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Prerequisites: Working with Pig requires some basic knowledge of the SQL query language, a brief understanding of the Hadoop eco-system and MapReduce 

Taught by a team which includes 2 Stanford-educated, ex-Googlers  and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with large-scale data processing jobs. 

Pig is aptly named, it is omnivorous, will consume any data that you throw at it and bring home the bacon!

Let’s parse that 

omnivorousPig works with unstructured data. It has many operations which are very SQL-like but Pig can perform these operations on data sets which have no fixed schema. Pig is great at wrestling data into a form which is clean and can be stored in a data warehouse for reporting and analysis.

bring home the baconPig allows you to transform data in a way that makes is structured, predictable and useful, ready for consumption.

What’s Covered: 

Pig Basics:  Scalar and Complex data types (Bags, Maps, Tuples), basic transformations such as Filter, Foreach, Load, Dump, Store, Distinct, Limit, Order by and other built-in functions.

Advanced Data Transformations and Optimizations: The mind-bending Nested Foreach, Joins and their optimizations using “parallel”, “merge”, “replicated” and other keywords, Co-groups and Semi-joins, debugging using Explain and Illustrate commands

Real-world example: Clean up server logs using Pig

Who this course is for:
  • Yep! Analysts who want to wrangle large, unstructured data into shape
  • Yep! Engineers who want to parse and extract useful information from large datasets

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