Explore architectural approaches to building Data Lakes that ingest, index, manage, and analyze massive amounts of data using Big Data technologies About This Book * Comprehend the intricacies of architecting a Data Lake and build a data strategy around your current data architecture * Efficiently manage vast amounts of data and deliver it to multiple applications and systems with a high degree of performance and scalability * Packed with industry best practices and use-case scenarios to get you up-and-running Who This Book Is For This book is for architects and senior managers who are responsible for building a strategy around their current data architecture, helping them identify the need for a Data Lake implementation in an enterprise context. The reader will need a good knowledge of master data management and information lifecycle management, and experience of Big Data technologies. What You Will Learn * Identify the need for a Data Lake in your enterprise context and learn to architect a Data Lake * Learn to build various tiers of a Data Lake, such as data intake, management, consumption, and governance, with a focus on practical implementation scenarios * Find out the key considerations to be taken into account while building each tier of the Data Lake * Understand Hadoop-oriented data transfer mechanism to ingest data in batch, micro-batch, and real-time modes * Explore various data integration needs and learn how to perform data enrichment and data transformations using Big Data technologies * Enable data discovery on the Data Lake to allow users to discover the data * Discover how data is packaged and provisioned for consumption * Comprehend the importance of including data governance disciplines while building a Data Lake In Detail A Data Lake is a highly scalable platform for storing huge volumes of multistructured data from disparate sources with centralized data management services. This book explores the potential of Data Lakes and explores architectural approaches to building data lakes that ingest, index, manage, and analyze massive amounts of data using batch and real-time processing frameworks. It guides you on how to go about building a Data Lake that is managed by Hadoop and accessed as required by other Big Data applications. This book will guide readers (using best practices) in developing Data Lake's capabilities. It will focus on architect data governance, security, data quality, data lineage tracking, metadata management, and semantic data tagging. By the end of this book, you will have a good understanding of building a Data Lake for Big Data. Style and approach Data Lake Development with Big Data provides architectural approaches to building a Data Lake. It follows a use case-based approach where practical implementation scenarios of each key component are explained. It also helps you understand how these use cases are implemented in a Data Lake. The chapters are organized in a way that mimics the sequential data flow evidenced in a Data Lake.

About the Author
Pradeep Pasupuleti has over 17 years of experience in architecting and developing distributed and real-time data-driven systems. Currently, he focuses on developing robust data platforms and data products that are fuelled by scalable machine-learning algorithms, and delivering value to customers in addressing business problems by applying his deep technical insights. Pradeep founded Datatma expressly to humanize Big Data, simplify it, and unravel new value on a previously unimaginable scale in economy and scope. He has created COE (Centers of Excellence) to provide quick wins with data products that analyze high-dimensional multistructured data using scalable natural language processing and deep learning techniques. He has performed roles in technology consulting and advising Fortune 500 companies. Beulah Salome Purra has over 11 years of experience and specializes in building large-scale distributed systems. Her core expertise lies in working on Big Data Analytics. In her current role at ATMECS, her focus is on building robust and scalable data products that extract value from the organization's huge data assets.


Book Information
ISBN 9781785888083
Author Pradeep Pasupuleti
Format Paperback
Page Count 164
Imprint Packt Publishing Limited
Publisher Packt Publishing Limited