Book Image

Hadoop Blueprints

By : Anurag Shrivastava, Tanmay Deshpande
Book Image

Hadoop Blueprints

By: Anurag Shrivastava, Tanmay Deshpande

Overview of this book

If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level. Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book. The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space.
Table of Contents (14 chapters)
Hadoop Blueprints
About the Authors
About the Reviewers

Chapter 8. Future Directions

The Hadoop ecosystem is constantly evolving. As a result, it has many more tools to offer, but at the same time, alternative technologies are emerging to compete with and complement Hadoop. Hadoop exists to solve certain business problems. Before we suggest that Hadoop is the solution, we must know what the problem really is and whether it requires a technology as complex as Hadoop to solve it. Some problems can be solved by using traditional relational database management systems that are better understood and well tested in the enterprise. Hadoop and its ecosystem of tools introduce a significant dimension of complexity to your technology landscape, and that requires skilled people to operate.

A successful Hadoop implementation that delivers business value will be a collaborative effort between engineers and data scientists. If you have found the right skilled people and a problem that is right for Hadoop, then you will be setting up a Hadoop cluster, if it...