Data Analytics Starter Guide Part II

As full-time working adults with busy personal lives, the ability to fully engage in a structured traditional course can be a roadblock. Video and interactive learning options is preferred so we can follow along, try applying the skills independently and be able to review the resources at our own pace. Three on-demand courses goes beyond classroom learning and gives practical perspectives. 

OpenRefine Foundation

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This free course covers the foundation of OpenRefine and its scripting language GREL. You will learn how to:

  • Use the facet/filter;

  • Leverage OpenRefine point and click transformation and fuzzy matching function for quick but powerful data cleaning ;

  • Write complex transformation in GREL, OpenRefine script language;

  • Call API and parse results in OpenRefine.

 

We developed the course in 2015 using OpenRefine 2.6-beta. We do our best to keep the content current with the latest version of OpenRefine. It is possible that some third-party services referenced in the course are not available any longer or have changed their interfaces. Please let us know if there is out of date information.

This course was developed by RefinePro in partnership with BigData University and Cognitive Class.  Since 2011, RefinePro has developed training programs for OpenRefine, including free online courses, in-person or remote courses, and individual coaching sessions.

Data Analytics Tutorial for Beginners: A Step-By-Step Guide

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This data analytics tutorial by Simplilearn also covers various data visualization skills and complex topics such as Python libraries and SQL. 

Data analytics enables organizations to uncover patterns and extract valuable insights from raw data. It helps companies understand their customers better, produce relevant content, strategize ad campaigns, develop meaningful products, and ultimately boost business performance.

 

This data analytics tutorial will help you learn all about data analytics - what it is, how to start a career in data analytics, various applications of data analytics, and the top questions asked in data analytics interviews.

Learn what you need and leave the rest for someone else :-)