Commercial data mining : processing, analysis and modeling for predictive analytics projects / David Nettleton

Von:

Nettleton, David, 1963- [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: The Savvy manager's guide | The Savvy Manager's GuidesVerlag: Amsterdam : Morgan Kaufmann, [2014]Beschreibung: 1 Online-Ressource (circa 348 Seiten)ISBN:

9781306447928
1306447925
9780124166585

Schlagwörter:

Andere physische Formen: 9780124166028 | 1306449960 | Erscheint auch als: Commercial data mining. Druck-Ausgabe Amsterdam [u.a.] : Elsevier, 2014. xi, 288 pagesRVK: RVK: ST 530LOC-Klassifikation:

QA76.9.D343

Online-Ressourcen:

Zugang im Netz des KIT

Zusammenfassung: Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling. Commercial Data Mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book. Illustrates cost-benefit evaluation of potential projects Includes vendor-agnostic advice on what to look for in off-the-shelf solutions as well as tips on building your own data mining tools Approachable reference can be read from cover to cover by readers of all experience levels Includes practical examples and case studies as well as actionable business insights from author's own experience.Zusammenfassung: Front Cover -- Commercial Data Mining: Processing, Analysis and Modeling for Predictive Analytics Projects -- Copyright -- Contents -- Acknowledgments -- Chapter 1: Introduction -- Chapter 2: Business Objectives -- Introduction -- Criteria for Choosing a Viable Project -- Evaluation of Potential Commercial Data Analysis Projects - General Considerations -- Evaluation of Viability in Terms of Available Data - Specific Considerations -- Factors That Influence Project Benefits -- Factors That Influence Project Costs -- Example1: Customer Call Center - Objective: IT Support for Customer Reclamations -- Overall Evaluation of the Cost and Benefit of Mr. Strongs Project -- Example2: Online Music App - Objective: Determine Effectiveness of Advertising for Mobile Device Apps -- Overall Evaluation of the Cost and Benefit of Melody-onlines Project -- Summary -- Further Reading -- Chapter 3: Incorporating Various Sources of Data and Information -- Introduction -- Data about a Businesss Products and Services -- Surveys and Questionnaires -- Examples of Survey and Questionnaire Forms -- Surveys and Questionnaires: Data Table Population -- Issues When Designing Forms -- Loyalty Card/Customer Card -- Registration Form for a Customer Card -- Customer Card Registrations: Data Table Population -- Transactional Analysis of Customer Card Usage -- Demographic Data -- The Census: Census Data, United States, 2010 -- Macro-Economic Data -- Data about Competitors -- Financial Markets Data: Stocks, Shares, Commodities, and Investments -- Chapter 4: Data Representation -- Introduction -- Basic Data Representation -- Basic Data Types -- Representation, Comparison, and Processing of Variables of Different Types -- Principal Types of Variables -- Normalization of the Values of a Variable -- Distribution of the Values of a Variable -- Atypical Values - Outliers.PPN: PPN: 791157911Package identifier: Produktsigel: ZDB-26-MYL | ZDB-30-PAD | ZDB-30-PBE | ZDB-30-PQE

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