|658.4033 PAC (Browse shelf)
|No cover image available
|658.4033 GUP Quantitative techniques for decision making
|658.4033 KEL Decision making using game theory : an introduction for managers
|658.4033 LET Modelling, computation and optimization in information systems and management sciences
|658.4033 PAC Business analytics : data science for business problems
|658.4033 TOP Supermodularity and complementarity
|658.4034 AHR Operations research proceedings 2003
|658.4034 BEE Decision and control : the meaning of operational research and management cybernetics
Include bibliographic references and index.
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of: 1. statistical, econometric, and machine learning techniques; 2. data handling capabilities; 3. at least one programming language. Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.