By Russell Jurney
Data technology groups seeking to flip study into valuable analytics purposes require not just the best instruments, but additionally the ideal technique if they’re to be triumphant. With the revised moment variation of this hands-on consultant, up-and-coming information scientists will the best way to use the Agile facts technological know-how improvement technique to construct information functions with Python, Apache Spark, Kafka, and different tools.
Author Russell Jurney demonstrates find out how to compose an information platform for construction, deploying, and refining analytics functions with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll examine an iterative process that permits you to fast switch the type of research you’re doing, counting on what the information is telling you. submit information technological know-how paintings as an online software, and have an effect on significant swap on your organization.
- Build price out of your info in a sequence of agile sprints, utilizing the data-value pyramid
- Extract gains for statistical versions from a unmarried dataset
- Visualize facts with charts, and divulge assorted elements via interactive reports
- Use historic info to foretell the long run through category and regression
- Translate predictions into actions
- Get suggestions from clients after every one dash to maintain your undertaking on track
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Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark by Russell Jurney