With a subtitle of Building Full-Stack Data Analytics Applications with Spark,  the revised second edition of this hands-on guide, shows 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.

Author: Russell Jurney
Publisher: O'Reilly
Date: June 2017
Pages: 352
ISBN: 978-1491960110
Print: 1491960116
Kindle: B072MKL34K
Audience: Data scientists
Level: Intermediate

• 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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