Agile Data Science: Building Data Analytics Applications with Hadoop


Agile Data Science: Building Data Analytics Applications with Hadoop 1st Edition
by Russell Jurney
Print Length 页数: 178 pages
Publisher finelybook 出版社: O’Reilly Media; 1 edition (October 28,2013)
Language 语言: English
ISBN-10: 1449326269
ISBN-13: 9781449326265


Book Description
By finelybook

Building Data Analytics Applications with Hadoop
About the Author
Russell Jurney cut his data teeth in casino gaming,building web apps to analyze the performance of slot machines in the US and Mexico. After dabbling in entrepreneurship,interactive media and journalism,he moved to silicon valley to build analytics applications at scale at Ning and LinkedIn. He lives on the ocean in Pacifica,California with his wife Kate and two fuzzy dogs.
Mining big data requires a deep investment in people and time. How can you be sure you’re building the right models? With this hands-on book,you’ll learn a flexible toolset and methodology for building effective analytics applications with Hadoop.
Using lightweight tools such as Python,Apache Pig,and the D3.js library,your team will create an agile environment for exploring data,starting with an example application to mine your own email inboxes. You’ll learn an iterative approach that enables you to quickly change the kind of analysis you’re doing,depending on what the data is telling you. All example code in this book is available as working Heroku apps.
Create analytics applications by using the agile big data development methodology
Build value from your data in a series of agile sprints,using the data-value stack
Gain insight by using several data structures to extract multiple features from a single dataset
Visualize data with charts,and expose different aspects through interactive reports
Use historical data to predict the future,and translate predictions into action
Get feedback from users after each sprint to keep your project on track
Contents
Part I. Setup
Chapter 1. Theory
Chapter 2. Agile Tools
Chapter 3. Data
Part II. Climbing the Pyramid
Chapter 4. Collecting and Displaying Records
Chapter 5. Visualizing Data with Charts and Tables
Chapter 6. Exploring Data with Reports
Chapter 7. Making Predictions
Chapter 8. Deploying Predictive Systems
Chapter 9. Improving Predictions
Appendix A. Manual Installation

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