Published 2025
Table of Contents:
“...2.2.3.1 Correlation coefficient -- 2.2.3.2 Linear regression -- 2.2.3.3 Predictive analytics use cases -- 2.2.4 Prescriptive analytics -- 2.3 Evolution of
data analytics -- 2.3.1 SQL analytics: relational database management systems, online transaction
processing, and online analytic
processing -- 2.3.2 Business analytics: business intelligence,
data warehousing, and
data mining -- 2.3.2.1 Business intelligence -- 2.3.2.2
Data warehouses, star schema, and online analytic
processing cubes -- 2.3.2.3 Extract, transform, and
load tools -- 2.3.2.4 Online analytic
processing servers -- 2.3.2.5
Data mining -- 2.3.2.5.1 Frequent patterns -- 2.3.2.5.2 Classification -- 2.3.2.5.3 Cluster analysis -- 2.3.2.5.4 Outlier detection -- 2.3.2.5.5 Evolution analysis -- 2.3.2.5.6 Graph
data mining application -- 2.3.3 Visual analytics -- 2.3.4 Big
data analytics -- 2.3.5 Cognitive analytics -- 2.4
Data science -- 2.4.1
Data lifecycle -- 2.4.2
Data quality -- 2.4.3 Building and evaluating models -- 2.5 Tools and resources for
data analytics -- 2.6 Recent advances and trends in
data analytics -- 2.7 Conclusion -- 2.8 Questions and exercise problems -- References -- 3
Data science tools and techniques to support
data analytics in transportation applications -- 3.1 Introduction to the R
programming environment for
data analytics -- 3.2 Research
data exchange -- 3.3 Fundamental
data types and structures:
data frames and list -- 3.3.1
Data frame -- 3.3.2 List -- 3.4 Importing
data from external files -- 3.4.1 Delimited -- 3.4.2 XML -- 3.4.3 SQL -- 3.5 Ingesting online social media
data -- 3.5.1 Static search -- 3.5.2 Dynamic streaming -- 3.6
Data mining and machine learning techniques and libraries in Python -- 3.6.1 Python libraries for
data analytics -- 3.6.2 Unsupervised learning with clustering -- 3.6.3 Supervised learning with regression....
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