81613 - Business Intelligence

Learning outcomes

The students is expert in the design, implementation and information systems management for intelligence of decisions that melt on the management knowledge of analytical nature. The second part (30 hours) of the course is developed in the computing laboratory using the system language of SAS System and SAS Enterprise Miner. At the end of the course, the student knows: - Customer relationship management (CRM) and Customer Intelligence; - Problems of evaluation of the advertising impact; - Oriented information system implementation for the analytical approach to the Business Intelligence; - Software realization for Analytical Business Intelligence projects and statistical data mining.

Course contents

This course provides an applied introduction to the main techniques of market research and
data analysis with a focus on their business applications. Compared to the bachelor’s course,
the master version is more concise (half the hours) and emphasizes technical
implementation and managerial use of results. The course covers: 1) overview of data types
in market research (commercial, administrative, survey data); 2) introduction to SAS
software for data management and descriptive analysis; 3) Multivariate descriptive
techniques: Factor Analysis, Principal Component Analysis (PCA), Cluster Analysis; 4)
analysis of categorical data: Chi-square test, Binary and Multiple Correspondence Analysis
(BCA, MCA); 5) application of data analysis to psychographic segmentation in CRM contexts;
6) focus on business interpretation of results rather than predictive modelling.


Structure of the course:
1. SAS software training - Hands-on training on the use of SAS for data management
and statistical modeling.
2. SAS software training (continued) - Continuation of practical exercises and lab work
using SAS.
3. Introduction to Statistics - Basic concepts: variables, distributions, central tendency,
and variability.
4. Introduction to Statistics (continued) - Applied examples and exercises on
descriptive statistics.
5. Analytical CRM - Use of data analysis to understand customer behavior and support
marketing strategies.
6. Principal Component Analysis (PCA) - Dimensionality reduction technique to
identify latent factors in multivariate data.
7. Clustering techniques - Unsupervised classification of individuals based on
similarity measures.
8. Clustering techniques (continued) - Application of clustering methods (e.g., k-
means, hierarchical) in CRM datasets.
9. Cluster description - Statistical profiling and naming of clusters based on their
distinctive traits.
10. CRM-based cluster interpretation and application - Strategic interpretation of
clusters for CRM, marketing segmentation, and targeting.

Readings/Bibliography

Data Mining and Statistics for Decision Making, Stephane Tuffery, Wiley, March 2011

Chapters: 7, 9, 11.1-11.3, 11.6

SAS ProgrammingThe One-Day Course - Neil Spencer Chapman and Hall/CRC 2003Print ISBN: 978-1-58488-409-5eBook ISBN: 978-0-203-49928-3

Teaching methods

Verification takes place through an individual oral exam in which the teacher asks technical questions about the methodological choices made in group work. The group works are carried out by groups of students (composed of a maximum of 3 or 4 subjects) who are formed independently and who carry out a real psychographic CRM project. The guidelines for the technical implementation of the group project are described during the course and in any case it involves applying the data analysis strategies addressed in the course to opinion data, collected by the group through an electronic questionnaire: definition of the topic, editing of the questionnaire, treatment of the distortion effects generated by the opinion scale, statistical modeling using the SAS software, drafting of the report to be delivered to the teacher.

Assessment methods

The exam is an individual oral discussion of a group work. The rating scale ranges from 1 to 30 and is a continuous indicator. The oral exam consists of 3/4 questions. The starting hypothesis is that the student knows the entire exam program perfectly and that, depending on the quality of his answers, starting from 30 (maximum grade) this grade can be reduced. The laude is awarded at the discretion of the teacher if the understanding of the technical topics of the course is particularly thorough in the methodological details.

Office hours

See the website of Furio Camillo