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)

Architectural guidance

As evidenced in the previous sections, there are a plethora of options available for Data Consumption; choosing the right tool depends primarily on the use case you are attempting to implement using the Data Lake. We also see that the market is flooded with umpteen tools that make decision making very difficult.

Data Discovery

We have seen, in the previous sections, that Data Lake exposes a queryable interface to data consumers to discover the data. Simple visualizations such as a histogram or tag cloud can provide an intuitive understanding of the data. The following figure depicts the key aspects that are to be considered while choosing the right tools and technologies for Data Discovery:

Key considerations for choosing a Data Discovery tool

Big Data tools and technologies

The following section takes you through an indicative list of Big Data tools and technologies that can be used for your specific use case.


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