Book Image

Data Lake Development with Big Data

By : Pradeep Pasupuleti, Beulah Salome Purra
Book Image

Data Lake Development with Big Data

By: Pradeep Pasupuleti, Beulah Salome Purra

Overview of this book

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.
Table of Contents (13 chapters)

Chapter 1. The Need for Data Lake

In this chapter, we will understand the rationale behind building a Data Lake in an organization that has huge data assets. The following topics will be covered in this chapter:

  • Explore the emerging need for Data Lake by understanding the limitations of the traditional architectures

  • Decipher how a Data Lake addresses the inadequacies of traditional architectures and provides significant benefits in terms of time and cost

  • Understand what a Data Lake is and also its architecture

  • Practical guidance on the key points to consider before deciding to build a Data Lake

  • Understand the key components that could be a part of a Data Lake and comprehend how crucial each of these components are to build a successful Data Lake