Tools for Data Analysis

Category: Discipline
  • Afonso, A., e Nunes, C. (2011). Probabilidades e Estatística: Aplicações e Soluções em SPSS. Lisboa, Portugal: Edições Sílabo. Guimarães, R. C., e Cabral, J. S. (2010). Estatística (2ª edição) . Lisboa, Portugal: Verlag Dashöfer Portugal. Murteira, B., Ribeiro, C. S., Silva, J. A., e Pimenta, C. (2015). Introdução à Estatística (3ª edição) . Lisboa, Portugal: Escolar Editora. Pestana, M. H., e Gageiro, J. N. (2014). Análise de Dados para Ciências Sociais - A Complementaridade do SPSS (6ª edição) . Lisboa, Portugal: Edições Sílabo Gomes, C. (2020). Material de Apoio à Unidade Curricular de Estatística. ISLA-Instituto Politécnico de Gestão e Tecnologia. Kazmier, L. (1982). Estatística Aplicada a Economia e Administração . Schaum McGraw-Hill. Reis, E. (2008). Estatística Descritiva (7ª ed.). Edições Sílabo.Estatística, Newman, J. (2021) The Microsoft Office 365 Handbook - Everything You Need To Know About Microsoft Office 365      
  • Sales and Marketing Management
  • 6739
  • 25037
  • Tools for Data Analysis
  • ISLA Gaia6739-25037
  • 1
  • 6
  • 0
  • 27
  • Não
  • Português
  • Classes are of a theoretical and practical nature, where the theoretical exposition of the syllabus is accompanied by the presentation of practical examples and exercises. The evaluation is carried out taking into account the assessment regulation Regulamento Geral de Avaliação da Universidade Lusófona do Porto. Pedagogical innovation practices : Pedagogical practices will be mediated by Information and Communication Technologies, using computers and/or mobile devices. Students will be exposed to interactive educational resources, such as quizzes. Problem-based learning will be promoted, where the students, guided by the teacher, should identify problems and plan and carry out resolution paths. The aim is to improve the teaching and learning process, to provide students with the necessary skills for the challenges currently facing humanity, and to increase their motivation in relation to the course
  • Mandatory
  • Presentation of techniques for analysing and interpreting data commonly used in empirical research and in the world of work. To provide students with a set of statistical techniques and methods that facilitate the analysis and interpretation of information. Students should understand theoretical probability distributions and recognise their applicability in concrete cases; understand the meaning of confidence intervals, hypothesis tests and linear regression; develop the ability to use a set of statistical techniques and methods that facilitate the analysis and interpretation of information, using software such as Excel (with a focus on Pivot Tables) and Power-BI.
  • Probability distributions of continuous variables Exponential distribution Normal distribution t-Student distribution Confidence intervals Confidence intervals for mean, difference of means, proportion, difference of proportions, variance, ratio of variances Hypothesis testing Test of the value of the mean, comparison of means, proportions, comparison of proportions, variance, comparison of variances Linear Regression Simple linear regression Scatter diagram Least squares method Standard error of estimate Coefficients of determination and correlation  Spreadsheets - Ms Excel Selecting, inserting, editing and working with cells Spreadsheets and basic operators Formatting, formulas and functions Outputs - spreadsheet configuration and printing Dynamic tables and graphs. Dashboards Power-BI

  • Avaliação Contínua

    DATA

    PESO

    1º Momento - Teste Teórico

    23/3/2026

     

    50%

    2º Momento - Trabalho + Defesa

    18/5/2026

    50%

    TAG

    25/5/2024

    100%

    Observações:

    a) Os alunos terão de optar entre a realização dos Testes intermédios ou a realização do Teste de Avaliação Global. Se o aluno tiver nota inferior a 7,5 valores no 1º Teste ou desistir, não pode comparecer ao 2º Teste. A aprovação na avaliação curricular implica nota final não inferior a 9,5 valores. Os alunos não podem ter nota inferior a 7,5 valores em cada um dos testes.

    b) Todos os alunos inscritos à unidade curricular podem realizar o exame final na época normal desde que não tenham realizado ou obtido aprovação na avaliação curricular
  • Semestral
  • The business world has lived through times of great instability and any decision that has to be taken can be crucial in differentiating between the success or failure of a company, in the market in which it operates. Data collection is the first stage of the empirical study. At a later stage, the treatment and analysis of the data are essential for carrying out an investigation related to a specific problem, as it allows researchers to obtain reasoned conclusions. Thus, in order to better sustain decisions, it is imperative to plan the investigation, collect, process and analyze the data, concluding this process with the sharing of the results obtained. The process of analyzing and interpreting data is a laborious and demanding task that makes it possible to achieve the main objective of a research project: the production of scientific knowledge!

Marketing and Advertising

Category: Discipline
  • Aaker, D. (2005). Strategic market management (7ª ed). John Wiley & Sons, NY. Bingham JR, F., et all (2005) Business marketing (3ª ed), McGraw-Hill, NY. Détrie, J.P. (2000). Strategor (3ª ed), D. Quixote, Lisboa. Farris, paul; Bendle, N. & Pfeifer, P. (2010). Marketing Metrics: The Definitive Guide to Measuring Marketing Performance (2nd Edition). Person, NY Kotler, P. (2002). Marketing Management. Prentice-hall, 11ª ed., NY Pride, W. & Ferrel (2013). Marketing 2014. South-Western Cengage. Mason
  • Accounting and Management
  • 2187
  • 3692
  • Marketing and Advertising
  • ISLA Gaia2187-3692
  • 2
  • 6
  • 0
  • 27
  • Não
  • Português
  • Teaching methodology: Theoretical classes - Expositive and interrogative method. Individual and group work. Presentations and discussion - Active and participatory method. Evaluation methodology: a) Curricular Evaluation (according to the Pedagogical Regulation of the CTeSP) Realization and presentation of an individual work (45%, minimum score 7) Test (45%, minimum score 7) Attendance and Attitudes (10%) Test: Penultimate lesson Presentation and defense of the Works: Last lesson b) Final Evaluation All students will be entitled to a final exam, to be held in an evaluation season. Observations: - No oral exams will be taken in this Curriculum Unit.
  • Mandatory
  • This course aims to provide students in the Higher Technical Diploma in Sales and Marketing Management with a comprehensive understanding of the principles and practices of marketing and advertising. Students will be equipped to analyze the market, develop effective marketing strategies, manage the marketing mix (product, price, distribution, and communication), and understand the significance of advertising as a promotional tool. Students will be encouraged to apply theoretical knowledge in practical contexts, preparing them to face real-world challenges in the professional sphere.
  • 1 - The concept, function, evolution and nature of marketing 2 - Marketing strategy and plan 3 - Internal marketing diagnosis 4 - Marketing-mix variables: the Product 5 - The brand 6 - Marketing-mix variables: Price 7 - Marketing-mix variables: Distribution 8 - Marketing-mix variables: Communication 9 - The Advertising variable of the Communication Mix 10 - Diagnosis of the company's customers 11 - External marketing diagnosis 12 - Market analysis 13 - SWOT analysis 14 - Strategic marketing decisions 15 - Marketing strategies 16 - Marketing action plans 17- Marketing disciplines  

  •  

    Descrição

    Data limite

    Ponderação

    Teste de Avaliação Global (TAG)

    dd-mm-yyyy

    45%

    Apresentação e defesa dos trabalhos

    dd-mm-yyyy

    45%

    Assiduidade, pontualidade e empenho

    ---------------

    10%

     

    Adicionalmente poderão ser incluídas informações gerais, como por exemplo, referência ao tipo de acompanhamento a prestar ao estudante na realização dos trabalhos; referências bibliográficas e websites úteis; indicações para a redação de trabalho escrito...

     
  • Semestral
  • This course aims to provide students with knowledge and mastery of the basic and transversal concepts of Marketing and Advertising. To enable students to apply Marketing techniques to the creation and development of communication products or services in a working context. To analyze the importance of marketing for companies in general and communication in particular in the current global context.

Representation of Multimedia Elements

Category: Discipline
  • Adobe Press, Adobe Audition CC Classroom in a Book, 2nd Edition, 2018 Adobe Press Adobe Illustrator Classroom in a Book (2020 release), 2020 Adobe Press Adobe Premiere Pro Classroom in a Book (2020 release), 2020 Adobe Press Adobe Photoshop Elements 2020 Classroom in a Book, 2020 Adobe Press Li, Z. N., Drew, M. S., Liu, J. Fundamentals of Multimedia, Springer International Publishing, 2014. Ribeiro, N. M. Multimédia e Tecnologias Interativas, FCA, 2012. Wallace, Jackson. Digital Image Compositing Fundamentals, Apress, 2015. Wallace, Jackson. Digital Video Editing Fundamentals, Apress, 2015
  • Digital Communication
  • 2201
  • 24102
  • Representation of Multimedia Elements
  • ISLA Gaia2201-24102
  • 1
  • 6
  • 0
  • 27
  • Não
  • Português
  • This course unit has two components: theoretical and practical. Classes will start with an approach to the definitions and theoretical concepts of the subjects. These will later be applied in the practical execution of worksheets, using the techniques learned with specific software. Group work will be promoted with presentations to other class members. Curricular Assessment: In-class assignments: 10% Theoretical-practical work I (Project and Report): 35% Theoretical-practical work  II (Project and Report): 55%   Exame All students who have not successfully completed the assessment may take a final theoretical-practical exam in the assessment period defined by the institution.
  • Mandatory
  • The curricular unit is intended for the student to learn the fundamentals on the following subjects: media and multimedia; digitization; compression; color and color coding; digital imaging; digital image compression; digital sound; digital video. At the end of the curricular unit, the student should be able to understand and explain the fundamentals of the processes involved in the computer representation of multimedia elements such as texts, images, sound, and video, as well as develop audiovisual projects with the concepts and techniques learned. In the context of learning social skills, it is intended to strengthen the capacities and attitudes of accountability and solidarity in the realization of group work projects.
  • 1. Multimedia Concepts and Definition Interactive Multimedia Applications Multimedia Project 2. Digital Data Representation Analog vs Digital Digitalization Process 3. Data Compression Techniques Entropy Coding Techniques Source Coding Techniques Compression and Decompression 4. Media, Concepts, Modalities Perception, Representation Storage, and Transmission Media Acquisition (image, sound, and video) Interaction: Input and Output Devices. Storage. 5. Digital Image Representation and Processing Color and Color Encoding: Color Models Compression and Image Formats Vector Image Processing Programs Bitmap and Raster Image Processing Programs 6. Digital Video and Audio Video Compression and Formats Audio Compression and Formats

  • Descrição dos instrumentos de avaliação (individuais e de grupo) ¿ testes, trabalhos práticos, relatórios, projetos... respetivas datas de entrega/apresentação... e ponderação na nota final.

    Exemplo:

    Descrição

    Data limite

    Ponderação

    Trabalhos em contexto de aula

    dd-mm-yyyy

    10%

    Trabalho prático I 

    dd-mm-yyyy

    35% 

    Trabalho prática II

     

    55%

     

    Todos os estudantes que não tenham concluído com sucesso a avaliação podem realizar um exame teórico-prático final na época avaliação definida pela instituição.

     
  • Semestral
  • The curricular unit allows students to acquire fundamental concepts that enable the understanding of multimedia, digital design and understand the capabilities of text, image, audio and video in visual communication.

Fundamentals of Business Intelligence and Data Analysis

Category: Discipline
  • Deckler, G. (2022). Learn Power BI Second Edition. A comprehensive, step-by-step guide for beginners to learn real-world business intelligence. Editor: Packt Publishing. ISBN: 9781801810074. Meier, M., Baldwin, D., Strachnyi, K., (2021), Mastering Tableau 2021: Implement advanced business intelligence techniques and analytics with Tableau, 3rd Edition, Packt. O'Connor, E. (2018), Microsoft Power BI Dashboards Step by Step, 1st Edition, Microsoft. Santos, M., Y., Ramos, I. (2017). Business Intelligence da Informação ao Conhecimento. Data Science. FCA. Shmueli, G., Bruce, P. C., Gedeck, P., & Patel, N. R. (2019). Data mining for business analytics: Concepts, techniques, and applications in Python. Wiley. Raschka, S., & Mirjalili, V. (2019). Python machine learning: Machine learning and deep learning with Python, scikit-learn, and TensorFlow 2 (3rd ed.). Packt Publishing.  
  • Analytics and Business Data Science
  • 6416
  • 24860
  • Fundamentals of Business Intelligence and Data Analysis
  • ISLA Gaia6416-24860
  • 1
  • 2
  • 0
  • 27
  • Não
  • Português
  • The teaching methodology consists of the presentation and discussion of topics, and whenever possible present existing technologies, through the implementation of application examples that demonstrate the concepts involved. At the end of each topic, exercises are proposed to consolidate learning. Assessment methodology: Curricular Assessment: Practical work with a weight of 100% in the final grade.
  • Mandatory
  • Understand how to use business intelligence and data analytics to outperform traditional companies in your industry. Learn effective data visualisation (Dashboards and Reports) with Power BI. Develop social skills (soft skills), namely teamwork and collaboration, communication, critical and agile thinking. Understanding and implementing types of analytics (descriptive, predictive, and prescriptive); - The role of data science in decision support and business value creation; - The KDD (Knowledge Discovery in Databases) process; - Data mining.
  • Description of contents Data, Information, Knowledge and Intelligence Fundamental concepts, data, information, knowledge, and intelligence. Importance of data quality in decision-making. ¿Data Mining Concept of ETL and the stages of the process. Examples of application in an organisational context ETL (Extract, Transform, Load) Stages of the ETL process and BI. Examples of data integration tools. Analytics e Data Science Types of analytics (descriptive, predictive, and prescriptive). Role of Data Science. KDD process. Data mining.   Business Intelligence ¿BI concept and objectives. Key performance indicators (KPIs) Business Intelligence Architecture ¿Components and layers of a BI architecture (data sources, staging, data warehouse, data marts). Overview of OLAP and dimensional models. Power BI Introduction to Power BI and the data model. Construction of interactive reports and dashboards to support decision-making.    

  • Descrição dos instrumentos de avaliação (individuais e de grupo) ¿ testes, trabalhos práticos, relatórios, projetos... respetivas datas de entrega/apresentação... e ponderação na nota final.

    Exemplo:

    Descrição

    Data limite

    Ponderação

    Trabalho prático

     

    100%

     

     

     

     

     

     

     

    Adicionalmente poderão ser incluídas informações gerais, como por exemplo, referência ao tipo de acompanhamento a prestar ao estudante na realização dos trabalhos; referências bibliográficas e websites úteis; indicações para a redação de trabalho escrito...

     
  • Anual
  • The main objective of this course is to introduce students to the potential of decision-making in organisations based on large data sets and their analysis in the context of Business Intelligence and data analysis. To promote understanding of data based on visualisation and the presentation of clear and strategic reports. Understand ETL (Extract, Transform, Load) processes, Analytics and Data Science KDD (Knowledge Discovery in Databases) and Data Mining. Understand how to use Business Intelligence and data analysis to support strategy formulation and decision-making. Learn effective data visualisation (Dashboards and Reports). Develop social skills, namely teamwork and collaboration, communication, critical and agile thinking.

Principles of Corporate Finance

Category: Discipline
  • FERNANDES, Carla et all; "Análise Financeira - Teoria e Prática" (5ª Edição); Edições Sílabo, 2019 NEVES, João Carvalho, "Análise e Relato Financeiro - Uma Visão Integrada de Gestão", 5ª edição, Texto Editores, 2012
  • Accounting and Management
  • 2187
  • 15136
  • Principles of Corporate Finance
  • ISLA Gaia2187-15136
  • 2
  • 6
  • 0
  • 27
  • Não
  • Português
  • Project-Based Learning (PBL) - Students work on practical projects that address real-world problems, encouraging the application of knowledge in concrete situations. Personalized Learning supported by Philix - Digital Tutor
  • Mandatory
  • At the end of the course unit the student should be able to assess the economic and financial performance of a company.
  • The objectives of financial analysis The phases of the financial diagnosis The financial analysis documents Financial analysis techniques Performance evaluation using the ratios method Analysis of financial balance Integrated profitability analysis Risk analysis Cash flow analysis
    • Teste de avaliação global (50%) em data a definir com os alunos
    • Trabalho de Grupo (40%) em data a apresentar e a entregar a definir com os alunos
    • Assiduidade (10%)
  • Semestral
  • The aim of this course is to provide students with the necessary techniques and instruments for assessing the company's financial situation and performance.
  1. Behavior and Organizational Communication
  2. Administrative Management of Human Resources
  3. Data Analysis Tools
  4. Critical Thinking and Argumentation

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