Data Transformations with Apache Pig
Learn Pig: a powerful open-source engine for parallel data processing on Hadoop. Handle messy, incomplete, or schema-less data effectively. Data transformation made easy!
Course Content
Data Transformations with Apache Pig is a beginner-level Pluralsight course taught by Janani Ravi. It runs 3h 15m, is taught in English, and includes a certificate of completion. Learners rate it 4.9 out of 5 from 35 reviews. It is a paid course, first published June 2024.
Learn Data Transformations with Apache Pig and unlock the power of big data! This course dives into using Pig, an open source software within the Hadoop ecosystem, for processing data beyond the capabilities of traditional data warehouses. Pig excels at handling missing, incomplete, and inconsistent data, even when it lacks a predefined schema.
You'll begin with the fundamentals:
- Installation & Grunt Shell: Get Pig installed and learn to navigate the Grunt shell – your command-line interface for interacting with Pig.
- Data Loading & Storage: Discover how to load data into relations within Pig and efficiently store transformed results to files using the
loadandstorecommands. - Real-World Data Analysis: Apply your skills to a practical case study: analyzing NYC accident data using collision data from the City of New York.
- Advanced Techniques: Explore powerful Pig constructs, including the nested foreach operator for complex data manipulation.
- Introduction to MapReduce: Get a brief overview of MapReduce and see how easily you can implement it within Pig for scalable data processing.
By the end of this course, you'll gain a solid understanding of data transformations with Apache Pig and be equipped to handle complex data challenges. Pig is a valuable tool for anyone working with large, unstructured datasets.
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