Lessons Learned from Challenging Data Science Case Studies

Kurt Stockinger, Martin Braschler, Thilo Stadelmann

Abstract: In this chapter, we revisit the conclusions and lessons learned of the chapters presented in Part II of this book and analyze them systematically. The goal of the chapter is threefold: firstly, it serves as a directory to the individual chapters, allowing readers to identify which chapters to focus on when they are interested either in a certain stage of the knowledge discovery process or in a certain data science method or application area. Secondly, the chapter serves as a digested, systematic summary of data science lessons that are relevant for data science practitioners. And lastly, we reflect on the perceptions of a broader public toward the methods and tools that we covered in this book and dare to give an outlook toward the future developments that will be influenced by them.