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Applied Analytics and Data for Decision Making

University at Buffalo and State University of New York via Coursera


By the end of this course, learners are prepared to identify and test the best solutions for improving performance and integrating concepts from operational excellence methodologies for optimum data-driven decision making. The course begins with a focus on deciphering the root cause of problems through a variety of tools before determining and assessing best-fit solutions. Learners discover how to apply ISO, Lean and Six Sigma in the pursuit of aligning organizational operations data with performance standards. Hospitality, manufacturing and e-commerce case studies help illustrate how to build data literacy while ensuring privacy and data ethics measures are in place.

Material features online lectures, videos, demos, project work, readings and discussions. This course is ideal for individuals keen on developing a data-driven mindset that derives powerful insights useful for improving a company’s bottom line. It is helpful if learners have some familiarity with reading reports, gathering and using data, and interpreting visualizations. It is the third course in the Data-Driven Decision Making (DDDM) specialization. To learn more about the specialization, check out a video overview at


  • Applying Analytics to Implement Solutions
    • This module guides learners through identifying the root causes for variation, and testing possible solutions.
  • Data-Driven Operational Excellence
    • This module prepares you to align an organization’s operations data to its performance standards to achieve operational excellence.
  • Applying Data-Driven Decisions
    • This module offers case examples of data-driven decision making in practice, and discusses how corporate culture relates to the success of such initiatives.
  • Project: Applied Analytics and Data for Decision Making
    • This module provides an opportunity to bridge theory and practice. Learners apply knowledge from this course to solve a business problem.

Taught by

Akshay Sivadas and Brittany O'Dea

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