Tips for Making Data Look Good in Presentations

I used to think colorful charts helped display information. Now I know they do exactly the opposite. When it comes to data visualization, color *is* crucial. But not in the way you’ve likely been taught. The general rule of thumb is that you should use color sparingly and strategically. In other words, never use color for the sake of being color*ful*. Here’s how: First, identify your core colors (I recommend 1-2 max): Option 1 ↳ Use your company’s (or client’s) brand colors. This is often the easiest and best choice. (But remember, you don’t have to use *all* the brand colors.) Option 2 ↳ Use an online color palette (check out the resources linked in the comments to get started). I’ve also searched Pinterest for things like “blue and green color palettes.” Second, follow best practices: Use grey as your default.  ↳ Create all your charts in greyscale first. Then, incorporate color to draw your audience’s eyes to the most important takeaways or data points. Use 1-2 core colors throughout your presentation.  ↳ Use your core colors to highlight the specific trends, categories, or insights you want your audience to pay attention to. Be aware of cultural associations.  ↳ Color symbolism varies across the globe - for example, red often carries a negative connotation in Western cultures, but represents luck and prosperity in Eastern/Asian cultures. Be mindful of color blindness.  ↳ Approximately 8% of men and 0.5% of women are colorblind (red-green being the most common). In general, less is more. Imagine someone were to look at your chart and say “Why is THAT particular bar blue? Why is THAT one green?” If you can’t give a clear answer, it's time to go back to the drawing board. —-— 👋🏼 I’m Morgan. I share my favorite data viz and data storytelling tips to help other analysts (and academics) better communicate their work.

A common mistake data storytellers make is 𝐨𝐯𝐞𝐫𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐭𝐡𝐞 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐜𝐞 𝐨𝐟 𝐰𝐡𝐢𝐭𝐞 𝐬𝐩𝐚𝐜𝐞 in their data scenes. White space is the empty space in a layout that helps create focus and balance. In an effort to add clarity and depth, we often fill slides with: 1️⃣ More text 2️⃣ More data 3️⃣ More charts 4️⃣ More graphics But instead of adding value, this "stuff" creates noise, distracting from our key messages.   𝐖𝐡𝐢𝐭𝐞 𝐬𝐩𝐚𝐜𝐞 𝐢𝐬𝐧’𝐭 𝐰𝐚𝐬𝐭𝐞𝐝 𝐬𝐩𝐚𝐜𝐞—𝐢𝐭’𝐬 𝐚 𝐭𝐨𝐨𝐥 𝐭𝐨 𝐟𝐨𝐜𝐮𝐬 𝐲𝐨𝐮𝐫 𝐚𝐮𝐝𝐢𝐞𝐧𝐜𝐞’𝐬 𝐚𝐭𝐭𝐞𝐧𝐭𝐢𝐨𝐧. It makes your content clearer, easier to process, and more impactful. Before adding any elements, ask yourself: "Is this essential?" 👉 𝐓𝐞𝐱𝐭: Use annotations judiciously to add context and draw attention to key data points. Avoid adding “dense” commentary to your story unless it is meant to be read (asynchronous), not presented live (synchronous). 👉 𝐃𝐚𝐭𝐚: Include more data only when it’s necessary to provide meaningful context or preemptively address key questions. 👉 𝐂𝐡𝐚𝐫𝐭𝐬: Use multiple charts sparingly. They should have a clear purpose, like enabling direct comparisons, rather than the result of just wanting to reduce a presentation’s slide count. 👉 𝐆𝐫𝐚𝐩𝐡𝐢𝐜𝐬: Leverage visuals to highlight key points or reinforce messages but avoid purely decorative elements. Maximize white space to emphasize your story’s key messages. Don’t let clutter dilute your story’s impact. Let’s use the power of white space to create clearer, more impactful #datastorytelling that truly resonates with audiences. How do you resist the urge to add more “stuff” to your data scenes? What are the most egregious forms of clutter? 🔽 🔽 🔽 🔽 🔽 Craving more of my data storytelling, analytics, and data culture content? Sign up for my newsletter today: https://lnkd.in/gRNMYJQ7 Check out my new data storytelling masterclass: https://lnkd.in/gy5Mr5ky Need a virtual or onsite data storytelling workshop? Let's talk. https://lnkd.in/gNpR9g_K

Want to create better dataviz? Before you call your next data visualization complete, make sure its passes these three tests: 1. The Spartan Test: Strip it down. Ruthlessly assess every element in your chart. If removing something doesn’t change the message, it’s clutter. Clear visuals build trust — give your audience only what they need. 2. The Peek Test: Look away for 5 seconds, then glance back at your visual. Where does your eye go first? Chances are, that’s where your audience will focus too. Adjust until attention is drawn to the key insight. 3. The Colleague Test: Think it’s perfect? Share it with a colleague who hasn’t seen the analysis. Provide minimal context and give them 10-15 seconds to interpret. Ask what they take away — does it match your intent? Nail these three, and your data visualization will not just look good — it will communicate clearly and effectively. Three passing grades means it's ready to be presented. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

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!

Do you want your data to make a difference? Transform your numbers into narratives that drive action—follow these five key steps: 📌 STEP 1: understand the context Before creating any visual, ask: - Who is your audience? - What do they need to know? - How will they use this information? Getting the context right ensures your message resonates. 📊 STEP 2: choose an appropriate graph Different visuals serve different purposes: - Want to compare values? Try a bar chart. - Showing trends? Use a line graph. - Need part-to-whole context? A stacked bar may work. Pick the right tool for the job! 🧹 STEP 3: declutter your graphs & slides More isn’t better. Remove unnecessary elements (gridlines, redundant labels, clutter) to let your data breathe. Less distraction = clearer communication. 🎯 STEP 4: focus attention Not all elements on your graphs and slides are equal. Use: ✔️ Color ✔️ Annotations ✔️ Positioning …to guide your audience’s eyes to what matters most. Help them know where to look and what to see. 📖 STEP 5: tell a story Numbers alone don’t inspire action—stories do. Structure your communication like a narrative: 1️⃣ Set the scene 2️⃣ Introduce the conflict (tension) 3️⃣ Lead to resolution (insight or action) Make it memorable! THAT'S the *storytelling with data* process! ✨ Following these five steps will help you create clear, compelling data stories. What's your favorite tip or strategy for great graphs and powerful presentations? Let us know in the comments!