Base Knowledge
Basic knowledge of data analysis and database management systems is recommended.
Teaching Methodologies
The teaching/learning methods include:
– Expositive.
– Experimental.
– Participatory.
– Auto-evaluation and peer-evaluation.
– Autonomous work.
Learning Results
The objectives of the Business Intelligence (BI) curricular unit (UC) are to provide students with the ability to:
– Analyze and present the latest research in the area of BI.
– Know the fundamental principles of design of the different types of BI applications for data-based decision making.
– Know and apply the fundamental principles of data visualization for BI systems and decision support.
– Guide, evaluate and analyze BI projects, namely design, and criticize different BI applications to support decision-making at operational, tactical and strategic level.
– Draw and develop BI applications.
– Analyze, criticize and draw standard reports, dashboards and scorecards for decision making.
– Define performance indicators with different levels of aggregation. Know, understand, and use Key Performance Indicators (KPIs).
Program
1. Introduction to Business Intelligence and Analytics (BI&A).
Definition of BI&A.
Key concepts and techniques in BI&A.
Types of BI&A systems and tools.
Evaluation and selection of BI&A softwares.
The role of Business Intelligence in organizations.
2. Key Performance Indicators (KPIs) and Scorecards.
Definition and types of KPIs and Scorecards.
Relationship between Scorecards and KPIs.
Types of KPIs and Scorecards.
Identify and select KPIs.
Creating and implementing KPIs and Scorecards.
3. Visualization and Dashboards.
Introduction to data visualization and importance of visualization in BI&A.
Types of data visualizations techniques.
Definition of dashboards and their purpose.
How to choose the right visualization for the data.
Designing and building effective and informative dashboards.
4. Research, case studies, applications, and projects.
Overview of BI&A implementations.
Analysis and comparison of BI&A solutions.
BI&A research.
Exercises using real-world data.
Analysis and building of dashboards in a real-world scenario.
Curricular Unit Teachers
Internship(s)
NAO
Bibliography
Available at ISEC:
– Allington, M. (2021). Supercharge Power BI : Power BI is better when you learn to write DAX, thirth edition. Holy Macro! Books (1A-19-52 (ISEC) – 19140)
– B-On. (n.d.). Retrieved 2023, from https://www.b-on.pt/
– Correia, F. B. (2024). Material para BI, from página web de BI
– Grossmann, W., Rinderle-Ma, S. (2015). Fundamentals of business intelligence, Springer (1A-19-50 (ISEC) – 17904)
– Turban, E., et al. (2008) Business intelligence: a managerial approach. Pearson international (1A-19-8 (ISEC) – 14234)
– Santos, M. Y., Ramos, I. (2006). Business intelligence: tecnologias da informação na gestão de conhecimento. FCA (1A-19-2 (ISEC) – 13711; 1A-19-15 (ISEC) – 14771)
– Grossmann, W., Rinderle-Ma, S. (2015). Fundamentals of business intelligence, Springer (1A-19-50 (ISEC) – 17904)
Not available at ISEC:
– Carvalho, A. (2019). Exercícios de Power BI – Importação e visualização de dados. FCA Editor
– Eckerson, W.W. (2010). Performance Dashboards: Measuring, Monitoring, and Managing Your Business, second Edition, Wiley
– Evergreen, Stephanie (2016). Effective Data Visualization: The Right Chart for the Right
Data. USA. SAGE Publications Ltd
– Healy K. (2018). Data Visualization: A Practical Introduction, first edition. Princeton University Press
– Jones, B. (2014). Communicating Data with Tableau: Designing, Developing, and Delivering Data Visualizations, first edition, O’Reilly Media
– Kaplan, R.S., Norton, D.P. (1996). The Balanced Scorecard: Translating Strategy into Action, first edition, Harvard Business School Press
– Kaplan R., Norton D. P. (2004) Strategy Maps: Converting Intangible Assets into Tangible Outcomes, Harvard Business School Press
– Knight, D., Ostrowsky, E., Pearson, M., Schacht, B. (2022). Microsoft Power BI Quick Start Guide: The ultimate beginner’s guide to data modeling, visualization, digital storytelling, and more, thirth Edition. Packt Publishing
– Milligan, J. (2022). Learning Tableau 2022: Create effective data visualizations, build interactive visual analytics, and improve your data storytelling capabilities, fifth edition. Packt Publishing
– Magalhães, A. (2017). Business Intelligence no SQL Server. FCA Editor
– Murray, D. G., Chabot, C. (2013). Tableau Your Data! Fast and Easy Visual Analysis with Tableau Software, first edition, Wiley
– Niven, P. R. (2006). Balanced scorecard step-by-step, second edition, John Wiley & Sons
– Nogueira, N. (2018). Power BI – para gestão e finanças. FCA
– Parmenter, D. (2019). Key Performance Indicators: Developing, Implementing, and Using Winning KPIs, fourth Edition, Wiley
– Person, R. (2013). Balanced Scorecards and Operational Dashboards with Microsoft Excel, 2nd Edition. Wiley
– Powell, B. (2018) Mastering Microsoft Power BI: Expert techniques for effective data analytics and business intelligence. Packt Publishing
– Russo, J. (2015). Balanced scorecard para PME e pequenas e médias instituições, Lidel
– Santos, M. Y., Ramos, I. (2017). Business Intelligence – da informação ao conhecimento, thirth updated edition. FCA
– Sharda, R., Delen, D., & Turban, E., King, D. (2018). Business Intelligence: A Managerial Approach, Global Edition, fourth edition. Pearson
– Vasconcelos, J. B., Barão, A. (2017). Ciência dos dados nas organizações – aplicações em Python. FCA
– Wexler, S., Shaffer, J., and Cotgreave, A. (2017) The Big Book of Dashboards: Visualizing Your Data -Using Real-World Business Scenarios. John Wiley & Sons Inc
– Wilke, C. O. (2019). Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures, first edition, O’Reilly Media