Analytics in a Big Data World: The Essential Guide to Data Science and its Applications 1st Edition by Bart Baesens – Ebook PDF Instant Download/Delivery: 1118892704, 978-1118892701
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ISBN 10: 1118892704
ISBN 13: 978-1118892701
Author: Bart Baesens
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.
Analytics in a Big Data World The Essential Guide to Data Science and its Applications 1st Table of contents:
Chapter 1 Big Data and Analytics
Example Applications
Basic Nomenclature
Analytics Process Model
Job Profiles Involved
Analytics
Analytical Model Requirements
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
Chapter 3 Predictive Analytics
Target Definition
Linear Regression
Logistic Regression
Decision Trees
Neural Networks
Support Vector Machines
Ensemble Methods
Multiclass Classification Techniques
Evaluating Predictive Models
Chapter 4 Descriptive Analytics
Association Rules
Sequence Rules
Segmentation
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
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
Chapter 7 Analytics: Putting It All to Work
Backtesting Analytical Models
Benchmarking
Data Quality
Software
Privacy
Model Design and Documentation
Corporate Governance
Chapter 8 Example Applications
Credit Risk Modeling
Fraud Detection
Net Lift Response Modeling
Churn Prediction
Recommender Systems
Web Analytics
Social Media Analytics
Business Process Analytics
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