Data-driven decision making is integral for any organization. However, just because you have the data, doesn’t mean you’re able to make sense of it and draw useful insights. That’s where data visualization comes in. When you implement good data visualization techniques on your analytics dashboards, you effectively communicate the meaning of your data to your business users. Data visualization allows you to take raw, disorganized data points and present them in a way that enables better decision making.What is Data Visualization and Why is It Important?Believe What You See When You See ItJust as anything in life, depending on which angle you’re looking at something, the story you tell will change. The same is true with data. The narrative is completely dependent on what you see and when you see it, which is why data visualization is key to better decision-making.Data on its own and in its raw format cannot easily show relationships, correlations, and patterns. In 1973, statistician Francis Anscombe constructed “Anscombe’s Quartet” to demonstrate the importance of graphic data to support statistical analysis.Data visualization is graphical representation of information, often self-service, that allows business users to easily understand data trends, outliers, and patterns. The right data visualizations can allow even the most novice of end users to consume and understand the most important information needed to achieve objectives and make data-driven decisions.The Key to Designing the Vision That Anyone Can See With modern analytics tools in place, the same data can be leveraged to tell different stories, which is especially important when you have users with different needs. However, just because you have the technology in place, there are still so many ways to design a dashboard, making it difficult to decipher how to do so in order to glean the insights you need.Here are six tips from our experts on how to create data visualizations that provide the most value to your organization:Step 1: Understand Context Knowing your audience and their data needs is key to creating powerful data visualizations. Understand that this will vary from business functions and users and that it can change over time.Start with an exploratory analysis. Ask questions to better understand what each user is looking to learn from the data and how this will help them more effectively move the overall business objective forward. Dig to understand what a successful outcome looks like and the nuances that can lead to getting there.Next, do an explanatory analysis where you explain the meaning of your data. This is where context matters. If you know your audience, you’ll be better equipped to tailor the story your data tells to their specific needs. The data visualization you create will help support each narrative because you’ve chosen the right angle to showcase.Step 2: Ensure the Dashboard Layout Emphasizes Your Primary KPIBy now, we’ve all learned that simplicity leads to ease—at least this is true when it comes to understanding complex information, such as data. The layout of your dashboard should facilitate a natural flow to help users consume the information you are providing.Seek user feedback from all teams to document all KPIs so that they find their place somewhere within the dashboard.Understand the relationship and dependencies between KPIs to determine your primary KPIs and the driving metrics that influence them.Put your most important KPIs along the top, with your primary KPI in the upper left corner, and supporting metrics below.Not everything needs to be viewable on the initial dashboard; incorporate the ability to provide more context with drill down and filter functionality as needed. This layout is a great starting point for creating a dashboard that guides users to insights. Elements of a DashboardStep 3: Follow Simple Design TechniquesJust as important as layout is design. A well- designed dashboard highlights what’s important and promotes intuitive understanding. When design lacks thoughtful hierarchy, the user won’t know where to start.Design the dashboard the way we read: from top to bottom and from left to right.Provide space and contrast between different datapoints to help guide the user through what is important, what is related, and the why behind both.Think about alignment and color among other design elements, too. Without a consistent layout, users can easily get distracted. And with too many colors, users can easily get confused.Reserve certain colors to highlight important pieces of information, such as red for decreases and green for increases.Use a monotonous color scheme to show relation and use a contrasting color scheme to show difference. There are a number of different ways to use color but be sure to remain consistent and thoughtful.Keeping in mind color-blind users, you may want to print in grayscale to test the contrast on your visualization. Flow, Alignment, and Color MatterStep 4: DeclutterThe KonMari Method coined by Marie Kondo encourages keeping only those things that speak to the heart and discarding items that no longer spark joy. You can apply this same method to creating data visualizations: If it doesn’t add meaning to the chart, don’t use it.This is true not only for the data within the dashboard, but the design and layout elements as well.Remember, less is more, and simplicity makes that which is complex more consumable.Start with adding clean lines, incorporating aesthetic use of white space, removing chart borders and gridlines, and labeling data directly just to name a few things.Step 5: Be Mindful of Size, Order, and QuantityAs you think about layout, design, and decluttering and all the things you leave out, you should also spend time thinking about being intentional of what you put in the dashboard.Think about how you use graphs: what and how many you include, what each represents, as well as width and space between bars and lines.Is it easy for users to follow and glean the insights they need? Always refer back to understanding who your audience is, what their needs are, and how to best provide the information they need quickly and effectively. Bar Chart Spacing and WidthStep 6: Avoid These Design PitfallsAs you think about how your data visualization dashboard will tell a story, avoid elements that could potentially visually skew data. There are some graph types and design techniques that detract from visualizations. If you can, avoid using pie charts, donut charts, 3D designs, and secondary y-axes.Remember, data visualization dashboards should point users to insights, not just access to their data. 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