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001-es BibID:BIBFORM100800
035-os BibID:(Scopus)85121642125
Első szerző:Takács Viktor László (közgazdász, informatikus)
Cím:Mathability in Business Education / Takács Viktor László, Bubnó Katalin
Megjegyzések:Data Analyst or Data Scientist is one of the most sought-after professions. In tertiary education, the most common way for someone to become a Data Analyst is to learn Business and, later, if someone has some computational skills they can learn Computer Science as well. With the two degrees, they can solve real-life problems in their job. But there are a lot of necessary things they had never studied before because the basic conceptual methodology and the mindset were not based on any of the two curricula. Our aim is to develop a method in introductory business education to lay down the bases of the right-thinking towards data sciences for undergraduate students in Economics. If they are interested in the topic, they can orient themselves towards data sciences during their further studies. In this paper, we present a methodology to help Economics and Business Students to understand the main business questions, formalize the questions correctly, find computer-based solutions, and discuss/debug the results. Furthermore, students must learn basic data transformations and data enrichment methods as well, which is the primary feature of high-mathability problem-solving approaches. The tool we use is Microsoft Excel which contains OLAP (On-Line Analytical Processes) elements.
Tárgyszavak:Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény hazai lapban
data science
management questions
computer problem-solving
high-mathability teaching approaches
knowledge transfer
Megjelenés:Acta Polytechnica Hungarica. - 19 : 1 (2022), p. 9-29. -
További szerzők:Takácsné Bubnó Katalin (1974-) (matematika tanár, informatika tanár)
Pályázati támogatás:EFOP-3.6.1-16-2016-00022
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