DATA ANALYTICS

Academic year
2021/2022 Syllabus of previous years
Official course title
DATA ANALYTICS
Course code
ET7024 (AF:332707 AR:179802)
Modality
On campus classes
ECTS credits
6
Degree level
Bachelor's Degree Programme
Educational sector code
SECS-S/03
Period
3rd Term
Course year
2
Where
RONCADE
Moodle
Go to Moodle page
Data Analytics provide management with relevant, accurate and valid information to support decision making. The focus of the course will be on marketing research, considering a variety of practical and technical aspects related to business environment and to quantitative measurement applied in real contexts. Fundamentals of multivariate statistics (such as factorial analysis and classification methods) will be illustrated and applied to develop marketing solutions, from customer satisfaction to brand positioning. The course aims to guide the student in the selection and learning of statistical tools, with particular attention to the interpretation of results in a marketing perspective. However, the approach we will go through is very general and applies to any area of management, not just marketing.
1. Knowledge and understanding
- To understand how to formulate a research design
- To know how to write a questionnaire
- To know the fundamentals of the multivariate techniques presented
- To understand the role of data analytics in the decision-making process

2. Ability to apply knowledge and understanding
- To implement the different multivariate techniques in R, from data imputation and coding to graphical representation
- Integrate secondary and primary data sources to address a business problem

3. Ability to judge:
- To develop marketing solutions through the appropriate statistical methods

4. Communication skills
- To communicate technically with the team work
- To present the research findings in a comprehensible format ready to be used by the management in the decision-making process

5. Learning skills
- Developing statistical solutions to management puzzles
- Learning by programming in R
- Learning by doing a complete case study of marketing research
- Learning by team working

Basic concepts of statistics and probability.
1. Introduction to marketing research
2. Research design formulation
a. Exploratory research design
b. Measurement and scaling
c. Questionnaire Design
d. Sampling
3. Data collection and Analysis
a. Basics of Business Analytics
b. Multivariate Analysis for Marketing Research
4. Report Preparation and Presentation
Malhotra, N.K., 2018, Marketing Research: An Applied Orientation (7th edition). Pearson.
The achievement of the course objectives will be assessed through the presentation of a team project work (40% of the final mark) and a written exam (60% of the final mark).
Lectures will be complemented by R lab sessions applied on a leading example.
English
written and oral
Definitive programme.
Last update of the programme: 12/07/2021