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This book offers an overview of knowledge management. It starts with an introduction to the subject, placing descriptive models in the context of the overall field as well as within the more specific field of data mining analysis. Chapter 2 covers data visualization, including directions for accessing R open source software (described through Rattle). Both R and Rattle are free to students. Chapter 3 then describes market basket analysis, comparing it with more advanced models, and addresses the concept of lift. Subsequently, Chapter 4 describes smarketing RFM models and compares it with more advanced predictive models. Next, Chapter 5 describes association rules, including the APriori algorithm and provides software support from R. Chapter 6 covers cluster analysis, including software support from R (Rattle), KNIME, and WEKA, all of which are open source. Chapter 7 goes on to describe link analysis, social network metrics, and open source NodeXL software, and demonstrates link analysis application using PolyAnalyst output. Chapter 8 concludes the monograph. Using business-related data to demonstrate models, this descriptive book explains how methods work with some citations, but without detailed references. The data sets and software selected are widely available and can easily be accessed.

Business. --- Big data. --- Risk management. --- Data mining. --- Business and Management. --- Big Data/Analytics. --- Data Mining and Knowledge Discovery. --- Risk Management. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Insurance --- Management --- Data sets, Large --- Large data sets --- Data sets

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Data mining. --- Business --- Data processing.

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Project management.

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Project management.

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This book is devoted to presenting models that have been applied in project management. There are a variety of project domains. We discuss engineering/construction projects, software development projects, massive projects to include governmental undertakings, and pharmaceutical product development. Chapter 1 gives an overview of projects, and discusses the difficulties in completing projects on time, within budget, and at designed functionality. While the successful completion of a project is a challenge, there are some things that can be done to improve the probability of a project’s success. The book reviews a number of project management concepts. These include developing organizational ability to work on projects, as discussed in Chapters 2 and 3. Sponsor expectations can be based on better information if a good job of project development, estimation and selection is conducted, as discussed in Chapters 4, 5 and 6. Project planning tools involving the critical path method are covered in Chapter 7. Tools to evaluate project risk are covered in Chapter 8. The critical chain method is covered in Chapter 9. Chapter 10 discusses means to rush projects when circumstances demand, to include project crashing as well as Agile and SCRUM approaches used in software engineering projects. Chapter 11 covers project implementation and control, including assessment of delay responsibility.

Project management. --- Project Management.