Isbn: 9783960671046 - customer payment trend analysis based on clustering for predicting the financial risk of business organizations (17 risultati)

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Taschenbuch. Condizione: Neu. Customer Payment Trend Analysis based on Clustering for Predicting the Financial Risk of Business Organizations | Jeeva Jose | Taschenbuch | 76 S. | Englisch | 2017 | Anchor Academic Publishing | EAN 9783960671046 | Verantwortliche Person für die EU: Bedey & Thoms Media GmbH, Björn Bedey, Hermannstal 119k, 22119 Hamburg, info[at]diplom[dot]de | Anbieter: preigu.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With the opening of the Indian economy, many multinational corporations are shifting their manufacturing base to India. This includes setting up green field projects or acquiring established business firms of India. The region of this business unit is expanding globally. The variety and size of the customer base is expanding and the business risk related to bad debts is increasing. Close monitoring and analysis of payment trends helps to predict customer behavior and predict the chances of customer financial strength.The present manufacturing companies generate and store tremendous amount of data. The amount of data is so huge that manual analysis of the data is difficult. This creates a great demand for data mining to extract useful information buried within these data sets. One of the major concerns that affect companies' investments and profitability is bad debts; this can be reduced by identifying past customer behavior and reaching the suitable payment terms. The Clustering and Prediction module was implemented in WEKA - a free open source software written in Java. This study model can be extended to the development of a general purpose software package to predict payment trends of customers in any organisation. 76 pp. Englisch.…

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Condizione: New. Print on Demand pp. 76.

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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. With the opening of the Indian economy, many multinational corporations are shifting their manufacturing base to India. This includes setting up green field projects or acquiring established business firms of India. The region of this business unit is expan.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - With the opening of the Indian economy, many multinational corporations are shifting their manufacturing base to India. This includes setting up green field projects or acquiring established business firms of India. The region of this business unit is expanding globally. The variety and size of the customer base is expanding and the business risk related to bad debts is increasing. Close monitoring and analysis of payment trends helps to predict customer behavior and predict the chances of customer financial strength.The present manufacturing companies generate and store tremendous amount of data. The amount of data is so huge that manual analysis of the data is difficult. This creates a great demand for data mining to extract useful information buried within these data sets. One of the major concerns that affect companies' investments and profitability is bad debts; this can be reduced by identifying past customer behavior and reaching the suitable payment terms. The Clustering and Prediction module was implemented in WEKA - a free open source software written in Java. This study model can be extended to the development of a general purpose software package to predict payment trends of customers in any organisation.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -With the opening of the Indian economy, many multinational corporations are shifting their manufacturing base to India. This includes setting up green field projects or acquiring established business firms of India. The region of this business unit is expanding globally. The variety and size of the customer base is expanding and the business risk related to bad debts is increasing. Close monitoring and analysis of payment trends helps to predict customer behavior and predict the chances of customer financial strength.The present manufacturing companies generate and store tremendous amount of data. The amount of data is so huge that manual analysis of the data is difficult. This creates a great demand for data mining to extract useful information buried within these data sets. One of the major concerns that affect companies¿ investments and profitability is bad debts; this can be reduced by identifying past customer behavior and reaching the suitable payment terms. The Clustering and Prediction module was implemented in WEKA ¿ a free open source software written in Java. This study model can be extended to the development of a general purpose software package to predict payment trends of customers in any organisation.Diplomica Verlag, Hermannstal 119k, 22119 Hamburg 76 pp. Englisch.…