Bart Baesens [Bart Baesens] - Analytics in a Big Data World: The Essential Guide to Data Science and its Applications
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- Book:Analytics in a Big Data World: The Essential Guide to Data Science and its Applications
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Analytics in a Big Data World: The Essential Guide to Data Science and its Applications: summary, description and annotation
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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 authors 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.
Bart Baesens [Bart Baesens]: author's other books
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Bart Baesens is an associate professor at KU Leuven (Belgium) and a lecturer at the University of Southampton (United Kingdom). He has done extensive research on analytics, customer relationship management, web analytics, fraud detection, and credit risk management (see www.dataminingapps.com). His findings have been published in well-known international journals (e.g., Machine Learning, Management Science, IEEE Transactions on Neural Networks, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Evolutionary Computation, and Journal of Machine Learning Research) and presented at top international conferences. He is also co-author of the book Credit Risk Management: Basic Concepts (Oxford University Press, 2008). He regularly tutors, advises, and provides consulting support to international firms with respect to their analytics and credit risk management strategy.
- A priori property
- A/B testing
- Accessibility
- Accountability principle
- Accuracy ratio (AR)
- Accuracy
- Action plan
- ActiTrac
- Activation function
- Active learning
- Actuarial method
- Adaboost
- Alpha algorithm
- Alter
- Amazon
- Analytical model requirements
- Analytics
- process model
- Anatomization
- ANOVA
- Apache/NCSA
- API
- Apriori algorithm
- Area under the ROC curve (AUC)
- benchmarks
- Assignment decision
- Association rules
- extensions
- mining
- multilevel
- post processing
- Attrition
- Backpropagation learning
- B2B advertisement tools
- Backtesting
- classification models
- clustering models
- framework
- policy
- regression models
- Bagging
- Bar chart
- Basel II
- Basel III
- Basic nomenclature
- Behavioral scoring
- Behavioral targeting
- Believability
- Benchmark
- expertbased
- external
- Benchmarking
- Best matching unit (BMU)
- Betweenness
- Bias term
- Bid term
- Bigraph
- Binary rating
- Binning
- Binomial test
- Black box
- techniques
- Board of Directors
- Boosting
- Bootstrapping procedures
- Bounce rate
- Box plot
- Brier score
- Bureau-based inference
- Business activity monitoring (BAM)
- Business expert
- Business intelligence
- Business process analytics
- Business process lifecycle
- Business process management (BPM)
- Business process modeling language (BPMN)
- Business process
- Business relevance
- Business-to-Business (B2B)
- Business-to-Consumer (B2C)
- C4.5 (See5)
- Capping
- Cart abandonment rate
- CART
- Case-based recommenders
- Categorization
- Censoring
- interval
- left
- right
- Centrality measures
- CHAID
- Champion-challenger
- Checkout abandonment rate
- Chief Analytics Officer (CAO)
- Chi-squared
- analysis
- Churn prediction
- models
- process
- Churn
- active
- expected
- forced
- passive
- Classification accuracy
- Classification error
- Classing
- Click density
- Clique
- Cloglog
- Closeness
- Clustering
- Clustering, Using and Interpreting
- Coarse classification
- Cold start problem
- Collaborative filtering
- Collection limitation principle
- Collective inference
- Column completeness
- Combined log format
- Commercial software
- Common log format
- Community mining
- Competing risks
- Completeness
- Compliance
- Component plane
- Comprehensibility
- Conditional density
- Confidence
- Conformance checking
- Confusion matrix
- Conjugate gradient
- Consistency
- Constraint-based recommenders
- Content based filtering
- Continuous process improvement
- Control group
- Conversion rate
- Convex optimization
- Cookie stealing
- Cookies
- first-party
- persistent
- session
- third-party
- Corporate governance
- Corporate performance management (CPM)
- Correlational behavior
- Corruption perception index (CPI)
- Coverage
- Cramer's V
- Crawl statistics report
- Credit conversion factor (CCF)
- Credit rating agencies
- Credit risk modeling
- Credit scoring
- Cross-validation
- Leave-one-out
- Stratified
- Cumulative accuracy profile (CAP)
- Customer acquisition
- Customer attrition
- Customer lifetime value (CLV)
- Customer retention
- Cutoff
- Dashboard
- Data cleaning
- Data mining
- Data poolers
- Data publisher
- Data quality
- dimensions
- principle
- Data science
- Data set split up
- Data sparsity
- Data stability
- Data warehouse administrator
- Database
- Decimal scaling
- Decision trees
- multiclass
- Decompositional techniques
- Defection
- Degree
- Demographic filtering
- Dendrogram
- Department of Homeland Security
- Dependent sorting
- Development sample
- Deviation index
- Difference score model
- Digital analytics association (DAA)
- Digital dashboard
- Disco
- Distance measures
- Euclidean
- Kolmogorov-Smirnov
- Mahalanobis
- Manhattan
- Distribution
- Bernoulli
- Binomial
- Exponential
- Generalized gamma
- Normal
- Weibull
- Divergence metric
- Document management system
- Documentation test
- Doubling amount
- Economic cost
- Edge
- Effects
- external
- internal
- Ego
- Egonet
- Ensemble
- methods
- model
- Entropy
- Epochs
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