📊Choose the right chart type to match your data for quick comprehension. 🎨Use contrasting colors to draw attention to key information. 🔍Focus on simplicity by eliminating unnecessary details that can distract viewers. 💡Highlight critical insights with labels or annotations for clarity. 🚀Use pre-built templates to streamline the design process and save time. 🖼Consider using a minimalist style to make the visualization impactful and easy to digest. 👥Keep the audience in mind to ensure the visualization communicates effectively at a glance.

1. Always think first about your audience; 2. Use few simple views with self explanatory titles; 3. Use filters lots of filters rather than duplicating the views. These are my 2 cents. I hope it helps. Dan

1. Start with the "So What?" 📊 Before diving into design, I always identify the single most important insight I want viewers to grasp. This clarity helps me choose the most appropriate visualization type and saves time on unnecessary iterations. 2. Follow the 5-Second Rule ⚡ If viewers can't grasp the main message within 5 seconds, I know I need to simplify. This means: - Using clear titles that state the insight - Limiting data points to those that support the core message - Incorporating white space strategically

When pressed for time, always aim for the most crisp form in which data can be visualised: - Try to combine different data sources to create an easily understandable KPI - Use the right chart to represent the KPI and have conditional formatting on the charts as much as possible - If working with geospatial data, heat maps can be an effective way

The main goal of visualizing the data is to analyze the data and make your inference easily understandable by others. In order to make a lasting impression, one can consider the following checklist - Goal: The primary goal of visualizing data is to extract insights and present them in an easily interpretable way. Components: Identify the minimum number of variables required and choose a chart type that best represents the relationships in the data. Tool: Select the most suitable tool for your needs, such as Tableau, or Plotly, depending on the complexity of the data and the level of interactivity required. Target Audience: Understand your audience's level of expertise and expectations.