Eres un profesional de BI que necesita crear una potente visualización de datos. ¿Cuál es el mejor software para usar?

In my opinion, one of the biggest mistakes that is often made is to perceive Power BI as pure data visualization software. Power BI can do so much more than data preparation and data modeling, etc. Reduced to data visualization, it is not the best tool, but as a whole with the entire platform and the Microsoft ecosystem, there is no better tool for me.

Imagine que os dados são como os ingredientes de uma receita. Sem uma receita, esses ingredientes são apenas uma coleção de itens separados, difíceis de entender como um todo. O software de visualização age como um chef que pega esses ingredientes e os transforma em um prato delicioso e fácil de entender, onde cada parte contribui para um entendimento mais claro do conjunto. Da mesma forma, esse software ajuda a transformar dados complexos em formatos visuais compreensíveis, facilitando a análise e a tomada de decisões.

🔍 Choosing Data Visualization Software: 📊 Understand software capabilities. 📈 Assess benefits for clarity & insight. ✅ Evaluate features for your needs. 🛠️ Match tool to your BI objectives.

Tableau: Best For: Interactive, complex visualizations and dashboards. Strengths: User-friendly, highly customizable, capable of handling large datasets, and offers a wide range of visualization options. Strong community support and extensive learning resources are available. Microsoft Power BI: Best For: Integration with Microsoft products and services. Strengths: Good for creating interactive reports and dashboards, especially effective for users already within the Microsoft ecosystem (like Excel, Azure). It's relatively affordable and offers a robust set of features. QlikView/Qlik Sense: Best For: Data discovery and associative data exploration. Strengths: Offers a unique approach to BI with its associative data modeling.

Sin lugar a dudas diría Power BI por las posibilidades que ofrece, y poder modelar y transformar datos en el mismo aplicativo. Pero para entornos de Google, recomendaría 100% Google Looker Studio.

I would definitely go with Power BI. Power BI is an excellent choice for data visualization and reporting. As it can be integrated with other Microsoft and non-Microsoft products. Power BI also has a user-friendly interface, and strong capabilities in data modeling and analysis. With its wide range of visualization options and also ability to support real-time data updates. But as well, the choice of selecting a visualization and reporting tool depends on the users' specific needs, preferences, and existing technology stack. Different tools have their strengths, so it's worth considering factors such as ease of use, cost, and integration with your existing data infrastructure when making a decision.

O software de visualização de dados transforma informações complexas em gráficos e imagens fáceis de entender, similar a como um chef transforma ingredientes brutos em um prato atraente e compreensível. Isso facilita a rápida identificação de tendências e padrões, tornando a análise de dados mais acessível para todos, independente de sua experiência com dados.

Used correctly, data visualisation software can help you communicate key information quickly and easily, improving and accelerating the decision-making process. The key is to focus on the most important metrics and define target or threshold values for them in advance. At a glance, report recipients can then see whether you are within expected KPIs, whether campaigns are running successfully, where you stand compared to last year or last quarter, and much more.

It also allows us to do real time monitoring which becomes a very useful test case in streaming dataset. It also helps in reaching out to the broader audience.

There are a lot of advantages, the main one is the fact that it allows you to understand what is happening in your organization. Humans are not maschines, which means, you can view all day long data in tables (DB) but without vizualizations that highlight the most important differences and changes, it is almost impossible to get the same insights. 1 picture = 1000 words

As principais no meu ver são: - Diversidade de gráficos e visualizações - Interatividade - Integração de dados - Personalização - Usabilidade - Dashboards e relatórios - Exportação e compartilhamento fácil e seguro - Análise em tempo real - Iteração através de linguagem natural

🔧 Data Visualization Software Features: 🔗 Connects to multiple data sources. 🛠️ Offers both basic & advanced operations. 🎨 Allows visual customization & interactivity. 👥 Supports collaboration. 📤 Facilitates easy export & sharing.

It can handle different types of data, such as quantitative or qualitative, and offer various techniques, such as statistical or thematic. It allows users to either input data directly or connect/import a spreadsheet of existing data sets. It automatically visualizes the selected chart or graph and allows users to color code segments, create labels, add a legend and more. It has a user-friendly interface, customizable reporting, real-time analysis, integration with existing systems, and scalability. It enables users to explore and interact with the data in different ways, and to present data to different audiences in a suitable format.

1. Data Source Connectivity: Ability to connect to diverse data sources for comprehensive analysis. 2. Data Operations: Perform both basic and advanced data operations like filtering, aggregation, and transformation. 3. Visual Customization: Create and customize visuals to match specific requirements and preferences. 4. Interactivity: Add interactive elements to visuals for enhanced user engagement and exploration. 5. Collaboration Tools: Collaborate with other users in real-time, facilitating teamwork and knowledge sharing. 6. Data Exploration Tools: Provide tools for exploring data visually, such as drill-down, filtering, and highlighting functionalities.

1. Embeddability 2. Performance 3. Chart and Graph Customization 4. Interactive Exploration 5. AI, Machine Learning, and NLQ Integration 6. Metadata Management 7. Self Service Capability 8. Geo Tagging and Location Intelligence 9. Data Discovery

Fica a dica: O "melhor" software será aquele que se alinha mais estreitamente com os requisitos, objetivos e capacidades do cliente, oferecendo uma solução que é tanto eficaz quanto eficiente para suas necessidades específicas de visualização de dados.

Here are certain factors that need to be considered: 1. Does the BI tool integrates with all my data sources. 2. Can it handle the processing power that will be required 3. How much of data manipulation is required to create BIs and does the tool support them 4. Pricing of different BI tools and what is optimal 5. ROI of using a BI tool compared to legacy solutions like spreadsheets 6. Visualization features of the BI tools 7. Security aspects of data sharing with the tool

Data type: Is your data quantitative or qualitative? You need software that can handle your data format and perform the appropriate analysis techniques. Analysis purpose: What are you trying to achieve with your data? You need software that can help you answer your research question and meet your goals. Software features: What are the capabilities and limitations of the software? You need software that has a user-friendly interface, customizable reporting, real-time analysis, integration with existing systems, and scalability. Some of the popular ones are: Microsoft Power BI: Best for business intelligence (BI) Tableau: Best for interactive charts

While the BI tools are undeniably impressive, they may lack a certain level of customisation with a quick turn around. In cases where time is a constraint, I find that relying on the tried-and-true Microsoft PowerPoint can facilitate the creation of impactful data visualisation, because it allows a clean canvas. Moreover, in today’s digital landscape, it has become increasingly convenient to automate data refresh in PowerPoint using Python libraries, in case the numbers need to be refreshed in regular intervals

Algumas das melhores ferramentas de visualização de dados incluem: - Tableau: conhecido por sua flexibilidade e facilidade de uso, é ótimo para criar visualizações complexas e interativas. - Power BI: uma escolha popular para integração com outras ferramentas da Microsoft, oferecendo uma boa relação custo-benefício. - QlikView/Qlik Sense: oferecem análises guiadas e descoberta de dados, com forte capacidade de manipulação e associação de dados. - Looker Studio: Uma opção acessível e eficaz, especialmente para aqueles que já utilizam outras ferramentas do Google. - Quicksight: ótima opção para usuários da Cloud AWS, simples e objetivo no meu ver. Com excelentes recursos de interatividade com o usuário.

If you work in a Microsoft environment, for example if you already use M365, Azure or SQL Server, then Power BI is the right choice for you. But Power BI also provides the right toolset for visualising recurring data from Excel or even PDF files, as well as website or API data. It also excels at importing data from more than 100 connectors, including Python, Salesforce, Oracle and PostgreSQL databases. Power BI also has many strengths in visualisation, with highly customisable visualisations, Python and R-based visualisations, and a marketplace for third-party visualisations. The interface is familiar from the Office suite, and DAX is a powerful scripting language for advanced calculations. New features are regularly added to Power BI.

There are many data visualization tools available, each with its own strengths and use cases. Some of the popular ones are: Microsoft Power BI: Best for business intelligence (BI) Tableau: Best for interactive charts Qlik Sense: Best for artificial intelligence (AI) Klipfolio: Best for custom dashboards Looker: Best for visualization options

Recomiendo Power BI por: - Tiene un coste bajo y ofrece 2 versiones: Power BI Pro y Power BI Premium, que se adaptan a las necesidades. - Permite hacer múltiples análisis de datos en un solo informe o panel, presentando los datos de forma visual y atractiva. - Los paneles se pueden compartir con toda la compañía o con clientes, fomentando el trabajo en equipo y la colaboración. - Es una herramienta fácil de utilizar e intuitiva. - Incluye las herramientas Power View y Power Map, que permiten ver datos en imágenes y gráficos en 3D, así como en mapas geográficos. - Se integra con otras herramientas de Microsoft, como Excel, SQL Server o Azure, así como con otras fuentes de datos externas. - Muy integrada en Microsoft 365 y con su identidad.

Dois pontos que não vi comentários por aqui... - Avalie não só as necessidades atuais, mas como a ferramenta poderá lidar com o crescimento futuro em volume de dados e complexidade de análises. - Além do preço inicial (muitos só pensa nisso), considere custos com treinamento, manutenção, atualizações e expansões.

🚀 For BI Visualization: 🌱 Small firms: Start with PBI/Tableau. ✨ Ideal: Custom AI-driven software. You should make an analysis to review what is the best fit for you based on the reporting requirements. Any organization can vary.

The type of the BI tool will depend on the type of project, the data volume, the timeline, company existing software and data bases. Also, if we need certain visuals which can only be created in particular tools we will have to use those.