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

Data Lake for Enterprises

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

Data Lake for Enterprises

2.9 (8)
By: Vivek Mishra, Tomcy 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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Thoughts on data traceability

Traceability is the ability to verify the history, location, or application of an item by means of documented recorded identification.
- Wikipedia

Data traceability means the path followed by data in moving from one location (origin) to another (destination), various processes and transformation it undergoes while doing so before reaching its intended destination. We have already seen what data lineage is, so what is the difference between lineage and traceability?

Data lineage is often associated with metadata management and governance and has a difference to what data traceability means.

Data lineage is more technical in nature and shows each and every important step the data undergoes when going from origin to destination. This is a very important capability/resource for a technical team but doesn't give much sense to a non-technical business or other users in the enterprise...

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Data Lake for Enterprises
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