Agile Data Science

Agile Data Science

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Mining big data requires a deep investment in people and time. How can you be sure youa€™re building the right models? With this hands-on book, youa€™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. Youa€™ll learn an iterative approach that enables you to quickly change the kind of analysis youa€™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 trackBuilding Data Analytics Applications with Hadoop Russell Jurney. ) TYPE= MyISAM; CREATE TABLE headers ... This is optimized for our process: doing data science, where wea#39;re deriving new information from existing data. There is no benefit.

Title:Agile Data Science
Author:Russell Jurney
Publisher:"O'Reilly Media, Inc." - 2013-10-15


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