The main goal of the Business Intelligence course is to give the students the knowledge and competences related with decision support capacities provided by the Business Intelligence processes and the supporting Data Warehouses, including the Business Intelligence development methodologies and the nowadays available information technologies in the field of Business Analytics, Data Visualization and Dashboarding.
Miguel de Castro Neto
Weekly - Available soon
Total - Available soon
Previous basic knowledge in databases and SQL is recommended.
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.
Other materials will be posted on Moodle.
The course will have 12 sessions of 2x90mn 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 from leading BI vendors and real world BI projects.
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 Business Intelligence Platform and Power BI. 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 according to MCO group affiliation list.
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 no later than March 11)
'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 no later than May 20)
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) Continuous evaluation (10%)
During the course the students will be evaluated with assignments, including classroom presentation and discussion.
c) Final individual written exam (30%)
To successfully complete the course students must obtain a minimum score of 9.5 in the final examination, irrespective of marks obtained in a) or b).
The main topics covered in the course lectures are:
T.1 – Digital Transformation and Data-Driven Organizations;
T.1 – Business Intelligence;
T.2 – Data Warehousing;
T.3 – Business Analytics;
T.4 – Text and Web Mining;
T.5 – Business Performance Management;
T.6 – Data Visualization and Dashboard Design;
T.7 – Data Security and Privacy<;
Labs – Storytelling with Dashboards (Microsoft Power BI)
Lab 1 – Introduction;
Lab 2 – Data Discovery;
Lab 3 – Data Engineering;
Lab 4 – Data Modelling;
Lab 5 – Data Visualization;
Lab 6 – Reporting & Dashboards;>/p>
Lab 7 – Advanced Analytics;
Lab 8 – Creating an End-to-End Solution.