Data Visualization Software

🚀 Power BI: Adding Custom Tooltips to KPI Cards! While exploring Power BI capabilities, I discovered a creative workaround to add detailed tooltips to KPI cards - something that's not natively supported! The Challenge 🎯 Standard KPI cards in Power BI lack the ability to show comprehensive tooltip information, limiting user interaction and data exploration. My Solution 💡 I developed a custom HTML-based approach that transforms regular KPI cards into interactive, information-rich components: ✅ HTML-Wrapped DAX Measures: Converted standard measures into HTML format for enhanced styling ✅ Dual Theme Support: Implemented both light and dark modes for better user experience ✅ Dynamic Theming: Created a separate theme table with all color variations ✅ Rich Tooltips: Added detailed breakdowns including Monthly Recurring Revenue, One-time Sales, and Refunds Key Features 🌟 Responsive Design: Adapts to different screen sizes Theme Consistency: Seamless light/dark mode switching Enhanced UX: Detailed information on hover without cluttering the main view Professional Styling: Clean, modern card design with gradients and shadows Implementation Highlights 🔧 // Theme table with comprehensive color schemes Theme = DATATABLE( "ThemeMode", STRING, "ColorType", STRING, "ColorValue", STRING, // Light & Dark theme definitions... ) Important Consideration ⚠️ While this solution works effectively, be mindful of the HTML card container's width as it can overlap with other visuals. Proper positioning and sizing are crucial for optimal user experience. Results 📊 ✨ Enhanced user engagement with interactive KPI cards ✨ Better data storytelling through rich tooltips ✨ Professional, modern dashboard appearance ✨ Improved accessibility with theme options This approach opens up new possibilities for creating more engaging and informative Power BI dashboards. Sometimes the best solutions come from thinking outside the box! Share your experiences in the comments! #PowerBI #DataVisualization #BusinessIntelligence #DAX #HTML #DataAnalytics #Innovation #Dashboard #Microsoft #DataScience

This month’s Power BI update is quite exciting... 🤓 The PBI Core Visuals team is working on some pretty cool stuff lately. Let’s dive into the details. 1️⃣ Marker Enhancements: Advanced controls for markers make data points pop: ↳ Customize by Categories or Series: Control marker styles at the category or series level. ↳ Marker Visibility Toggles: Toggle markers on/off for specific categories or series. ↳ Marker Shape & Transparency Control: Personalize markers by adjusting shapes (rotations supported, except circles) and sizes. ↳ Customizable Marker Borders: adjustable color, transparency, and width. 2️⃣ Small Multiples for Card Visuals: Compare data across categories or dimensions with ease: ↳ Flexible Layout Options: Choose Single Column, Single Row, or Grid layouts. ↳ Overflow Handling: Use pagination or continuous scrolling to manage excess data. ↳ Advanced Styling Controls: Customize borders, gridlines, and background colors. Round corners for a modern look. ↳ Header & Title Customization: Control header settings and adjust titles for font, color, padding, and text wrap. Align with your report’s branding. 3️⃣ New Text Slicer: Enhance data filtering with text-based searches: ↳ Intuitive Text Filtering: Type into the input box to filter data in real-time. ↳ Comprehensive Appearance Customization: Configure the input box with placeholder text, font, color, and transparency. ↳ Enhanced Button Controls: Adjust Apply button settings for color, transparency, borders, and padding. Customize the Dismiss button for clearing filters. ↳ Focus Accent Bar & Borders: Highlight the active input field with an accent bar. Set borders around the input area. Excited about these new features? I for sure am 🚀 * Note 1: Some features might still be in development. * Note 2: All images used are from Microsoft as unfortunately I don't have the latest version of Power BI on my laptop yet * Note 3: Links to all the updates details in the comments! #data #datapears #powerbi #report #reporting #dataviz #datavisualization #news

💡Line, bar, and pie chart design: tips & tricks Effective data viz makes it easy to communicate complex information without requiring people to read and interpret a lot of text. People tend to be familiar with common chart types, such as line and bar charts, so using one of these types in your app can make it more likely that people will already know how to read your chart. 🍎 General recommendations ✔ Ensure chart placement and size aligns with the visual hierarchy of the page. When using multiple charts at the same level of importance, they should have consistent sizing. ✔ Design charts to adapt to different screen sizes and resolutions without losing clarity or detail. ✔ Use colorblind-friendly palettes and ensure charts are legible in both dark and light mode. 🍏 Line chart Line charts connect a series of data points using a line, and are commonly used to show data trends over time. ✔ Simplify the lines: Use distinct, contrasting colors for each line. Avoid using more than four to six lines to prevent clutter. ✔ Axis labels and gridlines: Use subtle gridlines and clearly label the axes. ✔ Data points: Highlight data points with small markers (circles, squares) to make it easier to read exact values. ✔ Interactivity: Consider adding tooltips that show exact data values when users hover over specific points on the line. ✔ Avoid using just color to communicate meaning in your data visualization. Incorporate other visual indicators such as shapes, line texture, patterns, or direct labels to help users make sense of the data. How to create line chart in Figma: https://lnkd.in/edPVhsih 🍏 Bar chart Bar charts are used to compare categorical or discrete data. ✔ Baseline number: Don't set the baseline to any number other than zero. Doing so misrepresents the data. ✔ Color: Use a single color for all bars unless comparing different categories; in that case, use distinct colors for each category. ✔ Labels: Place value labels directly on top of or inside the bars to make the data easily accessible without needing to reference the axis. ✔ Stacked vs. grouped bars: Use stacked bars for comparing parts of a whole and grouped bars for comparing multiple categories across the same scale. 🍏 Pie chart Pie chart helps users visualize portions of a whole at a glance. ✔ Segment clarity: Limit the number of slices to 5; more slices make the chart difficult to read. Consider grouping smaller slices into an "Others" category. ✔ Pie order: show data in descending order, starting at the 12 o'clock point and moving clockwise. ✔ Minimalist design: Keep the design clean by avoiding 3D effects, shadows, or excessive borders, which can distort perception. How to create bar chart in Figma: https://lnkd.in/eAaV3KBs #dataviz #datavisualization #ui #uidesign #productdesign #userinterface #uxdesign

July's Power BI update has one feature worth your attention. Everything else can wait. 𝐑𝐞𝐩𝐨𝐫𝐭-𝐰𝐢𝐝𝐞 𝐭𝐡𝐞𝐦𝐢𝐧𝐠, straight from the 𝐅𝐨𝐫𝐦𝐚𝐭 𝐩𝐚𝐧𝐞. Customise current theme now sits in the Format pane. Click an empty part of the canvas, and it's there. → Change report-wide colours with a palette, without losing your other customisations → Set defaults for borders, backgrounds, shadows, header icons, corner radius and padding → Apply page size, background and wallpaper across every page at once → Push filter pane formatting to current and new pages → Export the result as a theme and reuse it or share it with your team Every new visual you drop on the canvas inherits it. The part I care about: consistency stops being a cleanup job at the end of the build. It becomes the default. Individual page and visual styling still wins where you need it, and you can reset any setting back to the theme. Still in preview. Turn on Modern visual defaults and customise theme improvements in Options first. #PowerBI #MicrosoftFabric #DataViz #BusinessIntelligence

#PowerBI has introduced new 𝐕𝐢𝐬𝐮𝐚𝐥 𝐋𝐞𝐯𝐞𝐥 𝐅𝐨𝐫𝐦𝐚𝐭 𝐒𝐭𝐫𝐢𝐧𝐠𝐬 (𝐩𝐫𝐞𝐯𝐢𝐞𝐰), offering more flexibility in formatting data🎉🎉 Originally designed to address the formatting limitations of #visual_calculations, which aren't part of the data model, this feature allows us to format calculations directly within visuals. With this update, Power BI now supports three hierarchical levels of format strings: 𝟏) 𝐌𝐨𝐝𝐞𝐥 𝐋𝐞𝐯𝐞𝐥: Applies to columns and measures 𝐚𝐜𝐫𝐨𝐬𝐬 𝐚𝐥𝐥 𝐯𝐢𝐬𝐮𝐚𝐥s unless overridden. 𝟐) 𝐕𝐢𝐬𝐮𝐚𝐥 𝐋𝐞𝐯𝐞𝐥: 𝐍𝐞𝐰𝐥𝐲 𝐢𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐞𝐝 with the August 2024 version, it allows formatting for any column, measure, or visual calculation within a specific visual, 𝐨𝐯𝐞𝐫𝐫𝐢𝐝𝐢𝐧𝐠 𝐦𝐨𝐝𝐞𝐥-𝐥𝐞𝐯𝐞𝐥 𝐬𝐞𝐭𝐭𝐢𝐧𝐠𝐬. 𝟑) 𝐄𝐥𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐯𝐞𝐥: Used for specific visual elements like 𝐝𝐚𝐭𝐚 𝐥𝐚𝐛𝐞𝐥𝐬, 𝐨𝐯𝐞𝐫𝐫𝐢𝐝𝐢𝐧𝐠 𝐛𝐨𝐭𝐡 𝐦𝐨𝐝𝐞𝐥 𝐚𝐧𝐝 𝐯𝐢𝐬𝐮𝐚𝐥 𝐥𝐞𝐯𝐞𝐥𝐬. 📊 For example, we can format a measure as a whole number on one visual while keeping it as a decimal in the model, or apply scientific notation only to data labels. This hierarchy ensures that the most specific formatting settings are applied, offering greater control and customization. #PowerBI #DataVisualization #BusinessIntelligence #DataAnalysis

8 out of 10 analysts struggle with delivering impactful data visualizations. Here are five tips that I learned through my experience that can improve your visuals immensely: 1. Know Your Stakeholder's Requirements: Before diving into charts and graphs, understand who you're speaking to. Tailor your visuals to match their expertise and interest levels. A clear understanding of your audience ensures your message hits the right notes. For executives, I try sticking to a high-level overview by providing summary charts like a KPI dashboard. On the other hand, for front-line employees, I prefer detailed charts depicting day-to-day operational metrics. 2. Avoid Chart Junk: Embrace the beauty of simplicity. Avoid clutter and unnecessary embellishments. A clean, uncluttered visualization ensures that your message shines through without distractions. I focus on removing excessive gridlines, and unnecessary decorations while conveying the information with clarity. Instead of overwhelming your audience with unnecessary embellishments, opt for a clean, straightforward line chart displaying monthly trends. 3. Choose The Right Color Palette: Colors evoke emotions and convey messages. I prefer using a consistent color scheme across all my dashboards that align with my brand or the narrative. Using a consistent color scheme not only aligns with your brand but also aids in quick comprehension. For instance, use distinct colors for important data points, like revenue spikes or project milestones. 4. Highlight Key Elements: Guide your audience's attention by emphasizing critical data points. Whether it's through color, annotations, or positioning, make sure your audience doesn't miss the most important insights. Imagine presenting a market analysis with a scatter plot showing customer satisfaction and market share. By using bold colors to highlight a specific product or region, coupled with annotations explaining notable data points, you can guide your audience's focus. 5. Tell A Story With Your Data: Transform your numbers into narratives. Weave a compelling story that guides your audience through insights. A good data visualization isn't just a display; it's a journey that simplifies complexity. Recently I faced a scenario where I was presenting productivity metrics. Instead of just displaying a bar chart with numbers, I crafted a visual story. I started with the challenge faced, used line charts to show performance fluctuations, and concluded with a bar chart illustrating the positive impact of a recent strategy. This narrative approach helped my audience connect emotionally with the data, making it more memorable and actionable. Finally, remember that the goal of data visualization is to communicate complex information in a way that is easily understandable and memorable. It's both an art and a science, so keep experimenting and evolving. What are your go-to tips for crafting effective data visualizations? Share your insights in the comments below!

𝗥𝗲𝗱𝗲𝗳𝗶𝗻𝗶𝗻𝗴 𝗟𝗲𝗴𝗲𝗻𝗱𝘀 𝗶𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜: 𝗨𝘀𝗶𝗻𝗴 𝗕𝗔𝗦𝗘64 𝗜𝗺𝗮𝗴𝗲𝘀 𝗳𝗼𝗿 𝗖𝘂𝘀𝘁𝗼𝗺 𝗩𝗶𝘀𝘂𝗮𝗹𝘀 Power BI’s default legends are functional, but not always flexible. They take up space, limit design options, and don’t always match the look you want. A simple way to take control is by using 𝗕𝗔𝗦𝗘64 𝗶𝗺𝗮𝗴𝗲𝘀 inside custom visuals. This lets you design your own legend system with icons, logos, or stylised shapes - all within Power BI. ✅ Why it’s worth trying: • 𝗗𝗲𝘀𝗶𝗴𝗻 𝗳𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆 → swap plain text for icons or branded graphics • 𝗦𝗽𝗮𝗰𝗲 𝗼𝗽𝘁𝗶𝗺𝗶𝘀𝗮𝘁𝗶𝗼𝗻 → cleaner, inline indicators instead of bulky legends • 𝗖𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆 → align with brand guidelines or client design systems • 𝗨𝘀𝗲𝗿 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 → faster to scan and interpret at a glance ⚙️ How to set it up: 1. Create or source your icons (PNG → BASE64 conversion works well). 2. Convert them into BASE64 strings. 3. Store those strings in a table (e.g. LegendIcons). 4. Set the column’s Data Category to “Image URL” so Power BI renders the BASE64 as an image. 5. Bind the column to an Image custom visual. 6. Place the icons wherever you need them - legends, headers, KPI cards, or even table rows. This approach lets you 𝗱𝗶𝘁𝗰𝗵 𝗿𝗶𝗴𝗶𝗱 𝗱𝗲𝗳𝗮𝘂𝗹𝘁𝘀 and treat your report more like a designed application. Small tweaks like this can transform how polished and usable your dashboards feel. #PowerBI #UIUX #DataViz

Clear communication of research findings is one of the most overlooked skills in UX and human factors work. It’s one thing to run a solid study or analyze meaningful data. It’s another to present that information in a way that your audience actually understands - and cares about. The truth is, most charts fall short. They either say too much, trying to squeeze in every detail, or they say too little and leave people wondering what they’re supposed to take away. In both cases, the message gets lost. And when you're working with stakeholders, product teams, or executives, that disconnect can mean missed opportunities or poor decisions. Drawing from some of the key ideas in Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic, I’ve been focusing more on what it takes to make a chart actually work. It starts with thinking less like an analyst and more like a communicator. One small but powerful shift is in how we title our visuals. A label like “Sales by Month” doesn’t help much. But a title like “Sales Dropped Sharply After Q2 Campaign” points people directly to the story. That’s the difference between describing data and communicating an insight. Another important piece is designing visuals that prioritize clarity. Not every chart needs five colors or a complex legend. In fact, color works best when it’s used sparingly, to highlight what matters. Likewise, charts packed with gridlines, borders, and extra labels often feel more technical than informative. Simplifying them not only improves readability - it also sharpens the message. It also helps to think ahead to the question your visual is answering. Is it showing change? Comparison? A trend? Knowing that upfront lets you choose the right format, the right focus, and the right amount of detail. In the examples I’ve shared here, you’ll see some common before-and-after chart revisions that demonstrate these ideas in action. They’re simple changes, but they make a real difference. These techniques apply across many research workflows - from usability tests and survey reports to concept feedback and final presentations. If your chart needs a walkthrough to make sense, it’s probably not working as well as it could. These small adjustments are about helping people see what’s important and understand what it means - without needing a data dictionary or a deep dive.

🎨 𝗗𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗖𝘂𝘀𝘁𝗼𝗺 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗩𝗶𝘀𝘂𝗮𝗹𝘀 𝘄𝗶𝘁𝗵 𝗙𝗶𝗴𝗺𝗮! One of the aspects I truly enjoy about data visualization and design in Power BI is the creative freedom it offers. While the native visuals cover most of the basic needs, there's always that extra edge you can achieve by incorporating HTML or SVG to tailor everything exactly to the client’s specifications. ✨ This is where Figma comes into play! It's my go-to tool for creating mockups, background templates, and SVG elements for custom visuals. It’s incredibly intuitive and easy to use, which is why I rely on it often for designing visuals that go beyond the ordinary. The visual added as a .gif to the post was created entirely in Figma —it's a simple yet effective infographic that dynamically represents 1 of 5 different states based on a rating. Not only does it look great, but it's also highly customizable, offering a level of freedom that native Power BI visuals simply can't match. 𝗛𝗲𝗿𝗲’𝘀 𝗺𝘆 𝗽𝗿𝗼𝗰𝗲𝘀𝘀: 1️⃣ 𝗗𝗲𝘀𝗶𝗴𝗻 𝘁𝗵𝗲 𝘃𝗶𝘀𝘂𝗮𝗹 𝗶𝗻 𝗙𝗶𝗴𝗺𝗮. Design the visual in Figma for all possible states, or just for a single state if you prefer to have full control over its behavior using DAX. 2️⃣ 𝗘𝘅𝗽𝗼𝗿𝘁 𝗶𝘁 𝗮𝘀 𝗮𝗻 𝗦𝗩𝗚. Once the visual is created, export it as an SVG file. Then, open the file in Notepad, where you'll see the code that defines your SVG vector visual. Copy the code into a Power BI Measure, ensuring you switch all double quotes (") to single quotes ('). 3️⃣ 𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝘁𝗵𝗲 𝗦𝗩𝗚 𝗰𝗼𝗱𝗲 𝗶𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝘂𝘀𝗶𝗻𝗴 𝗺𝗲𝗮𝘀𝘂𝗿𝗲𝘀. You can customize it further to make it dynamic based on Power BI data—no limits except your creativity! 🌐 𝗖𝗵𝗲𝗰𝗸 𝗼𝘂𝘁 𝘁𝗵𝗲 𝗢𝗻𝗹𝗶𝗻𝗲 𝗩𝗲𝗿𝘀𝗶𝗼𝗻: https://lnkd.in/duF5KBYG What are your thoughts? Do you use Figma in your daily work? If so, for what purposes? Let's chat! #analytics #data #powerbi #datavisualization #report #dashboard #reporting #visualization #microsoftpowerbi #pbicorevisuals #svg #html #customvisuals #UXDesign #Figma

You should group information, prevent overload. Our brain can only process a limited amount of information at once. Yet, we display information all at once. Users Freeze. When you feed information in chunks, end-users can decide more efficiently. Group what belongs together. Then reveal detail on demand. You can: 🔹 Group charts visually. Use whitespace & alignment so users consume related visuals together. 🔹 Use subtle containers. Light borders on white, white tiles on light-grey just enough structure to signal groups. 🔹 Share axes & titles. Consistent scaffolding reduces mental switching costs. 🔹 Chunk inside charts. Intentional spacing and consistent colors across pages accelerate pattern recognition. 🔹 Label directly. Put text where eyes land to ease working-memory load. 🔹 Use progressive disclosure. Show only what’s relevant for the task; reveal details via drill/hover when needed. 🔹 Visual hierarchy. Lead with Level 1 KPIs, then Levels 2 & 3, guide the sequence of attention. 𝗥𝗲𝗺𝗲𝗺𝗯𝗲𝗿: If you design for how people think, not how much data you have, users stop struggling to find the right info and start deciding. #Datavisualization #Businessintelligence #Dashboard