更新时间：2021-07-14 09:51:55
封面
版权页
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Why subscribe?
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Hadoop and Big Data
The beginning of the big data problem
Building open source Hadoop
Enterprise Hadoop
The design of the Hadoop system
MapReduce
Building a MapReduce Version 2 program
Hadoop platform tools
Big data use cases
The architecture of Hadoop-based systems
Summary
Chapter 2. A 360-Degree View of the Customer
Capturing business information
Setting up the technology stack
Test driving Hive and Sqoop
Engineering the solution
Presenting the view
Chapter 3. Building a Fraud Detection System
Understanding the business problem
Selecting and cleansing the dataset
Machine learning for fraud detection
Designing the high-level architecture
Creating our fraud detection model
Putting the fraud detection model to use
Chapter 4. Marketing Campaign Planning
Creating the solution outline
Supervised learning
Tree-structure models for classification
Finding the right dataset
Setting the up the solution architecture
Building the machine learning model
Running the Model on Hadoop
Creating the target List
Post campaign activities
Chapter 5. Churn Detection
A business case for churn detection
Building a churn predictor using Hadoop
Chapter 6. Analyze Sensor Data Using Hadoop
A business case for sensor data analytics
Technology stack
Batch data analytics
Stream data analytics
Chapter 7. Building a Data Lake
Data lake building blocks
Hadoop security
Apache Ranger
Apache Flume
Apache Zeppelin
Technology stack for Data Lake
Data Lake business requirements
Chapter 8. Future Directions
Hadoop solutions team
Hadoop on Cloud
NoSQL databases
