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Data Mining and Statistics for Decision Making by Stéphane Tufféry

Data Mining and Statistics for Decision Making Stéphane Tufféry ebook
Publisher: Wiley
Page: 716
ISBN: 0470688297, 9780470688298
Format: pdf

Data mining is the automated analysis of large Web mining requires the use of mathematical algorithms and statistical techniques integrated with software tools. How do companies make They use data mining and business intelligence software to identify patterns and make sense of all the data. While the bulk of the paper describes the statistical model used to identify a relationship between data-driven decision making and business outcomes, it summarizes some of key findings from the research: It's not just about collecting data-it's about using it. Data-driven decision making leads to business success. In other words, it is the retrieval of useful information from large masses of information, which is also presented in an analyzed form for specific decision-making. Specifically, the Data Scientist gathers, manages, and studies internal and external data using data preparation, statistical modeling, and data mining techniques to understand the pool of potential University of Michigan donors. Statistical Methods: focused mainly on testing of preconceived hypotheses and on fitting models to data. The acquired knowledge is used in the development of Apply statistical hypothesis testing methods to estimate the impact of decisions and quantify the uncertainty surrounding decision-making. Thus, performing data mining process can lead to utilize in assist to make decision making process within the organization. Data mining has a vital role to extract important information to help in decision making of a decision support system. In addition, several operational research studies are planned to assess the effectiveness of specific interventions and inform government policy development and decision making. Where appropriate, operational research questions may be Develop and coordinate market research to inform the development of the demand generation strategy, potentially including focus groups, surveys and data analysis.