Thanks to the intensive literature study and discussions with peers, I understand why Dehmer and Emmert-Streib (2017) defined Data Science to deal with all aspects of data and why such a broad definition is needed.
In fact, this definition implies that there will be no shortage of jobs in Data Science, as Saxena (2021) claims. The traditional field of AI is complex questions, but even the most successful AI methods address simple questions (Emmert-Streib et al., 2020). This means the possibility of automating Data Scientists do not exist. Therefore, it is not surprising that economic works also conclude that "engineering activities" cannot be automated in the future (World Economic Forum, 2020). Instead, Josten and Lordan (2020) emphasised that "thinking" and "people" skills are increasingly critical. Both are core data science skills (Kenett & Redman, 2019). The argument of a peer to justify the concerns by the rapid development of quantum computers is also unfounded because the necessary algorithms do not yet exist and may never exist (Bennett et al., 1997; Biswas et al., 2017).
As identified by peers, the roles and responsibilities of data scientists change depending on the orientation and size of the company (What, 2020). Therefore, I use the umbrella term "Data Professional" (true to the module's name) for summarising possible responsibilities. Among others, a data professional must be able to accompany the entire data lifecycle (collection, processing, storage, management, analysis, visualisation and interpretation) (Dietrich, 2015). In-depth knowledge and application of data protection and information security management systems (ISO/IEC 27001, 2018) are just as central as knowledge of various process models and technologies such as Master Data Management (MDM), data mesh and data products (Strengholt, 2020). For example, a Data Professional must be able to advise that MDM should be considered if data is stable and truly matters or consider domain-specific approaches if the data is fast and fluid.
This is why such a loose definition, as proposed by Dehmer and Emmert-Streib (2017), is needed, and data science is a promising profession, albeit with downsides (Yildirim, 2020).
Bennett, C., Bernstein, E., Brassard, G. and Vazirani, U. (1997). Strengths and weaknesses of quantum computing. SIAM journal on Computing, 26(5): 1510-1523.
Biswas, R. et al. (2017). A NASA perspective on quantum computing: Opportunities and challenges. Parallel Computing, 64: 81-98.
Dehmer, M & Emmert-Streib, F. (2017). Frontiers in data science. 1st ed. CRC Press.
Dietrich, D., Heller, B. and Yang, B. (2015) Data science & big data analytics: Discovering, analyzing, visualizing and presenting data. EMC Education Services.
Emmert-Streib, F., Yli-Harja, O. and Dehmer, M. (2020) Artificial intelligence: A clarification of misconceptions, myths and desired status. Frontiers in artificial intelligence 3: 524339.
ISO/IEC 27001 (2018) Information Technology—Service Management—Part 1: Service Management System Requirements. International Organization for Standardization: Geneva, Switzerland
Josten, C. & Lordan, G. (2020) Robots at work: Automatable and non-automatable jobs. Springer International Publishing.
Kenett, R. and Redman, T. (2019) The Real Work of Data Science: Turning data into information, better decisions, and stronger organizations. John Wiley & Sons.
Saxena, P. (2021) There Will Be a Shortage of Data Science Jobs in the Next 5 Years?. Available from: https://towardsdatascience.com/there-will-be-a-shortage-of-data-science-jobs-in-the-next-5-years-9f783737ed23 [Accessed 25 September 2022]
Strengholt, P. (2020). Data Management at Scale. O'Reilly Media, Inc.
What, L.S. (2020) What does a data scientist actually do?, Medium. Towards Data Science. Available at: https://towardsdatascience.com/what-does-a-data-scientist-actually-do-7318b994b138 [Accessed: October 2, 2022]
World Economic Forum (2020) The Future of Jobs Report 2020. Available at: https://www.weforum.org/reports/the-future-of-jobs-report-2020/in-full/executive-summary [Accessed: October 11, 2022].
Yildirim, S. (2020) The Dark Side of the Sexiest Job of the 21st Century. Available from: https://towardsdatascience.com/the-dark-side-of-the-sexiest-job-of-the-21st-century-fd9c46bf4cae [Accessed 25 September 2022]