Firm level strategic decision-making with data science & analytics

Michael Sienna Goldstein

Firm level strategic decision-making with data science & analytics

Číslo: 1/2022
Periodikum: Business & IT
DOI: 10.14311/bit.2022.01.25

Klíčová slova: Big data analytics; Data mining; Banking; Survey

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Anotace: Even though the usage of big data will add value for business throughout the whole value chain, the integration of big data analytics on the decision-making process is still a struggle. This particular study, according to an organized literature review, thematic analysis as well as qualitative interview findings, proposes a set of six steps to build each relevance and rigor in the approach of analytics driven decision making. Our findings illuminate the primary key stages in this particular choice process such as issue definition, review of previous results, data collection, model development, data analysis in addition to methods on insights in the context of service methods. Even though results are reviewed in a sequence of actions, the study identifies them as iterative and interdependent. The recommended six step analytics driven decision making process, pragmatic proof from service methods, along with future studies agenda, supply entirely the groundwork for future scholarly research and will function as a step wise guidebook for business practitioners.