Agile Data Science 2.0

Building Full-Stack Data Analytics Applications with Spark

Nonfiction, Computers, Database Management, Programming, Programming Languages, Application Software
Cover of the book Agile Data Science 2.0 by Russell Jurney, O'Reilly Media
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Author: Russell Jurney ISBN: 9781491960066
Publisher: O'Reilly Media Publication: June 7, 2017
Imprint: O'Reilly Media Language: English
Author: Russell Jurney
ISBN: 9781491960066
Publisher: O'Reilly Media
Publication: June 7, 2017
Imprint: O'Reilly Media
Language: English

Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.

Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization.

  • Build value from your data in a series of agile sprints, using the data-value pyramid
  • Extract features for statistical models from a single dataset
  • Visualize data with charts, and expose different aspects through interactive reports
  • Use historical data to predict the future via classification and regression
  • Translate predictions into actions
  • Get feedback from users after each sprint to keep your project on track
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Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.

Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization.

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