Business Intelligence and Analytics

The Business Intelligence and Analytics curricular unit enables students to learn about, manage and develop the ability to propose Data
Analytics, Data Visualisation and, overall, Business Intelligence and Analytics solutions. To this end, and in a first phase, students will take
theoretical and practical classes where they learn to manipulate Self Service Business Intelligence tools (such as Tableau or Power BI) and
understand how data should be presented and communicated so that it can be understood by the public.
Few (2019) states that ‘we are not yet in the Information Age but in the Data Age’ and, given the multiplicity of data available to facilitate the
decision-making process, students will benefit if they are able to propose more efficient and effective solutions for the presentation of
information in their companies.
The Business Intelligence and Analytics course includes lectures with external guests on current research topics (it is essential that all
Master’s courses contribute to students feeling able to carry out research) in the area of BI, Business Analytics and application cases,
among others.
The teaching methodology is essentially ‘problem-based learning’ and ‘project-based learning’, encouraging students to propose solutions
to problems presented in class and to develop a project over the course of the semester. Even when it comes to writing a scientific article, it
is based on the project methodology as the student will have to hand in various stages of their work and receive feedback on each one in
order to move on to the next. The aim is to promote research and the publication of research articles with students,
The teaching methodology allows students to develop research and practical skills in specific areas of BI that the student considers to be
relevant to their training and/or their company.

Objectives:
OB1: to familiarise students with the potential of Business Intelligence processes and the operational systems that support them
OB2: learn about current information technologies and methodologies for developing Business Intelligence solutions for data-driven
companies
OB3: learn about the main trends in tools for data visualisation and task automation
OB4: know how to use a data visualisation tool and implement the entire data analysis circuit, with a critical sense of the solutions to be
used.
Competences:
C1) scientific and research: knowledge of the main authors and most recent studies and trends on the themes of this area in Business
Intelligence and Analytics.
2) of a practical nature, namely that students learn about, manage and develop the ability to propose Data Analytics, Data Visualisation and,
overall, Business Intelligence and Analytics solutions.

1.- Data-driven Decisions
1.1 Importance of data-driven decisions
1.2 Frameworks for informed decision-making
1.3 Main challenges and pitfalls in using data
2 – Business Intelligence & Analytics
2.1 Fundamentals of BI and Analytics
2.2 Types of BI analyses
2.3 Components of a BI solution
2.4 Key indicators and metrics (KPIs)
3 – Data governance, culture and data curation
3.1 Fundamentals of data governance
3.2 Data-driven culture
3.3 Data curation and quality
4 – Process automation
4.1 Introduction to automation in BI
4.2 Robotic Process Automation (RPA) and BI
4.3 Machine Learning and Artificial Intelligence in BI
5 – Tools for analysing data
5.1 Overview of BI tools
5.2 Languages and technologies for analysing data
5.3 Comparison of tools and selection criteria
6- Business Intelligence and Analytics project
6.1 Project planning
6.2 Building and implementing the solution
6.3 Project evaluation and presentation

NAO