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  4. Postgraduate Program in Statistical Systems with a specialization in Official Statistics
  5. Business Intelligence

Business Intelligence

Objectives

The main goal of the Business Intelligence course that we now initiate 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 and Performance Management.

General characterization

Code

400131

Credits

6.0

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

Basic knowledge in Databases (SQL). A SQL Crash course is offered to the students who don't have this previous knowledge in the beginning of the semester.

Bibliography

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

§Larson, Brian (2017). Delivering Business Intelligence with Microsoft SQL Server 2016. Mc Graw Hill, ISBN: 978-1-25-964148-0

§Ferrari & Russo (2016). Introducing Microsoft Power BI, Microsoft Press
https://www.microsoftpressstore.com/store/introducing-microsoft-power-bi-9781509302284  

Teaching method

This course will include lectures and labs. In the lectures will consist of theoretical concepts, case studies and real world examples. The applied component of the course will include several computer labs where students will apply the concepts and theories presented in lectures leveraging the Microsoft Business Intelligence Platform (Power BI). In this context the students will have to develop a project.

Evaluation method

The assessment includes:

a) Project (50%)

b) Final exam (50%)

To successfully complete the course students must obtain a minimum score of 9.5 in the final exam (both seasons), irrespective of marks obtained in a) or b).

Subject matter

LECTURES

T.1 - Digital Transformation and Data-Driven Organizations

T.2 - Business Intelligence

T.3 - Data Warehousing

T.4 - Business Analytics

T.5 - Data, Text and Web Mining

T.6 - Business Performance Management

T.7 - Information Visualization

T.8 - Data Governance

LABS

L.1 ¿ Introduction to Power BI

L.2 ¿ Data Discovery

L.3 ¿ Data Engineering

L.4 ¿ Data Modelling

L.5 ¿ Data Visualization

L.6 ¿ Reporting & Dashboards

L.7 ¿ Advanced Analytics