Successful Data Analysis for Modern Industries

Enrollment in this course is by invitation only

About This Course

While the fundamental skills of data analysis contain common patterns for every organization and industry, there are specific considerations when tackling data analyst work in context. This course is meant to give the aspiring data analyst deeper practice in specific organizational and industrial contexts, so that they can be better prepared for the unique contexts they’ll find themselves in when doing work on the job.

Please Note: Learners who successfully complete this course can earn a CloudSwyft digital certificate and skill badge - these are detailed, secure and blockchain authenticated credentials that profile the knowledge and skills you’ve acquired in this course.

What you'll learn

In this course, you will learn how to:

  • Understand Data’s contexts and applications in specific industries and in organizational settings
  • Practice common data analyst techniques while adapting for unique scenarios
  • Work with different types of data
  • Try out different types of data analyst roles to see what data problems resonate
  • Learn about where a Data Analyst career can go from this course and beyond


  • Basic excel proficiency, fundamental math and statistics background, data visualization fluency

Course Syllabus

  • Module 1: Data Analysis in Context
  • Module 2: Data Analysis for Business
  • Module 3: Data Analysis for Education
  • Module 4: Data Analysis for Healthcare
  • Module 5: Data Analysis for Government
  • Module 6: Careers for Data Analysts

Course Staff

Ben Olsen

Ben Olsen

Sr. Content Developer

Ben is a Sr. Content Developer for Microsoft's Learning and Readiness team, and is an analytics professional and educator with over 8 years of industry and managerial experience. Prior to joining Microsoft, Ben ran and directed multiple consulting firms, where he also held critical analytics roles in companies as diverse as Juniper Networks, Costco, and T-Mobile. He has taught Data Visualization at The University of Washington, and recently founded Seattle Pacific University's Analytics Certificate Program.

Trevor Barnes

Trevor Barnes

Content Developer


Tom Carpenter

Tom Carpenter

Assistant Professor of Psychology, Data Science consultant
Seattle Pacific University

Dr. Tom Carpenter is Assistant Professor of Psychology at Seattle Pacific University, and is also a Data Science consultant. His areas of expertise include personality-social psychology, research methods, and statistics. His teaching focuses on introductory and advanced research methods and statistics in psychology as well as social and personality psychology. Dr. Carpenter’s research focuses on our hypocritical human nature: our propensity to ignore our overt preferences and standards and to transgress against ourselves and others. One line of research in this area focuses on implicit bias, the impulsive thoughts that can undermine our higher reasoning. Dr. Carpenter has developed new software methods for running the Implicit Association Test (IAT) using online survey software (read more here: A second line of research focuses on guilt, shame, and self-forgiveness, specifically focusing on the functions of ‘guilt-proneness’ and ‘shame-proneness’ as well as associations with the general ability to forgive the self. Finally, Dr. Carpenter has conducted research related to his area of teaching (statistics education).

Frequently Asked Questions

Do I need desktop Excel?


Do I need a Windows computer to complete the course?

No. You can complete the labs using a computer running Windows, Mac OS X, or Linux.

  1. Course Number

  2. Classes Start

  3. Classes End

  4. Estimated Effort

    Total 12 to 24 hours