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# Swell training and development Lda.: Swell – Training and Development helps companies solve business problems through consulting and training in Power BI, Power Apps, Power Automate and Artificial Intelligence. We combine hands-on expertise with a teaching mindset to drive digital transformation.

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## Posts
- [My buyers were comparing me to a competitor I’d ruled out](https://www.swell.com.pt/my-buyers-were-comparing-me/): The demonstration usually went well until the last ten minutes. I would be showing Training App — the platform we built to run a training operation: scheduling, trainers, venues, the compliance file the regulator wants — and the prospect would ask the question. How do the trainees get in? Where do they see their timetable, fill in their forms, find the materials for the course? Across roughly ten demonstrations the question came up in nine, and I had a stock reply. Training App is a TMS, a training management system, not an LMS, a learning management system.
- [Integrating bank reconciliation with the document flow: The green pen and the red pen](https://www.swell.com.pt/integrating-bank-reconciliation/): Client statements arrived as PDFs — most of them scans of paper — and were printed again so an accountant could work down the page with two felt-tip pens: green for movements that matched the ledger, red for those that needed chasing. When we started building software to take over the job and asked for the firm's reconciliation rules, nobody could recite a complete set. There was no set to recite. The rules lived in the pens, and in the hands that held them. Also, in the minds of those involved in the process.
- [How to Automate an Accounting Firm: Cheaper, Bigger, Fewer](https://www.swell.com.pt/automate-an-accounting-firm/): An accounting firm spends most of its hours on operations rather than accounting itself — the layer AI now handles well. The opener of a series on automating a firm almost end to end, and on where the freed people go.
- [When the guest is a machine](https://www.swell.com.pt/when-the-guest-is-a-machine/): Retreating to what the agent cannot value is half right and half dangerous. If everything comparable collapses to price, the agent never shortlists you, and the human never arrives to feel the welcome. So how the hotel reads to the agent — and inside the chatbot the traveller actually asks — comes to matter as much as how it reads to a person. Being chosen by the machine is the new price of being met by the guest.
- [Where the value is when intelligence is a commodity](https://www.swell.com.pt/value-is-when-intelligence-is-a-commodity/): If anyone can rent the same intelligence, what is left that a competitor cannot simply buy?
- [The value you can’t keep](https://www.swell.com.pt/the-value-you-cant-keep-ai/): Most business cases ask whether AI will create value. The harder question is whether your firm will keep any of it.
- [AI Document Management for Accounting Firms: The Debitus, 2026 Case Study](https://www.swell.com.pt/ai-document-management-for-accounting-firms/): Most accounting firms survive by cutting costs. The margins are thin, and the instinct is to defend them by spending less - so equipment ages, software stays frozen, and the way the work gets done belongs to an earlier decade. Plenty of firms still run the accounting package they installed years ago - the same every firm in the industry uses - and have not touched the workflow, the processes nor the customer service ever since. When a firm of this kind does invest, the money tends to go into new premises or a "brochure" website. The work itself - how documents move through the office, how clients are served, how the firm finds what it already knows - stays as it was.
- [AI Gym – Training Lucidity Under Cognitive Acceleration](https://www.swell.com.pt/ai-gym-training-lucidity-under-acceleration/): AI Gym is a simple idea: the practice of staying lucid under cognitive acceleration.
- [AI in Management: Why Structural Thinking Still Matters for Better Decisions](https://www.swell.com.pt/ai-in-management-is-transforming-business/): Without it, even the most advanced tools fail to produce real impact.
- [Artificial Intelligence in the Workplace 2026: Augmentation vs Replacement](https://www.swell.com.pt/artificial-intelligence-in-the-workplace/): The future of work will not be decided by how many people Artificial Intelligence replaces. It will be decided by how much more useful it makes them.
- [Commercial discount strategy: where value is created and where it’s quietly destroyed](https://www.swell.com.pt/commercial-discount-strategy-profit-impact/): Most commercial discounts destroy value. Reporting simply fails to show it. When sales increase after a campaign, the conclusion seems obvious: the discount worked. Revenue went up, conversion improved. The dashboard confirms the intuition. This is where a commercial discount strategy often fails — it optimizes for visible revenue instead of incremental margin. But this reasoning rests on the fragile assumption that the customers who received the discount bought more than those who did not.
- [AI Gym: Training Cognitive Capacity for Decision Intelligence 2026](https://www.swell.com.pt/ai-gym-training-cognitive-capacity/): Call it the AI Gym.
- [Emotional intelligence will outlast artificial intelligence in 2026](https://www.swell.com.pt/emotional-intelligence-vs-artificial-intelligence/): At the time, conversations around Artificial Intelligence were already gaining momentum, and technical excellence was still seen as the main differentiator. Yet after some initial small talk, I asked him a question that was not on my interview script. Not to trick him, but because I needed to quickly understand whether we were aligned on something harder to measure: Emotional Intelligence, judgment, and how knowledge translates into real-world impact.
- [Hotel Pricing Optimization: Dumb AI Agents (Part 4)](https://www.swell.com.pt/hotel-pricing-optimization-ai-agents-part-4/): The agent’s role is deliberately limited:
- [From intuition to intelligence: Building a hotel pricing agent (Part 3) – Take me to the cloud](https://www.swell.com.pt/deterministic-hotel-pricing-api-azure-functions/): At this point, we have a disciplined conversational agent that recommends hotel room prices backed by a machine learning model trained on historical hotel data. No intuition, no heuristics, and no AI hallucinations.
- [From intuition to intelligence: Building a hotel pricing agent (Part 2) – The data model](https://www.swell.com.pt/hotel-pricing-optimization-machine-learning/): Now that we have a conversational agent that understands natural language and can provide a simple, heuristic-based, hotel price recommendation, we need to take the solution one step further: we want the recommendation to be based on the actual hotel data, to look at competitor prices, season, occupancy rate, etc. and provide an accurate pricing recommendation. For that, we need data. And a predictive model.
- [From intuition to intelligence: Building a hotel pricing agent (Part 1)](https://www.swell.com.pt/hotel-pricing-agent-ai-part-1/): Let’s build an agent for optimizing the pricing model of a hotel. Instead of fragmented decision processes and data, let’s create a system to maximize occupancy and revenue. This system should adapt to the hotel’s data and the market pricing and talk to the user using natural language. It will benefit not only the business, but also the consumer.
- [When your Inbox becomes your job – automate it and forget it](https://www.swell.com.pt/automate-it-and-forget-it/): That conversation gave me an idea… So, dear participant — if you’re reading this — here’s how you can automate your job and finally reclaim some time to actually think.
- [Excel Never Dies. But Low-Code Might.](https://www.swell.com.pt/excel-never-dies/): When Microsoft launched the Power Platform, I saw it as an Excel 2.0 for apps. The pitch was irresistible: business users could build applications, automate workflows, and connect systems — no programming required. The timing was perfect. Demand for software was exploding, while IT teams were stretched thin. Low-code seemed like the answer.
- [When Something Important Happens, You’ll Know — Instantly | Smart KPI Alerts](https://www.swell.com.pt/power-bi-smart-kpi-alerts-automation/): Alert! This is happening — and you need to act now.
- [Let’s make AI useful — and usable — in real life: Deploy Your Demand Forecast Model to the Cloud with Azure Functions](https://www.swell.com.pt/azure-functions-demand-forecast-power-bi/): This function receives a JSON array, transforms the data to match the model’s expectations, predicts demand, and returns the result.
- [Operationalize Your Machine Learning Model with Azure Functions](https://www.swell.com.pt/deploy-python-model-azure-functions/): In the previous article, I demonstrated how to train a machine learning model in Python to forecast daily product demand for a retail business. Now it’s time to take that model from a notebook into a real-world environment — where it can receive new data and return predictions on demand.
- [Forecasting Retail Demand with Python: The First Step Toward Smarter Inventory Management](https://www.swell.com.pt/retail-demand-forecast-python/): Inventory management is a critical challenge for most retail businesses. Overstocking ties up capital and increases the risk of obsolescence. Understocking, on the other hand, leads to lost sales, customer dissatisfaction, and potential long-term brand damage. That’s why accurate demand forecasting is essential—not just for operational efficiency but for strategic decision-making.
- [Playing with data visuals on Power Apps: a creative approach](https://www.swell.com.pt/power-apps-svg-data-visuals/): I have been playing around with some simple data visuals on Power Apps. This is an area that clearly needs improvement, in my humble opinion, since the default canvas Power Apps charts are really not that amazing and because in an automation solution it is interesting to have the analytics layer integrated with the User Interface / User Experience. Together, these two allow for action - not analysis alone. In short, this is what I’ve found: you can go a long way with user defined functions (UDF) in Power Apps that take data values as arguments and create SVG charts as outputs.
- [How can businesses use artificial intelligence to grow?](https://www.swell.com.pt/artificial-intelligence-for-business/): This post is a personal reflection that tries to answer a question I hear frequently from my consulting clients: “How can AI help my business?”
- [AI Features in Power BI: Churn Analysis, Forecasting and Anomalies](https://www.swell.com.pt/ai-features-in-power-bi-churn-analysis-forecasting-and-anomalies/): In this article, we will explore several artificial intelligence features in Power BI applied to a telecommunications company. Key Influencers analysis will help us identify the main factors driving churn, highlighting the impact of high daytime charges, the number of support calls, and having international plans. Next, we will use the forecasting feature to predict future sales based on time series, supporting stock management, marketing planning, and risk mitigation. Anomaly detection will allow us to spot unexpected deviations in sales, enabling a fast strategic response. As described in the previous article, we used the Power BI Design Kit to ensure visual consistency.
- [Anomaly Detection in Accounting Records with AI Builder and Power Platform](https://www.swell.com.pt/anomaly-detection-in-accounting-records-with-ai-builder-and-power-platform/): AI Builder Anomaly Detection in Power Platform allows organizations to improve their financial processes. This is the third case of intelligent automation in financial processes in this article series on using the Power Platform's AI Builder focuses on anomaly detection in accounting entries and financial transactions. This is a highly valuable solution that enhances the work of professionals in these areas.
- [Automating Accounting Classification with AI Builder and Power Platform](https://www.swell.com.pt/ai-builder-accounting-classification/): In my previous post, I showed how to use AI Builder to extract structured data from documents in image or PDF format. One of the main advantages of structuring data, as mentioned, is the ability to use it to train predictive models. That’s exactly what we’ll explore in this article: using invoice data to train a classification model that can predict which accounting entries should be recorded for each document. This is the foundation for an intelligent accounting automation system.
- [Automating Invoice Data Extraction with AI Builder and Power Platform](https://www.swell.com.pt/ai-builder-invoice-data-extraction/): In one of the most recent workshops where I spoke, I presented a series of use cases for automating financial processes. The first of these focused on extracting data from documents originally in paper format. What used to be difficult and costly to implement just a few years ago can now be done easily in any company using Microsoft’s Power Platform and its AI Builder add-in — a tool that brings AI models into applications and business processes with no-code integration.
- [Design Rules for Power BI: Wireframes, Themes and Icons for Clean Business Dashboards](https://www.swell.com.pt/power-bi-design-rules/): "Power corrupts. PowerPoint corrupts absolutely." – Edward Tufte
- [Power Apps NFC School Bus App: Real-Time Tracking & Insights](https://www.swell.com.pt/power-apps-nfc-school-bus-tracking/): In the interior of Portugal, school-aged children have to travel dozens of kilometers daily to attend school. For many families, the long distance between home and school has been a difficult problem to solve. Fortunately, today, some municipalities offer transportation services that allow these children to reach school on time and in comfort, helping them perform at their best—and have fun doing so.
- [Power BI Visual Calculations: A Simpler Way to Analyze Data Without DAX](https://www.swell.com.pt/power-bi-visual-calculations/): One of the biggest challenges when learning Power BI is mastering the DAX (Data Analysis Expressions) language. It is a powerful tool for data analysis, but it’s hard to learn due to its abstraction and the strict structure of the data model it relies on. A new feature called visual calculations, still in preview in Power BI Desktop, makes things easier by allowing calculations to be created directly in the visuals – much like Excel formulas.
- [Excel: still the main tool for the CFO?](https://www.swell.com.pt/excel-still-the-main-tool-for-the-cfo/): Excel is the financial manager's tool par excellence. Although, in our opinion, it suffers from many weaknesses when it comes to reporting functions, data governance, and its use as a process automation application, Excel remains unbeatable in terms of its function of analyzing and solving complex problems, performing calculations, and making it easier to build visualizations and charts.
- [Text analytics – what our trainees say about us](https://www.swell.com.pt/analyzing-training-feedback-power-automate-ai-builder/): I started teaching Excel for finance about 10 years ago. In 2015, with the launch of Power BI, I began a series of training sessions on this revolutionary data analysis and visualization technology, focused on business management. Today, we are a team of trainers and consultants, with thousands of trainees and over 500 training events behind us.
- [How to manipulate Excel from Power Automate – an introduction to Office Scripts](https://www.swell.com.pt/replacing-vba-with-office-scripts/): VBA (Visual Basic for Applications) was created in 1993 by Microsoft and integrated into version 5 of Excel (who remembers!?). Since then, millions of users around the world have sought to automate repetitive tasks in Excel, often turning Excel into applications that serve the most diverse purposes (some quite funny!). 30 years later, VBA for Excel is still alive and with legions of enthusiastic followers and some critical processes in some companies continue to depend on it.
- [DAX Queries for Power Automate: how to populate Word templates with Power BI data](https://www.swell.com.pt/power-bi-word-automation-dax-queries/): Sometimes it is necessary to write a report in text format, in Word, for example, which contains data relating to a specific indicator. The most common process is to write the text separately from the numerical values, filling in the data manually, or through “copy-paste” in the document. Wouldn't it be great if we connected to a Power BI dataset and entered the values directly into a document? That's what we'll see in this post.
- [Automate document management with Power Automate and SharePoint. How to create a document archive by year and entity](https://www.swell.com.pt/automate-document-management-power-automate-sharepoint/): The scenario is common to many companies: they receive hundreds or thousands of documents per year from their suppliers and want to automate the archive according to their business rules. This facilitates organization, auditing, research and internal control. In this article, we'll look at how to create an automated archiving solution with Power Automate and SharePoint.
- [The second fastest way to read large Excel tables in Power Automate](https://www.swell.com.pt/read-excel-table-power-automate-office-scripts/): Our client, a transportation company, challenged us to build an app that plays a sound every time they receive an order for a customer. They are based here in Portugal, and ship dozens of trucks throughout all Europe carrying all sorts of goods. Time is crucial, and, sometimes, they delay the deliveries because no one is paying attention to the order book. If a customer places a new order, they must act immediately in order to avoid unnecessary delays.
- [Customer-Centric Machine Learning: Clustering, Association Rules, and Churn](https://www.swell.com.pt/customer-centric-machine-learning/): For companies that build their strategy around the customer and their satisfaction, there are three machine learning models that are relatively easy to apply and can have a high impact: clustering, as a way to understand consumer behavior; association rules, which uncover which products are frequently bought together; and churn prediction, which estimates which customers are most likely to stop being customers.

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Training Programs PT   EN Nível 1 Nível 2 Módulo 1 – Introdução à Power Platform O que é a Plataforma Power Ferramentas Power (Power Apps, Power Automate, Power BI, Power Pages, Power Virtual Agents) O que é o low code e qual o seu potencial na transformação digital Visão geral do ecossistema Microsoft Power e casos de uso empresariais Módulo 2 – Ferramentas de Inteligência Artificial AI Builder: modelos predefinidos e modelos personalizados Azure AI Services: visão computacional, análise de texto e predição Introdução ao uso do Copilot na Power Platform Aplicações práticas de IA para inovação empresarial Módulo 3 – Conectores e Integração com Dados O que são conectores na Power Platform Conectores padrão vs. conectores premium Integração com APIs e serviços externos Considerações de segurança, performance e licenciamento Módulo 4 – Integração com Office 365 Excel como origem de dados Integração com SharePoint (listas, bibliotecas, permissões) Integração com Outlook (emails, calendários, tarefas) Integração com Microsoft Teams (notificações, formulários, bots) Casos práticos de integração no contexto empresarial Módulo 5 – Dataverse como Backend de Dados O que é o Dataverse e vantagens face a outras fontes Criação de tabelas e modelos de dados relacionais Relacionamentos, colunas calculadas e de escolha Segurança e permissões (perfis, papéis, partilhas) Limites de delegação de dados no Power Apps Módulo 6 – Explorar o Power Apps Tipos de aplicações: Canvas, Model-Driven, Portais Aplicações “out of the box” e personalização rápida Partilha de aplicações com utilizadores e controlo de acesso Exemplos de aplicações empresariais por setor (Finanças, RH, Operações) Módulo 7 – Programar com Power Fx Sintaxe inspirada nas fórmulas do Excel Tipos de variáveis: contextuais, globais, coleções Funções essenciais Power Fx para lógica, filtros, UI e integração Exemplos práticos com navegação, validações, cálculos e chamadas a flows Módulo 8 – Boas Práticas de Desenvolvimento com Low Code Convenções de nomeação (ex: btn_, txt_, col_) Organização visual: grupos, containers e componentes reutilizáveis Organização da lógica: separação entre UI, dados e estado Boas práticas com variáveis (Set, UpdateContext, ClearCollect) Comentários no código e documentação interna da app Otimização de performance: delegation warnings, With, Concurrent Application Lifecycle Management (ALM): ambientes, soluções, versões Estruturação de ambientes: desenvolvimento, teste, produção Checklist final de qualidade para cada aplicação Módulo 9 – Hands on: O Caso Power Décor Problema: caos na gestão de contactos a clientes Solução: criação de uma app para organizar contactos e otimizar a gestão de cobranças Módulo 10 – Hands on: O Caso Indústrias OnStart Problema: atrasos nas entradas e saídas dos colaboradores Solução: desenvolvimento de uma aplicação móvel para registo de tempos e análise dos dados Módulo 11 – Hands on: O Caso ClearCollect Consulting Problema: necessidade de gerir despesas de viagens de consultores Solução: criação de uma app responsive para submissão de despesas com upload de comprovativos e aprovação Módulo 1 – Power Automate: Fundamentos e Conectividade O que é o Power Automate Ligações e conectores (standard vs. premium) Fluxos de ambiente de trabalho Licenciamento e implicações práticas Governança e segurança: políticas DLP, controlo de partilhas e auditoria Módulo 2 – Anatomia de um Flow e ALM Triggers e ações Tipos de fluxos (automatizados, instantâneos, agendados, UI flows) Utilização de templates como ponto de partida Application Lifecycle Management (ALM): soluções, ambientes, versões Migração de flows entre ambientes (desenvolvimento, teste e produção) Módulo 3 – Resolução de Erros e Boas Práticas Erros mais comuns no Power Automate Estratégias de diagnóstico e resolução Estrutura lógica dos fluxos Dicas para criar fluxos escaláveis e reutilizáveis Módulo 4 – Expressões e Conteúdo Dinâmico Como criar expressões no Power Automate Combinação de expressões com conteúdo dinâmico Compreensão e manipulação de estruturas JSON Ferramentas de debugging: Compose, Peek Code, Run History Módulo 5 – Integração com Outras Ferramentas da Power Platform e APIs Execução de fluxos a partir do Power Apps Power BI como trigger Chamadas a APIs externas com conector HTTP Autenticação com Azure AD Criação e utilização de conectores personalizados Módulo 6 – Dataverse para Automação e IA O que é o Dataverse Criação e gestão de tabelas e colunas Relacionamentos e regras de negócio Alternate Keys Níveis de segurança e controlo de partilha Utilização do Dataverse como backend para apps e flows Módulo 7 – AI Builder: Aplicações Reais de Inteligência Artificial O que é o AI Builder Tipos de modelos disponíveis Introdução à Inteligência Artificial Generativa Estudo de caso: BrazilCommerce e Prompt Engineering Ligação dos modelos AI Builder a fluxos automatizados Módulo 8 – Prompt Engineering para Automação Inteligente O que é o Prompt Engineering Conceitos e terminologias fundamentais Tipos de prompts: simples, encadeados, estruturados Boas práticas para criação de prompts eficazes Aplicações empresariais do prompt engineering Estudo de caso: Melhoria do atendimento ao cliente Desafios atuais e perspetivas futuras Prompt Engineering como estratégia de negócio Módulo 9 – Caso Prático 1: Automação de Documentos com IA Recolha automática de faturas por email Extração de dados estruturados (datas, valores, IVA, descrição) Classificação automática em contas específicas Integração entre modelos de IA, flows e Dataverse Módulo 10 – Caso Prático 2: Arquivo Inteligente com SharePoint Processamento automático de documentos de fornecedores Criação de estrutura de pastas e nomenclatura inteligente Classificação com metadados e fluxos de aprovação Módulo 11 – Caso Prático 3: Automação Avançada com Excel Leitura e escrita de dados no Excel com Power Automate Utilização de Office Scripts para manipulação avançada Automatização de relatórios e dashboards Módulo 12 – Caso Prático 4: Modelo de IA para Extração de Dados de Faturas Criação e treino de modelo de IA para leitura de faturas Integração do modelo com fluxo de automação Armazenamento estruturado no Dataverse ou SharePoint Level 1 Level 2 Module 1 – Introduction to Power Platform What is Power Platform Power tools (Power Apps, Power Automate, Power BI, Power Pages, Power Virtual Agents) What is low code and its potential for digital transformation Overview of the Microsoft Power ecosystem and business use cases Module 2 – Artificial Intelligence Tools AI Builder: prebuilt models and custom models Azure AI Services: computer vision, text analysis and prediction Introduction to using Copilot in the Power Platform Practical applications of AI for business innovation Module 3 – Connectors and Data Integration What are connectors in the Power Platform Standard vs. premium connectors Integration with APIs and external services Security, performance and licensing considerations Module 4 – Integration with Office 365 Using Excel as a data source Integration with SharePoint (lists, libraries, permissions) Integration with Outlook (emails, calendars, tasks) Integration with Microsoft Teams (notifications, forms, bots) Practical integration cases in business contexts Module 5 – Dataverse as the Data Backend What is Dataverse and its advantages over other sources Creating tables and relational data models Relationships, calculated and choice columns Security and permissions (roles, teams, sharing) Delegation limits in Power Apps Module 6 – Exploring Power Apps Types of applications: Canvas, Model-Driven, Portals Out-of-the-box apps and rapid customization Sharing apps and access control Examples of business apps by sector (Finance, HR, Operations) Module 7 – Programming with Power Fx Excel-style formula syntax Variable types: context, global, collections Key Power Fx functions for logic, filtering, UI and integration Practical examples: navigation, validations, calculations, flow calls Module 8 – Best Practices for Low-Code Development Naming conventions (e.g., btn_, txt_, col_) Visual structure: control groups, containers, reusable components Logic structure: separation of UI, data and state Best practices for using Set, UpdateContext, ClearCollect Code comments and internal app documentation Performance optimization: delegation warnings, With, Concurrent Application Lifecycle Management (ALM): environments, solutions, versioning Environment strategy: development, test and production Final quality checklist for every app Module 9 – Hands-on: The Power Décor Case Problem: chaos in managing customer contacts Solution: building an app to organize contacts and optimize collections Module 10 – Hands-on: The OnStart Industries Case Problem: delays in employees clocking in and out Solution: developing a mobile app to register time entries and exits and analyze results Module 11 – Hands-on: The ClearCollect Consulting Case Problem: consultants frequently travel and need to manage expenses Solution: creating a responsive app to submit travel expenses with receipt uploads and approval workflow Module 1 – Power Automate: Fundamentals and Connectivity What is Power Automate Connections and connectors (standard vs. premium) Desktop flows Licensing and practical implications Governance and security: DLP policies, sharing controls, and audit logging Module 2 – Flow Anatomy and ALM Triggers and actions Flow types (automated, instant, scheduled, UI flows) Using templates as a starting point Application Lifecycle Management (ALM): solutions, environments, versions Moving flows between dev, test and production environments Module 3 – Error Handling and Best Practices Common Power Automate errors Debugging strategies Logical structuring of flows Tips for building scalable and reusable flows Module 4 – Expressions and Dynamic Content How to build expressions in Power Automate Combining expressions with dynamic content Understanding and working with JSON Debugging tools: Compose, Peek Code, Run History Module 5 – Integration with Other Power Platform Tools and APIs Triggering flows from Power Apps Using Power BI as a trigger Calling external APIs with HTTP connector Authentication with Azure AD Creating and using custom connectors Module 6 – Dataverse for Automation and AI What is Dataverse Creating and managing tables and columns Relationships and business rules Alternate Keys Security levels and sharing controls Using Dataverse as a backend for apps and flows Module 7 – AI Builder: Real-World Applications What is AI Builder Available model types Intro to Generative AI Case study: BrazilCommerce and Prompt Engineering Connecting AI Builder models with automated flows Module 8 – Prompt Engineering for Smart Automation What is Prompt Engineering Key concepts and terminology Types of prompts: simple, chained, structured Best practices for writing effective prompts Business use cases for prompt engineering Case study: Improving customer service Current challenges and future outlook Prompt Engineering as part of business strategy Module 9 – Practical Case 1: Document Automation with AI Automatically fetching invoices from email Extracting structured data (dates, values, VAT, description) Auto-classification into accounts Combining AI models with flows and Dataverse Module 10 – Practical Case 2: Smart SharePoint Archiving Processing supplier documents automatically Creating folder structures and naming conventions Using metadata and approval flows Module 11 – Practical Case 3: Advanced Excel Automation Reading and writing Excel data with Power Automate Using Office Scripts for advanced manipulation Automating reports and dashboards Module 12 – Practical Case 4: AI Model for Invoice Data Extraction Building and training a custom AI model for invoice reading Integrating the model into automated flows Structured storage in Dataverse or SharePoint Choose you learning format Tailored Corporate Training - Tailored Programs for Companies In addition to scheduled sessions, this training can also be delivered as a customized program for your company. You define the dates, times, and number of participants, and we adapt the program to your specific needs. Request a Corporate Training Proposal 1 Target AudienceProfessionals from a wide range of fields who wish to create advanced reports with Power BI, without depending on IT teams. 2 Duration16 hours of training, delivered in person or via Live Streaming. 3 PrerequisitesThere are no prerequisites — just curiosity and a strong willingness to learn. 4 ResourcesParticipants must bring their own laptop with Excel and Power BI Desktop installed. Access to Power BI Service accounts will be provided.    
- [Power BI for business and finance](https://www.swell.com.pt/power-bi-for-business-and-finance/): Power BI for business and finance See beyond the numbers—turn data into clarity, confidence, and action with Power BI. Training Programs PT   EN Nível 1 Nível 2 Módulo 1: Introdução à Transformação Digital e ao Power BI Definição e Contexto Principais Componentes da Transformação Digital Benefícios da Transformação Digital – para empresas e profissionais Desafios da Transformação Digital Exemplos de Transformação Digital Questionário de autodiagnóstico: transformação digital, quão preparada está a sua organização? Módulo 2: A Plataforma Power da Microsoft Ecossistema de transformação digital low code Power Apps – Aplicações à medida do seu negócio Power Automate – Automação de processos digitais na cloud e desktop Power Pages – Websites Copilot Studio – IA generativa Módulo 3: Conceitos de Business Intelligence Extract Transform and Load (ETL) Importância do ETL no Business Intelligence Ferramentas e Processos ETL no Power BI Linguagem Power Query M Exemplo de código M Modelação de dados Data Analysis Expressions – DAX Integração entre o Excel e o Power BI Módulo 4: Storytelling com o Power BI O caso web analytics – analisar visitas ao nosso website A interface do Power BI desktop Primeiros passos com as visualizações do Power BI – Visualizações Simples Além do básico – mapas Análise multivariada com visualizações Power BI Análise de séries temporais Filtrar os dados com slicers Comparação com objetivos ou valores de referência Publicar e partilhar relatórios no Power BI Service Colaborar através de áreas de trabalho (workspaces) Exportar relatórios para PDF ou PPT Publicar relatórios numa página web Publicar relatórios no SharePoint Integrar relatórios numa app Power BI Mobile layouts – otimizar visualizações em dispositivos móveis Filtrar, agrupar e resumir dados: os requisitos essenciais de análise Dashboards no Power BI Service Comunicar visualmente – escolher a visualização certa para a mensagem com mais impacto Módulo 5: Transformar relatórios em apps interativas Marcadores – o que são e para que servem os marcadores? Tooltips avançadas e tooltips de ajuda Páginas de detalhes Módulo 6: Visualizações com inteligência artificial Key influencers – que variáveis têm mais impacto nos resultados? Análise de churn com key influencers Possíveis estratégias para reduzir o churn Forecasting – efetuar previsões utilizando séries temporais Deteção de anomalias – analisar valores anormalmente baixos ou elevados Clustering – compreender e segmentar clientes com base no seu comportamento Outras visualizações com inteligência artificial Árvore de decomposição – como funciona? Narrativa inteligente Módulo 7: Introdução ao Power Query O que é o Power Query? Onde funciona o Power Query? Para que serve o Power Query? Ligar-se a diversas origens de dados Fornecer estrutura a dados pouco estruturados Corrigir erros e omissões Automatizar processos repetitivos Enriquecer os dados Combinar dados de origens diferentes Duas abordagens, uma ferramenta: Power Query para todos os perfis Importar ficheiros Excel, CSV, PDF e XML Importar dados a partir de diretórios e de páginas web Módulo 1: Introdução à linguagem DAX O que é a linguagem DAX, como funciona e para que serve? Sintaxe da linguagem DAX, operadores, tipos de dados Colunas calculadas, medidas calculadas e tabelas calculadas Semelhanças e diferenças em relação às funções do Excel Modelo de dados e impacto na linguagem DAX Editor DAX, boas práticas e recomendações Módulo 2: Funções DAX Funções básicas de agregação Funções iteradoras Funções lógicas e de controlo Funções de data e hora Funções de texto Funções de filtro Funções de tabela Funções financeiras Funções de time intelligence Módulo 3: Variáveis DAX Melhorar o desempenho e a legibilidade da linguagem DAX com variáveis Exemplos práticos Módulo 4: Calculation Groups O que são os calculation groups e porque são tão importantes na reutilização de medidas DAX Exemplos práticos Módulo 5: Casos de aplicação prática da linguagem DAX Equipa comercial: analisar dados com estrutura hierárquica Converter balancetes em relatório financeiro e analisar rácios financeiros Controlar o orçamento e compará-lo com valores reais, como lidar com diferenças de granularidade? Relações ativas e inativas: analisar dados com diferentes perspetivas temporais Calendário fiscal e calendário civil Segmentar clientes ou produtos através da classificação de Pareto ABC Segmentar clientes ou produtos através de modelos de clustering: o modelo RFM (Recency, Frequency, Monetary Value) Módulo 6: Casos práticos de Power Query Importação e transformação de dados em Excel utilizando diversas técnicas e funções Importar dados a partir de web API Automatizar o processo de importação de dados com funções do Power Query Utilizar o Power Query para analisar texto e detetar sentimento Módulo 7: Plataforma Power Centralizar processos de ETL na cloud através de Power BI Dataflows Utilizar o SharePoint como repositório de ficheiros com dados Power BI Apps: distribuir conteúdo Power BI numa única aplicação Deployment Pipelines: gerir o ciclo de vida de uma solução Power BI Level 1 Level 2 Module 1: Introduction to Digital Transformation and Power BI Definition and Context Main Components of Digital Transformation Benefits of Digital Transformation – for companies and professionals Challenges of Digital Transformation Examples of Digital Transformation Self-assessment quiz: how prepared is your organization for digital transformation? Module 2: The Microsoft Power Platform Low-code digital transformation ecosystem Power Apps – Custom applications tailored to your business Power Automate – Cloud and desktop process automation Power Pages – Websites Copilot Studio – Generative AI Module 3: Business Intelligence Concepts Extract, Transform and Load (ETL) The importance of ETL in Business Intelligence ETL Tools and Processes in Power BI Power Query M language Sample M code Data modeling Data Analysis Expressions – DAX Integration between Excel and Power BI Module 4: Storytelling with Power BI Web analytics case – analyzing website traffic Power BI Desktop interface Getting started with basic visualizations Beyond the basics – maps Multivariate analysis using Power BI visuals Time series analysis Filtering data with slicers Comparing with goals or benchmark values Publishing and sharing reports in Power BI Service Collaborating through workspaces Exporting reports to PDF or PPT Publishing reports to a web page Publishing reports to SharePoint Embedding reports in a Power BI app Mobile layouts – optimizing for mobile devices Filtering, grouping and summarizing data: essential analysis techniques Dashboards in Power BI Service Visual communication – choosing the right visual for maximum impact Module 5: Turning Reports into Interactive Apps Bookmarks – what they are and what they’re for Advanced tooltips and help tooltips Drillthrough pages Module 6: AI-Powered Visualizations Key influencers – which variables impact results the most? Churn analysis using key influencers Possible strategies to reduce churn Forecasting – using time series to make predictions Anomaly detection – identifying unusually low or high values Clustering – understanding and segmenting customers by behavior Other AI visualizations Decomposition tree – how it works Smart narrative Module 7: Introduction to Power Query What is Power Query? Where does Power Query work? What is Power Query used for? Connecting to multiple data sources Structuring unstructured data Correcting errors and omissions Automating repetitive processes Enriching data Combining data from different sources Two approaches, one tool: Power Query for all profiles Importing Excel, CSV, PDF and XML files Importing data from folders and web pages Module 1: Introduction to DAX What is DAX, how does it work, and what is it for? DAX syntax, operators, data types Calculated columns, calculated measures, and calculated tables Similarities and differences compared to Excel functions Data model and its impact on DAX DAX editor, best practices and recommendations Module 2: DAX Functions Basic aggregation functions Iterator functions Logical and control functions Date and time functions Text functions Filter functions Table functions Financial functions Time intelligence functions Module 3: DAX Variables Improving DAX performance and readability using variables Practical examples Module 4: Calculation Groups What are calculation groups and why they are essential for reusing DAX measures Practical examples Module 5: Practical Use Cases for DAX Sales team: analyzing hierarchical data structures Convert trial balances into financial reports and analyze financial ratios Budget control and comparison with actuals – dealing with different granularities Active vs. inactive relationships: analyzing data from different time perspectives Fiscal calendar vs. calendar year Customer or product segmentation using ABC Pareto classification Segmentation using clustering models: RFM (Recency, Frequency, Monetary Value) Module 6: Power Query Use Cases Importing and transforming Excel data using various techniques and functions Importing data from a web API Automating the import process with Power Query functions Using Power Query to analyze text and detect sentiment Module 7: Power Platform Centralizing ETL processes in the cloud with Power BI Dataflows Using SharePoint as a file-based data repository Power BI Apps: distributing Power BI content in a single app Deployment Pipelines: managing the lifecycle of a Power BI solution Choose you learning format Tailored Corporate Training – Tailored Programs for Companies In addition to scheduled sessions, this training can also be delivered as a customized program for your company. You define the dates, times, and number of participants, and we adapt the program to your specific needs. Request a Corporate Training Proposal 1 Target AudienceProfessionals from a wide range of fields who wish to create advanced reports with Power BI, without depending on IT teams. 2 Duration16 hours of training, delivered in person or via Live Streaming. 3 PrerequisitesThere are no prerequisites — just curiosity and a strong willingness to learn. 4 ResourcesParticipants must bring their own laptop with Excel and Power BI Desktop installed. Access to Power BI Service accounts will be provided.    
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