TY  - BOOK
AU  - Baesens,Bart
TI  - Analytics in a Big Data World: The Essential Guide to Data Science and Its Applications
T2  - Wiley and SAS Business Ser
SN  - 9781118892718
AV  - HD30.215.B34 2014eb 
U1  - 658.4/038 
PY  - 2014///
CY  - New York
PB  - John Wiley & Sons, Incorporated
KW  - Big data
KW  - Decision making -- Data processing
KW  - Management -- Data processing
KW  - Management -- Statistical methods
KW  - Electronic books
N1  - Intro -- Analytics in a Big Data World -- Wiley & SAS Business Series -- Contents -- Preface -- Acknowledgments -- CHAPTER 1 Big Data and Analytics -- EXAMPLE APPLICATIONS -- BASIC NOMENCLATURE -- ANALYTICS PROCESS MODEL -- JOB PROFILES INVOLVED -- ANALYTICS -- ANALYTICAL MODEL REQUIREMENTS -- NOTES -- CHAPTER 2 Data Collection, Sampling, and Preprocessing -- TYPES OF DATA SOURCES -- SAMPLING -- TYPES OF DATA ELEMENTS -- VISUAL DATA EXPLORATION AND EXPLORATORY STATISTICAL ANALYSIS -- MISSING VALUES -- OUTLIER DETECTION AND TREATMENT -- STANDARDIZING DATA -- CATEGORIZATION -- WEIGHTS OF EVIDENCE CODING -- VARIABLE SELECTION -- SEGMENTATION -- NOTES -- CHAPTER 3 Predictive Analytics -- TARGET DEFINITION -- LINEAR REGRESSION -- LOGISTIC REGRESSION -- DECISION TREES -- NEURAL NETWORKS -- SUPPORT VECTOR MACHINES -- ENSEMBLE METHODS -- Bagging -- Boosting -- Random Forests -- MULTICLASS CLASSIFICATION TECHNIQUES -- Multiclass Logistic Regression -- Multiclass Decision Trees -- Multiclass Neural Networks -- Multiclass Support Vector Machines -- EVALUATING PREDICTIVE MODELS -- Splitting Up the Data Set -- Performance Measures for Classifi cation Models -- Performance Measures for Regression Models -- NOTES -- CHAPTER 4 Descriptive Analytics -- ASSOCIATION RULES -- Basic Setting -- Support and Confidence -- Association Rule Mining -- The Lift Measure -- Post Processing Association Rules -- Association Rule Extensions -- Applications of Association Rules -- SEQUENCE RULES -- SEGMENTATION -- Hierarchical Clustering -- K‐Means Clustering -- Self‐Organizing Maps -- Using and Interpreting Clustering Solutions -- NOTES -- CHAPTER 5 Survival Analysis -- SURVIVAL ANALYSIS MEASUREMENTS -- KAPLAN MEIER ANALYSIS -- PARAMETRIC SURVIVAL ANALYSIS -- PROPORTIONAL HAZARDS REGRESSION -- EXTENSIONS OF SURVIVAL ANALYSIS MODELS -- EVALUATING SURVIVAL ANALYSIS MODELS -- NOTES; CHAPTER 6 Social Network Analytics -- SOCIAL NETWORK DEFINITIONS -- SOCIAL NETWORK METRICS -- SOCIAL NETWORK LEARNING -- RELATIONAL NEIGHBOR CLASSIFIER -- PROBABILISTIC RELATIONAL NEIGHBOR CLASSIFIER -- RELATIONAL LOGISTIC REGRESSION -- COLLECTIVE INFERENCING -- EGONETS -- BIGRAPHS -- NOTES -- CHAPTER 7 Analytics: Putting It All to Work -- BACKTESTING ANALYTICAL MODELS -- Backtesting Classifi cation Models -- Backtesting Regression Models -- Backtesting Clustering Models -- Developing a Backtesting Framework -- BENCHMARKING -- DATA QUALITY -- SOFTWARE -- PRIVACY -- MODEL DESIGN AND DOCUMENTATION -- CORPORATE GOVERNANCE -- NOTES -- CHAPTER 8 Example Applications -- CREDIT RISK MODELING -- FRAUD DETECTION -- NET LIFT RESPONSE MODELING -- CHURN PREDICTION -- Churn Prediction Models -- Churn Prediction Process -- RECOMMENDER SYSTEMS -- Collaborative Filtering -- Content‐Based Filtering -- Demographic Filtering -- Knowledge-Based Filtering -- Hybrid Filtering -- Evaluation of Recommender Systems -- Examples -- WEB ANALYTICS -- Web Data Collection -- Web KPIs -- Turning Web KPIs into Actionable Insights -- Navigation Analysis -- Search Engine Marketing Analytics -- A/B and Multivariate Testing -- SOCIAL MEDIA ANALYTICS -- Social Networking Sites: B2B Advertisement Tools -- Sentiment Analysis -- Network Analytics -- BUSINESS PROCESS ANALYTICS -- Process Intelligence -- Process Mining and Analytics -- Coming Full Circle: Integrating with Data Analytics -- NOTES -- About the Author -- INDEX
N2  - The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities
UR  - https://ebookcentral.proquest.com/lib/buse-ebooks/detail.action?docID=1676384
ER  -