By Russell Jurney
Data technology groups trying to flip examine into worthwhile analytics purposes require not just the best instruments, but in addition the ideal strategy if they’re to be triumphant. With the revised moment version of this hands-on consultant, up-and-coming facts scientists will how you can use the Agile facts technology improvement technique to construct info functions with Python, Apache Spark, Kafka, and different tools.
Author Russell Jurney demonstrates the way to compose an information platform for development, deploying, and refining analytics purposes with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll research an iterative technique that permits you to fast swap the type of research you’re doing, counting on what the knowledge is telling you. submit info technological know-how paintings as an online software, and have an effect on significant switch on your organization.
- Build worth out of your information in a chain of agile sprints, utilizing the data-value pyramid
- Extract beneficial properties for statistical versions from a unmarried dataset
- Visualize facts with charts, and disclose diverse points via interactive reports
- Use old information to foretell the longer term through type and regression
- Translate predictions into actions
- Get suggestions from clients after each one dash to maintain your venture on track
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Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark by Russell Jurney