rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Profit-driven business analytics
    sub title: a practitioner's guide to transforming big data into added value
  name:
    name part: Verbeke, Wouter
    name part: 1983-
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Bravo, Cristián
    name part: 1983-
    role:
      role term: author.
  name:
    name part: Baesens, Bart
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: nju
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: Maximize profit and optimize decisions with advanced business analytics Profit-Driven Business Analytics provides actionable guidance on optimizing the use of data to add value and drive better business. Combining theoretical and technical insights into daily operations and long-term strategy, this book acts as a development manual for practitioners seeking to conceive, develop, and manage advanced analytical models. Detailed discussion delves into the wide range of analytical approaches and modeling techniques that can help maximize business payoff, and the author team draws upon their recent research to share deep insight about optimal strategy. Real-life case studies and examples illustrate these techniques at work, and provide clear guidance for implementation in your own organization. From step-by-step instruction on data handling, to analytical fine-tuning, to evaluating results, this guide provides invaluable guidance for practitioners seeking to reap the advantages of true business analytics. Despite widespread discussion surrounding the value of data in decision making, few businesses have adopted advanced analytic techniques in any meaningful way. This book shows you how to delve deeper into the data and discover what it can do for your business.-Reinforce basic analytics to maximize profits -Adopt the tools and techniques of successful integration -Implement more advanced analytics with a value-centric approach -Fine-tune analytical information to optimize business decisions Both data stored and streamed has been increasing at an exponential rate, and failing to use it to the fullest advantage equates to leaving money on the table. From bolstering current efforts to implementing a full-scale analytics initiative, the vast majority of businesses will see greater profit by applying advanced methods. Profit-Driven Business Analytics provides a practical guidebook and reference for adopting real business analytics techniques.
  table of contents: Cover ; Title Page ; Copyright ; Contents ; Foreword; Acknowledgments; Chapter 1: A Value-Centric Perspective Towards Analytics ; Introduction ; Business Analytics ; Profit-Driven Business Analytics ; Analytics Process Model ; Analytical Model Evaluation ; Analytics Team ; Profiles.
  table of contents: Data Scientists Conclusion ; Review Questions; Multiple Choice Questions; Open Questions; References ; Chapter 2: Analytical Techniques ; Introduction ; Data Preprocessing ; Denormalizing Data for Analysis ; Sampling ; Exploratory Analysis ; Missing Values ; Outlier Detection and Handling.
  table of contents: Principal Component Analysis Types of Analytics ; Predictive Analytics ; Introduction ; Linear Regression ; Logistic Regression ; Decision Trees ; Neural Networks ; Ensemble Methods ; Bagging ; Boosting ; Random Forests ; Evaluating Ensemble Methods.
  table of contents: Evaluating Predictive Models Splitting Up the Dataset ; Performance Measures for Classification Models ; Performance Measures for Regression Models ; Other Performance Measures for Predictive Analytical Models ; Descriptive Analytics ; Introduction ; Association Rules.
  table of contents: Sequence Rules Clustering ; Survival Analysis ; Introduction ; Survival Analysis Measurements ; Kaplan Meier Analysis ; Parametric Survival Analysis ; Proportional Hazards Regression ; Extensions of Survival Analysis Models ; Evaluating Survival Analysis Models.
  note: Wouter Verbeke, Bart Baesens, Cristián Bravo.
  note: Includes index.
  note: Includes bibliographical references and index.
  subject:
    topic: Management
    topic: Statistical methods
  subject:
    topic: Management
    topic: Data processing
  subject:
    topic: Big data
  subject:
    topic: Value added
  subject:
    topic: Strategic planning
  subject:
    topic: Business
    topic: Data processing
  classification: HD30.215 .V47 2017
  classification: 658.4/033
  related item:
    title info:
      title: Profit-driven business analytics
    name:
      name part: Verbeke, Wouter, 1983-
    origin info:
      publisher: Hoboken, New Jersey : John Wiley & Sons, Inc., [2018]
    identifier: (DLC) 2017028656
  identifier: 9781119286998
  identifier: 1119286999
  identifier: 9781119286981
  identifier: 1119286980
  identifier: 9781119443179
  identifier: 1119443172
  identifier: 9781119286554
  identifier: 1119286557
  identifier: 2017040378
  identifier: 7C6F2756-CE32-4DE6-9FFA-D3C3F2D44C38 OverDrive, Inc.
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: DLC
    record creation date: 170824
    record change date: 20260215000845.9
    record identifier: in00005690212
    language of cataloging:
      language term: eng