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Implementation of ISO 22301 and IT Business Continuity Management at VWDS Strategies and Business Plan for Critical Scenarios
No full textNa era digital atual, as empresas enfrentam desafios significativos em manter operações contínuas durante eventos disruptivos e cenários críticos.
Esta tese aborda o desafio de implementar eficazmente a norma ISO 22301:2019 para Gestão da Continuidade do Negócio focado em IT, na Volkswagen Digital Solutions, integrando um padrão internacional no contexto operacional de uma empresa de um grupo líder de soluções digitais na indústria automóvel, o Volkswagen Group.
A integração da ISO 22301:2019 é complexa devido à necessidade de adaptar o contexto operacional específico da VWDS, assegurando resiliência e melhoria de desempenho. A abordagem envolve uma análise detalhada e um plano de implementação dentro da VWDS, focado em aumentar a eficiência organizacional e operacional contra cenários críticos, através de uma Análise do Impacto no Negócio rigorosa, gestão de riscos e desenvolvimento de estratégias de continuidade do negócio adaptadas às necessidades da empresa.In today's digital era, businesses face significant challenges in maintaining continuous operations during disruptive events and critical scenarios.
The work addresses the challenge of effectively implementing ISO 22301:2019 standards for IT Business Continuity Management within Volkswagen Digital Solutions, integrating an international standard into a company of a leading digital solutions provider's operational context in the automotive industry, Volkswagen Group.
The integration of ISO 22301:2019 is complex due to the need to adapt VWDS's specific operational context, ensuring resilience and performance enhancement. The approach involves a detailed analysis and implementation plan within VWDS, focusing on enhancing organisational and operational efficiency against critical scenarios, through rigorous BIA, risk management, and development of business continuity strategies adapted to the company's needs
What is the viability of investing in autonomous energy storage systems in Portugal
No full textThis thesis explores the viability of investing in autonomous energy storage systems in
Portugal. With the European Union's commitment to greener energy solutions and
Portugal's aims to be carbon neutral by 2050, there is a growing need for systems that
ensure grid stability while integrating renewable energy sources. This study analyzes the
potential of energy storage systems to provide crucial flexibility services to grid operators
like REN and E-REDES. By examining market trends, regulatory frameworks, and
economic factors, this research provides insights into the opportunities and challenges
associated with developing a sustainable energy storage infrastructure in Portugal
Machine Learning for Credit Card User Segmentation in the Financial Sector
No full textDissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe competitive landscape of the financial sector requires innovative approaches in
marketing, prompting banking institutions to integrate data science methodologies. This study
aims to bridge the gap in delivering personalized customer experiences by transitioning from
traditional rule-based segmentation to data-driven segmentation using machine learning.
Focusing on credit card users from a confidential European financial institution, we propose
the development of multiple machine learning models to segment customers based on their
purchasing behavior. Several clustering algorithms were evaluated, including K-means,
Hierarchical Clustering, Gaussian Mixture (GMM), and DBSCAN. The goal is to provide
actionable insights to the marketing team, enabling them to make informed decisions
regarding marketing campaigns and fostering more personalized customer relationships. We
define and utilize various data sources, establish exclusion rules, and apply statistical
techniques to ensure data quality and relevance. By employing diverse clustering algorithms,
we aim to create dynamic customer segments that can inform personalized marketing
strategies. Based on existing literature, it is anticipated that data-driven segmentation will
enhance customer satisfaction, retention, and marketing efficiency. This research contributes
to the financial marketing field by providing a robust framework for customer segmentation
and offering insights into customer behaviors and preferences, which is expected to drive
business growth
Designing and Implementing a Metadata-driven Modern Data Warehouse: Automating ELT Processes through Metadata-Driven Pipelines
No full textDissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe increasing volume, variety, and velocity of data have exposed the limitations of traditional
data warehouses and sparked a transformative shift towards modern, cloud-based solutions.
These modern data warehouses (MDW) are not just about scalability, flexibility, and advanced
capabilities but about redefining how we meet evolving business needs. This project work
delves into the implementation of a metadata-driven approach to automate and optimise ELT
(Extract, Load, Transform) processes within this revolutionary modern data warehouse
architecture.
The project leverages Microsoft Azure Synapse Analytics to minimise manual intervention and
enhance scalability. A metadata repository serves as the foundation for developing generic,
reusable data pipeline templates capable of handling diverse scenarios based on metadata
parameters. This standardisation enables efficient and automated data ingestion,
transformation, and modelling while reducing development and maintenance time. The
solution supports both full and incremental data ingestion into a data lake and implements
modelling techniques, such as slowly changing dimensions (SCD) Types 1 and 2 and fact tables.
To enhance user accessibility, a Power App interface was developed, simplifying parameter
management and enabling non-technical users to interact with the system seamlessly.
Additionally, to ensure operational reliability, a monitoring framework was meticulously
designed and implemented, providing robust oversight of the solution. The whole solution
was tested and deployed in a medium-sized health insurance company, demonstrating its
effectiveness in improving efficiency, scalability, and data quality.
This project work demonstrates the practical benefits of applying a metadata-driven approach
to a modern data warehouse by automating and standardising data pipelines using metadata.
This sets a foundation for further research in metadata-driven applications in cloud
environments
Building the future: analyzing business models for sustainable construction
No full textThis thesis explores the importance of innovative business models and operational strategies to
drive the adoption of sustainable construction materials, focusing on Soul of Concrete’s (SOC)
patented Mesh reinforcement technology. By analyzing industry challenges including high
environmental impact, high costs and low productivity, opportunities for transformation and
optimal value proposition are identified. A hybrid business model combining production-as-a service, direct sales, and data-driven-insights is proposed to address market inertia. Operational
strategies prioritize scalable, decentralized production through a phased plan with focus on
micro-factories and mobile units enhancing logistics and sustainability. This thesis provides
actionable recommendations for SOC’s market entry and scaling
Optimizing product visualization via advanced stable diffusion xl model and prompt engineering
No full textRecent advances in generative AI have shown promising potential in creative tasks, yet challenges
persist in adapting these technologies for specialized industrial applications. This research
introduces an AI-powered product design assistant that bridges abstract concepts and visual
representations, focusing on product design visualization. Through model implementation on
Gradio, comparative analysis, and a comprehensive prompt engineering framework, the system
leverages Stable Diffusion XL to generate industrial product visualizations, complemented by
product variations and a dynamic user preference analyzer. The system's structured database
supports preference integration and mood board functionality, enabling users to organize and
visualize their design roadmap. Results demonstrate improved image generation efficiency while
preserving industrial design specifications
Neméas: an entrepreneurial case study on building a sustainable direct-to-consumer ski touring brand - market and sale
No full textThis thesis presents a business plan and an investment memorandum for neméas, an Austrian
startup company offering sustainable, high-performance ski touring apparel. Addressing the
growing demand for eco-conscious outdoor gear, the business plan outlines the founders’
approach to launching the company and includes a market analysis, information on products
and production, a detailed marketing and sales strategy, financial projections for the next five
years and the funding requirements of the company. The investment memorandum evaluates
the company as a pre-seed investment opportunity for an angel investor
Relatório de Estágio na Vírgula d’Interrogação Editora
No full textO presente relatório tem como objetivo descrever a experiência vivida durante o estágio
curricular, realizado enquanto componente não letiva do Mestrado em Edição de Texto,
na Vírgula d’Interrogação Editora, entre novembro de 2024 e fevereiro de 2025. Iniciando
com uma breve apresentação da editora e do seu catálogo, serão apresentadas as tarefas
propostas e realizadas, assim como as dificuldades sentidas ao longo das mesmas.
Procurando ligar as aprendizagens adquiridas durante o mestrado e estes três meses de
estágio, são expostas algumas reflexões não só sobre o mercado editorial como sobre os
sistemas de inteligência artificial e os “limites” de um editor.The aim of this report is to describe the experience I had during my internship, as a nonteaching component of the Master's Degree in Text Editing, at Vírgula d'Interrogação
Editora, between november 2024 and february 2025. Beginning with a brief presentation
of the publishing house and its catalog, the tasks proposed and carried out will be
presented, as well as the difficulties experienced during them. In an attempt to link the
learning acquired during the master's degree and these three months of internship, some
reflections are presented not only on the publishing market but also on artificial
intelligence systems and the “limits” of an editor
A DEA and SFA analysis on public emergency department efficiency in Portugal and the role of frequent users
No full texthis Work Project carries out a comparative analysis of the efficiency of 15 emergency
departments (EDs) within the Portuguese National Health Service, using Data Envelopment
Analysis (DEA) and Stochastic Frontier Analysis (SFA). The work takes on a Problem-based
learning (PBL) approach, in which complex real-world problems—like the efficiency of healthcare
services—are used as vehicles for learning and collaborative student work. The dataset used,
covering 2021 to 2023, was collected by EDs and submitted to the Tribunal de Contas (Portuguese
Court of Auditors) for an upcoming audit.
The analysis highlights Decision-Making Units (DMUs) 8 and 10 as best performers, showcasing
adequate resource management, staffing levels and time allocation. In contrast, DMUs 7 and 14
consistently underperform, exhibiting inefficiencies in staffing ratios and prolonged patient wait
times. A seasonality analysis revealed that efficiency drops in summer, due to staffing shortages
and operational challenges, while a cost-analysis identified DMU 13 as the more cost-effective
unit. Further analyses are conducted to examine factors influencing ED efficiency, such as non
urgent users, frequent users, and those who leave without being seen. These findings trace a clear
path for targeted policy interventions, where underperforming units can benefit from adopting best
practices observed in efficient EDs
Skyfarm: building and evaluating a business case for vertical farming in Portugal
No full textThis work project evaluates the feasibility of launching a vertically
integrated agri-tech startup – SkyFarm, in Portugal, using vertical farming
and aquaponics. The analysis focuses on adapting these technologies to the
local context through a subscription-based business model. Results indicate
that, under conservative assumptions, SkyFarm can reach €13.8m in
cumulative revenue by 2032, with profitability projected from 2030. The
project also estimates a terminal value between €35 and €70m, supporting
investor return potential in line with venture capital expectations