators, including GROUP, JOIN, UNION, SPLIT, and FILTER, while demonstrating the use of built-in functions to prepare data for analytics. Finally, learners gain hands-on experience with Pig scripting, debugging, execution plans, and extending Pig’s capabilities using user-defined functions and community-contributed libraries. Unlike traditional MapReduce coding, Pig offers a simplified scripting environment that reduces development time and complexity. This course is unique because it blends practical scripting exercises with real-world data transformation scenarios, equipping learners with the skills to efficiently process large-scale datasets. By the end, learners will confidently apply Apache Pig to streamline ETL workflows and enhance big data analytics.