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Big Data, Data Mining, Machine Learning und Predictive Analytics: Ein konzeptioneller Überblick

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  • Brühl, Volker

Abstract

Mit der fortschreitenden Digitalisierung von Wirtschaft und Gesellschaft wächst die Bedeutung von Big Data Analytics, maschinellem Lernen und Künstlicher Intelligenz für die Analyse und Pognose ökonomischer Trends. Allerdings werden in wirtschaftspolitischen Diskussionen diese Begriffe häufig verwendet, ohne dass jeweils klar zwischen den einzelnen Methoden und Disziplinen differenziert würde. Daher soll nachfolgend ein konzeptioneller Überblick über die Gemeinsamkeiten, Unterschiede und Interdependenzen der vielfältigen Begrifflichkeiten im Bereich Data Science gegeben werden. Denn gerade für Entscheidungsträger aus Wirtschaft und Politik kann eine grundlegende Einordnung der Konzepte eine sachgerechte Diskussion über politische Weichenstellungen erleichtern.

Suggested Citation

  • Brühl, Volker, 2019. "Big Data, Data Mining, Machine Learning und Predictive Analytics: Ein konzeptioneller Überblick," CFS Working Paper Series 617, Center for Financial Studies (CFS).
    • Handle: RePEc:zbw:cfswop:617
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    JEL classification:

    • A10 - General Economics and Teaching - - General Economics - - - General
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

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