How to Use Graphs in Presentations

Most people don’t need more charts. They need the right chart. This graphic shows 50 ways to visualize data — and that’s exactly why many dashboards are confusing. Too many choices, not enough thinking. Here’s how I’d use this: Start with the question, not the chart. Comparison? Use column/bar. Trend? Line, area, or sparkline. Distribution? Histogram or box/violin (not 12 pie charts…). Choose by relationship, not aesthetics. Correlation → scatter, correlogram. Composition → stacked bar/area, not donut overload. Flow or structure → Sankey, org chart, network. One insight per visual. If your audience can’t say, “This chart shows X,” in 5 seconds, it’s decoration, not communication. Reduce cognitive load. Fewer colors. Clear labels. No 3D anything. Ever. Build your “go-to 10.” From these 50, pick 10 charts you’ll master. Use them 90% of the time. The pros look “simple” because they obsess over clarity, not complexity. Save this as a checklist for your next report or dashboard. And if you want to go deeper into data storytelling and visualization, Corporate Finance Institute® (CFI)'s resources are a great place to start.

Most plots fail before they even leave the notebook. Too much clutter. Too many colors. Too little context. I have a stack of visualization books that teach theory, but none of them walk through the tools. In Effective Visualizations, I aim to fix that. I introduce the CLEAR framework—a simple checklist to rescue your charts from confusion and make them resonate: Color: Use color sparingly and intentionally. Highlight what matters. Avoid rainbow palettes that dilute your message. Limit plot type: Just because you can make a 3D exploding donut chart doesn’t mean you should. The simplest plot that answers your question is usually the best. Explain plot: Add clear labels, titles. Remove legends! If you need a decoder ring to read it, you’re not done. Audience: Know who you’re talking to. Executives care about different details than data scientists. Tailor your visuals accordingly. References: Show your sources. Data without provenance erodes trust. All done in the most popular language data folks use today, Python! When you build visuals with CLEAR in mind, your plots stop being decorations and start being arguments—concise, credible, and persuasive.

Here are 13 chart types — and exactly when to use each one. 📊 Save this. Use it every time you build a report. 📈 TREND OVER TIME 1. Line Chart → Use when: Showing how a metric changes over weeks, months, quarters. → Example: Monthly revenue over 12 months. → Rule: More than 4 time periods = line chart, not bar chart. 2. Area Chart → Use when: Same as line, but you want to emphasize volume or cumulative totals. → Example: Stacked area showing revenue by region over time. → Rule: Use stacked area for part-to-whole over time. 3. Sparklines → Use when: You need a tiny trend inside a table cell. No axes, no labels — just the shape. → Example: A KPI table with a mini trend next to each metric. → Rule: Perfect for dashboards where space is limited. 📊 COMPARISON 4.Bar Chart (Horizontal) → Use when: Comparing categories with long names. → Example: Sales by product name, revenue by country. → Rule: If labels are longer than 2 words — go horizontal. 5. Column Chart (Vertical) → Use when: Comparing categories across time or short labels. → Example: Q1 vs Q2 vs Q3 vs Q4 revenue. → Rule: Max 6-8 columns. More = cluttered. 6. Clustered Bar / Column → Use when: Comparing 2-3 series side by side. → Example: This year vs last year sales by region. → Rule: Never cluster more than 3 series. It becomes unreadable. 7. 🍩 PART OF A WHOLE Pie Chart → Use when: Showing 2-4 segments of a total. That is it. → Example: Market share split between 3 competitors. → Rule: More than 5 slices = stop. Use a bar chart instead. 8. Donut Chart → Use when: Same as pie but you want a cleaner look or a KPI number in the center. → Example: "78% complete" with a single donut ring. → Rule: One donut = beautiful. Nested donuts = nightmare. 9. Treemap → Use when: Showing hierarchical part-to-whole with many categories. → Example: Budget allocation across 20 departments and sub-departments. → Rule: Use when pie chart would have too many slices. 🎯 SINGLE VALUE / KPI 10. KPI Card → Use when: Showing one important number with context (vs target or vs last period). → Example: "Revenue: $1.2M ▲ 12% vs LY". → Rule: Every dashboard needs 3-5 KPI cards at the top. Executives look here first. 11. Gauge Chart → Use when: Showing progress toward a single goal. → Example: "Q3 target: 75% achieved." → Rule: Use sparingly. One gauge = clear. Five gauges = a cockpit nobody reads. 📍 DISTRIBUTION & RELATIONSHIP 12. Scatter Plot → Use when: Exploring relationship between two numeric variables. → Example: Ad spend vs revenue — is there a correlation? → Rule: Add a trendline. Without it, scatter plots confuse most viewers. 13. Histogram → Use when: Showing distribution of a single variable. → Example: How many employees fall into each salary range? → Rule: Choose bin sizes carefully. Too few = vague. Too many = noisy. Print this. Pin it on your wall. Share it with your team. What chart type do YOU use most? 👇

Choosing the right chart is half the battle in 𝐃𝐚𝐭𝐚 𝐒𝐭𝐨𝐫𝐲𝐭𝐞𝐥𝐥𝐢𝐧𝐠. This one visual helped me go from “𝐖𝐡𝐢𝐜𝐡 𝐜𝐡𝐚𝐫𝐭 𝐝𝐨 𝐈 𝐮𝐬𝐞?” → “𝐆𝐨𝐭 𝐢𝐭 𝐢𝐧 10 𝐬𝐞𝐜𝐨𝐧𝐝𝐬.”👇 The right chart makes insights stick. The wrong one? Confusion. 𝐇𝐞𝐫𝐞'𝐬 𝐦𝐲 𝐃𝐚𝐭𝐚 𝐒𝐭𝐨𝐫𝐲𝐭𝐞𝐥𝐥𝐢𝐧𝐠 𝐂𝐡𝐞𝐚𝐭𝐬𝐡𝐞𝐞𝐭 – which chart to use, when, and why: 𝟏. 𝐁𝐚𝐫 𝐂𝐡𝐚𝐫𝐭 – Compare values across categories • When: Sales by region, product performance • Why: Our brains process length differences instantly 𝟐. 𝐋𝐢𝐧𝐞 𝐂𝐡𝐚𝐫𝐭 – Show trends over time • When: Revenue growth, user adoption curves • Why: Makes patterns and changes obvious 𝟑. 𝐏𝐢𝐞 𝐂𝐡𝐚𝐫𝐭 – Display parts of a whole • When: Market share, budget allocation • Why: Works when you have 5 or fewer segments 𝟒. 𝐒𝐜𝐚𝐭𝐭𝐞𝐫 𝐏𝐥𝐨𝐭 – Find relationships between variables • When: Price vs. demand, experience vs. salary • Why: Reveals correlations and outliers 𝟓. 𝐇𝐢𝐬𝐭𝐨𝐠𝐫𝐚𝐦 – Show frequency distribution • When: Customer age ranges, response times • Why: Spots normal vs. skewed distributions 𝟔. 𝐑𝐚𝐝𝐚𝐫 𝐂𝐡𝐚𝐫𝐭 – Compare multi-dimensional data • When: Employee skills assessment, product features • Why: Shows strengths and gaps at a glance 𝟕. 𝐌𝐚𝐩 – Visualize geographic data • When: Sales by state, store locations • Why: Location patterns jump out immediately 𝟖. 𝐇𝐞𝐚𝐭𝐦𝐚𝐩 – Highlight intensity patterns • When: Website clicks, correlation matrices • Why: Color gradients reveal hot spots 𝟗. 𝐁𝐮𝐛𝐛𝐥𝐞 𝐂𝐡𝐚𝐫𝐭 – Display three variables • When: Market cap vs. growth vs. profit margin • Why: Adds a third dimension through size 𝟏𝟎. 𝐃𝐨𝐧𝐮𝐭 𝐂𝐡𝐚𝐫𝐭 – Modern take on pie charts • When: KPI progress, category breakdown • Why: Center space for key metrics 𝐏𝐫𝐨 𝐭𝐢𝐩: Match your chart to your audience's decision. Executives need trends? Line chart. Team needs to compare options? Bar chart. The right visualization = clearer insights, faster decisions, stronger impact. ♻️ Save this guide for your next presentation! 𝐏.𝐒. I share job search tips and insights on data analytics & data science in my free newsletter. Join 16,000+ readers here → https://lnkd.in/dUfe4Ac6

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!

The no-bullsh*t playbook for building a winning MBB-style PPT When a client tells me: “Can you make this deck prettier?”. What they mean is: “I don’t understand a damn thing; help me.” Because if the presentation were clear, no one would care about the design. If MBB was about aesthetics, we’d hire cartoonists and museum curators, not top-tier analysts, economists, and engineers. Yet, people struggle with decks because no one teaches you how to structure a presentation that drives decisions. So here’s your no-BS playbook. Save it. Use it EVERY-SINGLE-TIME. 1. Every great deck starts with the storyline Your presentation is a narrative, not a collection of slides. • Start with the problem → “Why are we even discussing this?” • Support with evidence → “What do we know for sure?” • Lay out the options → “What choices do we have?” • Land the recommendation → “What’s the best move forward?” Start always with the main takeaway and then build the flow. Before jumping into slides, summarize your whole deck in five to ten bullet points; otherwise, you won’t have a deck; you will have a mess. 2. Your slide titles should tell the full story A classic MBB rule: You should be able to read just the slide titles and get the full story. • “Market trends” says nothing. • “The market is growing 15%, but only 3 players capture 80% of the upside” makes the insight obvious. If your audience has to read graphs and footnotes to understand the key message, your slide has failed. 3. Use visuals for impact, not decoration Consultants don’t add charts because they “look nice.” We add them because they clarify the story. A giant data dump with no clear takeaway is useless. A bar chart showing a clear comparison, with the key insight highlighted, adds value. Use the right tool for the job: • Bar charts → For comparisons • Line charts → For trends over time • Scatter plots → For correlations • Heatmaps → To emphasize intensity and distribution • Tables → Only if they’re digestible in seconds Your visuals exist to reduce cognitive load, not increase it. 4. Prioritize signal over noise A simple test: If your boss came and said, “Cut this to 10 slides,” could you do it while keeping all the critical insights? If yes, your deck is well structured. If not, you’re adding noise. Every 100-page deck should be distillable into 10 critical pages if needed. Every slide should add new critical insight. If it doesn’t, move it to backup. 5. Make decisions easy The best decks don’t just inform. They drive decisions. Your final slide should answer: So what? What do we do next? A deck that doesn’t lead to action is just another PowerPoint, not a decision-making tool. Bottom line: A great deck isn’t about aesthetics. It’s about clarity, structure, and impact.

I was sitting in a meeting, and a graph popped up during the presentation. It had five different colors, two types of chart elements (bars and lines), and it told multiple stories. I didn’t know where to look. My eyes – and brain – eventually gave up. The five-second rule (not the one about dropping food on the ground!) came from user research, and it measures how effectively information is communicated to the audience within the first five seconds. Originally used for testing web pages, it is now a recommended guide for interactive visual images – like infographics, charts, etc. Before you insert a complex graph into a presentation, I beg you to step away from your Excel file and consider the following: ☑ Can an audience understand this in five seconds? ☑ Is there a better way to tell this in a narrative? ☑ Is the chart necessary? If so, how can it be simplified? Does it have a clear title? Easy elements to understand? Remember, the more data points you have in a visual, the harder it is for your audience to know where to focus. And, if they are trying to figure out an image, they aren’t listening to you! Also, you have the curse of knowledge. You’ve been staring at this data for longer than five seconds. You are assuming your audience will know more than they do! Data is only helpful IF your audience can understand it; otherwise, it’s a reason for them to tune out! What are your tricks for simplifying complex information in presentations? I break charts into one or two slides, and I tell a story with them. Your audience needs to know why this chart matters to them! (I also avoid all the fancy options like 3D and breaking up pie charts! Simplicity for the win!) #CommunicationTips Image credit: visme dot com

Don’t let your visuals kill your insights. These 4 graph elements do exactly that. If it looks good but communicates nothing, It’s decoration - not data. Clarity > aesthetics. Here are 4 things to avoid - and what to do instead: 1. Pie Charts Hard to compare angles. Can’t judge how much bigger one slice is than another. Instead: - Use a horizontal bar chart (clear baseline) - Sort values to highlight what matters 2. Donut Charts Arc lengths are even harder to read than pie slices. Instead: - Use a horizontal bar chart (clear baseline) - Make comparisons easy and instant 3. Dual Y-Axis Charts Confusing. Readers don’t know which data belongs to which axis. Instead: - Label the second dataset directly - Or split the chart and share a common x-axis 4. Axis + Data Labels Repeating values adds clutter without insight. Instead: - Show the axis or label the data - not both - Remove gridlines to reduce noise Most charts are forgettable. Clear ones get people to act. 💬 Drop a comment - What’s one design habit you’ve had to unlearn? 👇 ♻️ Follow Mike Reynoso for more tips on clear, actionable BI communication. 🔁 Reshare to help others turn cluttered charts into meaningful insight. 📌 Save this post — better data storytelling starts with better visuals.

They’re not disinterested. They’re just overwhelmed by your graph. Let’s fix it. Most researchers present graphs like this: A vague title. A sea of bars or dots. No clear takeaway. The result? Your audience's working memory is overloaded. But here’s the good news: 3 simple steps can change everything: 1. Turn your title into a headline. Tell them why the graph matters. 2. Highlight key data. Use color or callouts to direct attention where it counts. 3. Align your text with the data. Don’t make people hunt for meaning, bring it to them. It’s not about dumbing down your research. It’s about clearing the path to insight. And when you do that? Your ideas land. Your message sticks. Your impact grows. That's the secret to success.