Agile Data Science

Agile Data Science Front Cover
1 Reviews
178 pages

Book Description

Mining big data requires a deep investment in people and time. How can you be sure you’re building the right ? With this hands-on book, you’ll learn a flexible toolset and methodology for building effective analytics applications with .

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 you’re doing, depending on what the data is telling you. All example 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 on track

Table of Contents

Part I. Setup
Chapter 1. 
Chapter 2. Data
Chapter 3. Agile Tools
Chapter 4. To the Cloud!

Part II. Climbing the Pyramid
Chapter 5. Collecting and Displaying Records
Chapter 6. Visualizing Data with Charts
Chapter 7. Exploring Data with Reports
Chapter 8. Making Predictions
Chapter 9. Driving Actions

Book Details

  • Title: Agile Data Science
  • Author:
  • Length: 178 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2013-10-25
  • ISBN-10: 1449326269
  • ISBN-13: 9781449326265
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