What to Expect from Case Studies and Review Sessions

The Case Studies in the SAS Academy for Data Science are different from the exercises in the courses.

• The case studies are selected because they do not have a clean solution.
• The data sets are messy (and real!), and the business problem is framed by a domain expert who knows very little about data management, analytics, or programming.
• This enables you to experience true client interactions, where you, the data scientist, are the technical expert and the client lacks the vocabulary to guide you to appropriate analyses.

If you find the case studies frustrating to work on, take heart in knowing that you are doing realistic data science work. Use the case study review sessions to observe the thought process of an experienced analyst.

In data science, solving problems often requires taking a novel approach, making assumptions, engineering new inputs, or combining analyses in unconventional ways.

• It is rare that one solution is uniformly correct!
• It is rare that a problem has a clean solution.

Seeing the approaches of different analysts helps you find new ways to solve problems in the future.