Data Analysis and Visualization

This second course of the Data-Driven Decision Making (DDDM) series provides a high-level overview of data analysis and visualization tools, preparing learners to discuss best practices and develop an ensuing action plan that addresses key discoveries. The course material includes common hurdles that obstruct adoption of a data-driven culture, data analysis tools (R software, Minitab, MATLAB, and Python), statistical process control for studying variation over time, visualization software (Tableau, Excel, Power BI), and creating a data story.   

This online course is available on the Coursera platform.

Course Duration: Approximately 11 hours

Learning Outcomes

  • Identify stakeholders and key components imperative to an analytics project plan
  • Name strengths and weaknesses of different analysis and visualization tools
  • Visually identify, monitor, and remove process variation
  • Explain how to create a compelling data story

Intended Audience

Individuals keen on developing a data-driven mindset that derives powerful insights useful for improving a company’s bottom line

Prerequisites

  • Some familiarity with reading reports, gathering and using data, and interpreting visualizations is helpful
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