Data professionals and how to become one - final submission and poster

Data professionals are workers who collect, store, manage, and/or analyse, interpret, and visualise data as their primary part of their activity. Professions in data industry are one of the fastest growing professions. They provide information support for effective decision-making, they ensure quality and security of IT infrastructures and they help add value to the business. It is a complicated profession due to rapid emergence of new methods and technologies for working with data. Therefore, it is important to distinguish different types of data professionals and the skills that they work with. There are two main differences in professionals working with data: those who collect, store and manage, and those who analyse and visualise data. We singled out a few professions and analysed the job requirements for each: Data architect, Data engineer, Data analyst, Data scientist and Machine learning engineer. On the basis of job descriptions, there are several things employers always search for and that is: proven competence, analytical skills, technical skills, soft skills, domain expertise and seniority. Data architects’ tasks include integrating data within an organisation and guiding the design and development of data. Data engineer’s tasks, on the other hand, consist of collecting, processing, storing and transforming data as well as ensuring the readiness of data for further use. The expert called Data analyst is in charge of analysing, visualising and interpreting and also reporting data to stakeholders. Data analyst’s responsibility is validating, grouping and reporting data as an informative basis when it comes to decision-making. As data science is an interdisciplinary field, a Data scientist must possess knowledge in fields of machine learning, data mining and big data. Lastly, experts who often work together with Data scientist, Machine learning engineers, should be in control of creating, designing, implementing and deployment of machine learning models for the purpose of solving business tasks. In this poster, on the basis of job descriptions, we will guide you through some of the types of data professionals as well as provide you with information on what soft and hard skills you have to possess in order to become one. References/Bibliography: Bennett, Rachel & Alberti, Gianmarco & Cibik, Aytekin & Eremenko, Tatiana & Formosa, Saviour & Formosa‐Pace, Janice & Jiménez‐Buedo, María & Lynch, Kenneth & Salazar, Leire & Ubeda, Paloma. (2022). “Bringing about the data revolution in development: What data skills do aspiring development professionals need?” Journal of International Development. n/a-n/a. 10.1002/jid.3642. URL: https://www.researchgate.net/publication/359106375_Bringing_about_the_data_revolution_in_development_What_data_skills_do_aspiring_development_professionals_need [accessed 28.04.2022.] European Commission. Final results of the European Data Market study measuring the size and trends of the EU data economy. (2017). URL: https://wayback.archive-it.org/12090/20210728143405/https:/digital-strategy.ec.europa.eu/en/library/final-results-european-data-market-study-measuring-size-and-trends-eu-data-economy [accessed 28.04.2022.] N. Ahmad, A. Hamid and V. Ahmed, "Data Science: Hype and Reality," in Computer, vol. 55, no. 2, pp. 95-101, Feb. 2022, doi: 10.1109/MC.2021.3130365. URL: https://ieeexplore.ieee.org/abstract/document/9714109 [accessed 28.04.2022.] Persaud, Ajax. "Key competencies for big data analytics professions: a multimethod study." Information Technology & People (2020). URL: https://ruor.uottawa.ca/bitstream/10393/40272/1/Competencies%20for%20BDA%20Professions.pdf [accessed 28.04.2022.] SSA Group Team. Data professionals: An overview of specialisations and responsibilities (2021). URL: https://www.ssa.group/blog/data-professionals-an-overview/ [accessed 28.04.2022.