Data Mining. Grundlagen und Verfahren mit praktischem Bezug
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Data Mining. Grundlagen und Verfahren mit praktischem Bezug

Data Mining. Grundlagen und Verfahren mit praktischem Bezug


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About the Book

Studienarbeit aus dem Jahr 2022 im Fachbereich Informatik - Wirtschaftsinformatik, Note: 1,3, SRH Fernhochschule, Sprache: Deutsch, Abstract: Durch die zunehmende Digitalisierung von Wirtschaft und Gesellschaft werden Analysen und Prognosen ökonomischer Trends immer wichtiger. Da betriebliche Prozesse eng mit Daten vernetzt sind, können sich mit ihrer Hilfe außerdem große Optimierungspotenziale von Prozessen oder Produkten, und somit von Wettbewerbsvorteilen insgesamt ergeben. Folglich nehmen Daten eine zentrale Rolle ein und sind ein unverzichtbarer Rohstoff für Unternehmen. Das Problem ist heute meist nicht mehr, an die Daten heranzukommen und sie zu speichern, sondern diese zu strukturieren, relevante Informationen aus ihnen zu ziehen und sie letztlich effektiv für das Unternehmen zu nutzen, sprich, mithilfe des generierten Wissens die richtigen Entscheidungen zu treffen. Zur Identifikation von Trends, Korrelationen und generell von Mustern dient das Data Mining. Beim Data Mining werden statistische und mathematische Verfahren oder Algorithmen auf die Daten angewendet. Diese Verfahren bzw. Algorithmen können die Muster identifizieren, dadurch Trends vorhersagen, Regeln aufstellen und Empfehlungen geben. Diese Hausarbeit beschäftigt sich mit Data Mining und dessen Methoden und Verfahren. Fragen, die sich stellen und im Verlauf der Arbeit thematisiert werden sollen, lauten: Was ist unter Data Mining zu verstehen? Welche Methoden und Verfahren des Data Mining existieren? Wie sähe eine Nutzung von Data Mining-Verfahren in einer Organisation wie der Bartels-Langness Handelsgesellschaft mbH & Co. KG (kurz: Bela) aus? Welche Vor- und Nachteile können sich für die Bela durch die Nutzung ergeben und wieso? Das Ziel dieser Arbeit liegt darin, auf die o. g. Fragen einzugehen und somit einen Überblick über das Thema Data Mining und dessen vielfältige Verfahren zu bekommen. Es sollen Beispiele zur Nutzung von Data Mining-Verfahren bei der Bartels-Langness Handelsgesell


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Product Details
  • ISBN-13: 9783346632036
  • Publisher: Bod Third Party Titles
  • Binding: Paperback
  • Language: German
  • Returnable: N
  • Weight: 109 gr
  • ISBN-10: 3346632032
  • Publisher Date: 11 May 2022
  • Height: 210 mm
  • No of Pages: 34
  • Spine Width: 2 mm
  • Width: 148 mm


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