Simplify Hadoop programming to create complex endtoend Enterprise Big Data solutions with PigAbout This BookQuickly understand how to use Pig to design end-to-end Big Data systems Implement a hands-on programming approach using design patterns to solve commonly occurring enterprise Big Data challenges Enhances users' capabilities to utilize Pig and create their own design patterns wherever applicableWho This Book Is ForThe experienced developer who is already familiar with Pig and is looking for a use case standpoint where they can relate to the problems of data ingestion, profiling, cleansing, transforming, and egressing data encountered in the enterprises. Knowledge of Hadoop and Pig is necessary for readers to grasp the intricacies of Pig design patterns better.What You Will LearnUnderstand Pig's relevance in an enterprise context Use Pig in design patterns that enable data movement across platforms during and after analytical processing See how Pig can co-exist with other components of the Hadoop ecosystem to create Big Data solutions using design patterns Simplify the process of creating complex data pipelines using transformations, aggregations, enrichment, cleansing, filtering, reformatting, lookups, and data type conversions Apply knowledge of Pig in design patterns that deal with integration of Hadoop with other systems to enable multi-platform analytics Comprehend design patterns and use Pig in cases related to complex analysis of pure structured dataIn DetailPig Design Patterns is a comprehensive guide that will enable readers to readily use design patterns that simplify the creation of complex data pipelines in various stages of data management. This book focuses on using Pig in an enterprise context, bridging the gap between theoretical understanding and practical implementation. Each chapter contains a set of design patterns that pose and then solve technical challenges that are relevant to the enterprise use cases.The book covers the journey of Big Data from the time it enters the enterprise to its eventual use in analytics, in the form of a report or a predictive model. By the end of the book, readers will appreciate Pig's real power in addressing each and every problem encountered when creating an analytics-based data product. Each design pattern comes with a suggested solution, analyzing the trade-offs of implementing the solution in a different way, explaining how the code works, and the results.