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  • Book Overview & Buying Data Lake for Enterprises
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Data Lake for Enterprises

Data Lake for Enterprises

By : Mishra, John, Pankaj Misra
2.9 (8)
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Data Lake for Enterprises

Data Lake for Enterprises

2.9 (8)
By: Mishra, John, Pankaj Misra

Overview of this book

The term "Data Lake" has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects — data lake and lambda architecture—together. This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient. By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake.
Table of Contents (13 chapters)
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Summary

The topic covered in this chapter is quite exhaustive. Rest assured that you have covered enough of Apache Kafka to implement a Data Lake.

In this chapter, we started with the relevance of messaging layer in the context of a Data Lake. After that, the chapter deep dived into Kafka and detailed it's architecture and its various components. It then showed you the full working example of Kafka with step-by-step instructions from installation all the way to taking data from a source, to destination using Kafka. Finally, as in other chapters we introduced other choices which can replace Kafka as the technology to achieve the same capability.

After reading this chapter, you should now have a clear idea of the messaging layer and a deep understanding of Apache Kafka and how it works. You should also have a clear idea of how our use case can use this technology and what exactly it accomplishes.

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Data Lake for Enterprises
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