Here's how you can improve your data visualization skills to impress your superiors.

Improve your data visualization skills to impress your superiors by: 1. Learning the Basics: Master fundamental principles of design & visualization 📚. 2. Using the Right Tools: Familiarize yourself with advanced tools like Tableau, Power BI, or D3.js 🛠️. 3. Clear and Concise: Ensure clarity and simplicity in your visuals to convey insights effectively 🔍. 4. Storytelling: Craft a compelling narrative around your data to make it engaging & impactful 📖. 5. Staying Updated: Keep up with the latest trends and best practices in data visualization 🌐. 6. Feedback and Practice: Seek feedback and continually practice to refine your skills 🗣️. These steps will help you create impressive, insightful visualizations that captivate your superiors.

To improve your data visualization skills and impress your superiors: - Learn fundamentals (color theory, typography, visual encoding) - Master data visualization tools (Tableau, Power BI, D3.js, Matplotlib) - Practice with real-world data - Study effective examples - Stay up-to-date with industry trends and tools - Seek feedback and focus on storytelling - Simplify complex data and use interactive visualizations - Showcase your work and achievements By following these steps, you'll become a skilled data visualizer and effectively communicate insights to impress your superiors.

The better we know the taxonomy of the data, the better we will be able to select the appropriate visualisation tool. And probably that would rather impress the superior when the right tool is used for the problem in hand.

🌟 Elevate Your Data Visualization Skills: 📊✨ Understanding your audience's level of expertise and what they expect to gain from your data presentation is crucial. Tailor your visualizations to their needs by focusing on clarity and relevance. Avoid overloading them with too much information or using overly complex charts that could confuse rather than enlighten. Instead, choose the right type of chart for the data you're presenting—bar charts for comparisons, line charts for trends, and pie charts for proportions are some of the basics you should master. By knowing your audience, you can create impactful visualizations that communicate your message effectively. #DataVisualization #KnowYourAudience #DataScience #LinkedInTips

Keep your visuals simple yet engaging, make sure that you are using the right kind of visual to explain your data and insights in detail. The major purpose of visualization is to make it understandable in simple words and how changes are taking place within the problem statement you are solving

Proficiency in data visualization tools is essential. Getting familiar with popular tools like Tableau, Power Bl, D3.js and Excel. Each tool has its strengths and can be chosen based on the complexity of the visualization required. Mastering these tools allows us to create professional and polished visuals quickly, enhancing our ability to communicate data insights effectively.

Get proficient with data visualization tools like Tableau, Power BI, or Python libraries such as Matplotlib and Seaborn. Knowing the capabilities and limitations of these tools will help you create effective visualizations.

Mastering tools like Power BI and Tableau is invaluable, as they enable easy understanding of data through charts and visual representations using diagrams and colors. Additionally, proficiency with Python libraries such as Matplotlib and Seaborn allows for the creation of various kinds of graphs.

- Master the Tools: Explore the advanced features of your data visualization tools. - Understand Your Audience: Customize visualizations to meet the needs and understanding of your audience. - Tell a Compelling Story with Data: Utilize storytelling techniques to logically convey your findings. - Use Effective Graphing Techniques: Select the appropriate graph type to represent your data. - Apply Smart Coloring Techniques: Use color strategically to emphasize important data points and trends. Please don't forget to eliminate your audience with too many colors.

Also we should search and I investigate about new and recent libraries about each program. This step could help us that be update and ready to show our skills to others.

Color is King (or Queen): Color plays a critical role. Use color palettes strategically to highlight key data points or categories. Avoid too many colors or confusing combinations that distract from the story.

Usar cores de forma inteligente também ajuda muito na interpretação dos dados. Por exemplo: - Utilizar a cor verde ou azul para indicadores positivos; - Utilizar a cor laranja ou amarelo para indicadores de alerta; - Por fim, utilizar a cor vermelha para indicadores negativos.

Using colors in your data charts is like coloring a picture in your coloring book. Pick colors that make your charts easy to read and understand. Use bright colors to show the most important parts. Remember, some people can't see certain colors well, so try not to use color combinations that might be hard for them to see. Always use the same colors in all your charts to make your presentation look neat and easy to follow.

Color is a powerful tool in data visualization but must be used wisely. It can highlight key data points, show differences, and draw attention to the important information. However, if not used properly it can lead to confusion and misinterpretation. Sticking to a consistent color scheme, using contrasting colors for emphasis and being mindful of colorblind-friendly palettes ensuring the visualizations are accessible to everyone.

Colour is crucial in data visualisation. A well-chosen colour palette enhances readability and guides viewer focus. Here’s how to use colour effectively: - Select a suitable colour palette: Choose colours that complement data and are accessible to all viewers. - Highlight key information: Use colour to emphasise important data points or trends. - Consider colour blindness: Avoid complex colour combinations for colourblind individuals to distinguish. - Maintain colour harmony: Employ a consistent colour scheme for a unified look. Effective colour use enhances visual appeal and clarity.

Effective data visualization goes beyond just presenting numbers; it tells a story. Structuring our visuals to guide the audience through the data, highlighting trends, patterns, and key insights. A compelling narrative can make complex data more understandable and engaging, helping the audience to grasp the significance of the information and remember it better.

Using design principles to keep visualizations clean and uncluttered ensures that important metrics are prominently displayed. For instance, when presenting quarterly sales performance, create a dashboard with a bar chart comparing sales by region, a line graph depicting sales trends, and a heatmap for sales density. Highlight significant insights, such as a 20% sales increase in a particular region because of a new product launch. This approach tells a clear and concise story and enables superiors to understand and act on the data quickly, showcasing your ability to effectively communicate complex information.

A data scientist should be able to tell a good story with data visualizations. First, clearly define the main message or insight from the data. Next, use charts and graphs that make the information easy to understand. Focus on design elements like color, layout, and labels to highlight the key points. Finally, practice presenting your visualizations to others and get feedback to improve.

I agree with this, your visualisation is not just for random colour play or fancy dashboards. Each visualisation serves a higher purpose - a theme of a story. Consider each visual to be a theme, while your dashboard is the whole story. So carefully curate each visual to tell an important theme/highlight of the story.

Uma ótima ideia é sempre levar em conta um OKR ao construir um dashboard, assim fica mais simples de construir um storytelling que faça sentido para o negócio.

Just like how you ask friends or teachers to look at your drawings, ask others to check your charts and graphs. They might see things you missed and can give you good advice to make your work better. Be open to their suggestions and ready to make changes. This way, you'll keep getting better and better at making great data pictures.

Seek Feedback for Improvement: Don't work in a silo. Get feedback from colleagues with diverse backgrounds. Ask for suggestions on clarity, effectiveness, and whether the visualization conveys your intended message.

Ninguém faz nada sozinho, gravar suas apresentações e pedir feedback podem ajudar muito em suas próximas apresentações e a ganhar confiança.

You are doing visualization for others so taking others perspective is important. What may seem obvious to you may not be to others especially to you team which may not have good understanding of data.

Regular practice is always the best way to improve. Whether you're telling a story, analyzing data, creating dashboards, or anything at all, regular practice is one way to get better

I believe that regular practice is essential to stay competitive in today's fast-paced world. By practicing consistently, we can outperform others at work, make a significant impact in our careers, and achieve higher positions.

Beyond the Basics! Consider data storytelling techniques, information hierarchy, and white space utilization. Remember, simplicity and clarity are key to impactful data visualizations.

Focus on how you can help audience (Senior, superior or client) drive critical decisions from your visualizations. (Example: Lower adoption of a feature, they are able to ask questions and come to a potential conclusion that they launched this feature ahead of time, that helps them take a strategic decision to move and re-launch the feature later). Importantly practice what you are presenting and avoid being overwhelmed if things go differently. Remember continuous learning is the key. Always thank your team and stakeholders every time (if possible) who helped you get to where you are.