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Agile Data Science: Building Data Analytics Applications with Hadoop

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Agile Data Science: Building Data Analytics Applications with Hadoop Cover

 

Synopses & Reviews

Publisher Comments:

Mining big data requires a deep investment in people and time. How can you be sure youre building the right models? With this hands-on book, youll 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. Youll learn an iterative approach that enables you to quickly change the kind of analysis youre 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

Synopsis:

Mining data requires a deep investment in people and time. How can you be sure youre building the right models? What tools help you connect with the customers needs? With this hands-on book, youll learn a flexible toolset and methodology for building effective analytics applications.

Agile Data shows you how to create an environment for exploring data, using lightweight tools such as Ruby, Python, Apache Pig, and the D3.js (Data-Driven Documents) JavaScript library. Youll learn an iterative approach that allows you to quickly change the kind of analysis youre doing, as you discover what the data is telling you. All the example code in this book is available as working Heroku apps.

  • Build an application to mine your own email inbox
  • Use several data structures to extract multiple features from a single dataset, and learn how different perspectives can yield insight
  • Rapidly boot your applications as simple front-ends to key/value stores
  • Add features driven by descriptive and inferential statistics, machine learning, and data visualization
  • Gather usage data and talk to real users to help guide your data-driven exploration

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.

Table of Contents

PrefaceSetupChapter 1: TheoryChapter 2: DataChapter 3: Agile ToolsChapter 4: To the Cloud!Climbing the PyramidChapter 5: Collecting and Displaying RecordsChapter 6: Visualizing Data with ChartsChapter 7: Exploring Data with ReportsChapter 8: Making PredictionsChapter 9: Driving ActionsColophon

Product Details

ISBN:
9781449326265
Author:
Jurney, Russell
Publisher:
O'Reilly Media
Subject:
Data Modeling & Design
Subject:
Database design
Subject:
agile;applications;big data;d3;data mining;hadoop;javascript;lightweight;machine learning;pig;python;ruby;visualization
Copyright:
Edition Description:
Print PDF
Publication Date:
20131031
Binding:
TRADE PAPER
Language:
English
Pages:
178
Dimensions:
9.19 x 7 in

Related Subjects

Computers and Internet » Computer Languages » Ruby
Computers and Internet » Computers Reference » General
Computers and Internet » Database » Design
Computers and Internet » Software Engineering » General
Science and Mathematics » Mathematics » General

Agile Data Science: Building Data Analytics Applications with Hadoop New Trade Paper
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$39.99 In Stock
Product details 178 pages O'Reilly Media - English 9781449326265 Reviews:
"Synopsis" by ,

Mining data requires a deep investment in people and time. How can you be sure youre building the right models? What tools help you connect with the customers needs? With this hands-on book, youll learn a flexible toolset and methodology for building effective analytics applications.

Agile Data shows you how to create an environment for exploring data, using lightweight tools such as Ruby, Python, Apache Pig, and the D3.js (Data-Driven Documents) JavaScript library. Youll learn an iterative approach that allows you to quickly change the kind of analysis youre doing, as you discover what the data is telling you. All the example code in this book is available as working Heroku apps.

  • Build an application to mine your own email inbox
  • Use several data structures to extract multiple features from a single dataset, and learn how different perspectives can yield insight
  • Rapidly boot your applications as simple front-ends to key/value stores
  • Add features driven by descriptive and inferential statistics, machine learning, and data visualization
  • Gather usage data and talk to real users to help guide your data-driven exploration

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