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.
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Stockinger, K., Braschler, M., Stadelmann, T. (2019). Lessons Learned from Challenging Data Science Case Studies. In: Braschler, M., Stadelmann, T., Stockinger, K. (eds) Applied Data Science. Springer, Cham. https://doi.org/10.1007/978-3-030-11821-1_24
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