Hadoop Blueprints
Anurag Shrivastava, Tanmay Deshpande
- 316 páginas
- English
- ePUB (apto para móviles)
- Disponible en iOS y Android
Hadoop Blueprints
Anurag Shrivastava, Tanmay Deshpande
Información del libro
Use Hadoop to solve business problems by learning from a rich set of real-life case studies
About This Book
- Solve real-world business problems using Hadoop and other Big Data technologies
- Build efficient data lakes in Hadoop, and develop systems for various business cases like improving marketing campaigns, fraud detection, and more
- Power packed with six case studies to get you going with Hadoop for Business Intelligence
Who This Book Is For
If you are interested in building efficient business solutions using Hadoop, this is the book for you This book assumes that you have basic knowledge of Hadoop, Java, and any scripting language.
What You Will Learn
- Learn about the evolution of Hadoop as the big data platform
- Understand the basics of Hadoop architecture
- Build a 360 degree view of your customer using Sqoop and Hive
- Build and run classification models on Hadoop using BigML
- Use Spark and Hadoop to build a fraud detection system
- Develop a churn detection system using Java and MapReduce
- Build an IoT-based data collection and visualization system
- Get to grips with building a Hadoop-based Data Lake for large enterprises
- Learn about the coexistence of NoSQL and In-Memory databases in the Hadoop ecosystem
In Detail
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.
Style and approach
This is an example-driven book where each chapter covers a single business problem and describes its solution by explaining the structure of a dataset and tools required to process it. Every project is demonstrated with a step-by-step approach, and explained in a very easy-to-understand manner.
Preguntas frecuentes
Información
Hadoop Blueprints
Hadoop Blueprints
Credits
Authors Anurag Shrivastava Tanmay Deshpande | Copy Editor Safis Editing |
Reviewers Dedunu Dhananjaya Wissem El Khlifi Randal Scott King | Project Coordinator Shweta H Birwatkar |
Commissioning Editor Aron Lazar | Proofreader Safis Editing |
Acquisition Editor Smeet Thakkar | Indexer Aishwarya Gangawane |
Content Development Editor Deepti Thore | Graphics Disha Haria |
Technical Editor Vivek Arora | Production Coordinator Nilesh Mohite |
About the Authors
I would like to thank my wife, Anjana, and daughter, Anika, for putting up with my late-night writing sessions and skipping of weekend breaks. I also would like to thank my parents and teachers for their guidance in life.
I would like to express my gratitude to colleagues at Xebia and Daan Teunissen, where I learned about the value of technical writing from colleagues, who inspired me to work on this book project. I would like to thank all the mentors that I’ve had over the years. I would like to express thanks and gratitude to Amir Arooni, my boss at ING Bank, who provided me time and opportunity to work on big data and, later on, this book. I also give thanks to the Packt team and the coauthor, Tanmay, who provided help and guidance in the whole process.
I would like to thank my family and the Almighty for supporting me throughout my all adventures.
About the Reviewers
@orawiss
.www.PacktPub.com
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