Business Analytics in Tourism

Objectives

None

General characterization

Code

400111

Credits

7.5

Responsible teacher

Miguel de Castro Simões Ferreira Neto

Hours

Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Prerequisites

 

The main topics covered in the course lectures are:

T.1 ¿ Business Intelligence for Tourism

T.2 ¿ Data Management

T.3 ¿ Data Warehousing

T.3 ¿ Business Analytics

T.4 ¿ Data Visualization and Dashboard Design

T.5 ¿ Data Security and Privacy

The main topics covered in the course Labs are

L.1 Storytelling with Dashboards (Microsoft Power BI)

Lab 1.1 - Data Discovery

Lab 1.2 - Data Engineering

Lab 1.3 - Data Modelling

Lab 1.4 - Data Visualization

Lab 1.5 - Reporting & Dashboards

Lab 1.6 - Advanced Analytics

Lab 1.7 ¿ Creating an End-to-End Solution

L.2  Geographic Information Systems (ARC GIS)

Lab 2.1 - Geospatial Technology as a Key to Tourism

Lab 2.2 - Power of Mapping Tourism

Lab 2.3 - How does GIS can work for tourism

 

Bibliography

Sharda, Delen & Turban (2017). Business Intelligence, Analytics, and Data Science: A Managerial Approach, Global Edition, ISBN: 9780134633282

Ferrari & Russo (2016). Introducing Microsoft Power BI, Microsoft Press, ISBN: 978-1-5093-0228-4

Additional references will be provided during the course aligned with each session content.

Teaching method

The final grade will be computed based on the following assessments:

a)      Project (60%)

   The Project will have two deliverables:

      i) Introductory Business Analysis (35% of the project grade and submitted on Moodle)  - ¿Business Needs Report¿ delivered by midterm where a company problem is presented and a potential solution is proposed using a Business Intelligence approach through a dashboard.

      ii) Decision Support Dashboard (65% of the project grade and shared on Microsoft PowerBI) - Delivery of the dashboard built with Microsoft Power BI containing the information (metrics) needed to support decision making within the context of the problem identified in the midterm report.

b) Final individual written exam (40%)

To successfully complete the course students must obtain a minimum score of 9.5 in the final exam, irrespective of the mark obtained in a).

Evaluation method

English

Subject matter

The course will have 14 sessions of 120 mn each and will be a mix of theory, case studies, real world cases presentations, and labs.

The lectures will include theoretical concepts, case studies and presentations.

The applied component of the course will include computer usage where students will apply the concepts and theories presented in lectures supported by the Microsoft  Power BI and ARC GIS. In this context the students will have to develop a group project.

The course will count heavily on the students¿ active participation, both in class and in its preparation. Students will be required to form teams.