Data Visualization Best Practices

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Data visualization of Chainsmokers popularity

When you think of data visualization, you might think of simple and stuffy Excel charts, but the practice often is much more creative and visually stunning. Data visualization is meant to tell a story, and can make or break the effect of your analysis.

Data Visualization Communicates Your Research

Data analysis gives you insight into your research at many different levels, but any data you’re collecting might as well be useless if no one can understand it! That’s where data visualization comes in. Compelling visualizations make your data easier to digest at a glance by communicating your findings in fast, snackable ways. One of the worst things that can happen to an analyst is presenting research only to have it fall on deaf ears. There are a few best practices you can follow when thinking about data visualization to ensure your analyses aren’t overlooked.

Know Your Audience

When presenting your research, it’s important to remember who your audience is. Are you speaking to someone technical? A high level decision maker? Someone on your marketing team? Different stakeholders have different motivations that you want to capture and reflect in your presentations.

For example, while your fellow analysts may want to talk raw data with you, your CEO and other high level decision makers are more often looking for snapshots they can run with. Including visuals–like heat maps, graphs and interactive dashboards–in your presentations or reports helps to explain your results through quick bites and key takeaways.

However, as a best practice, you want to avoid trying to serve your different audiences through one single report. Rather, identify the key stakeholders for a project and focus on delivering the information that is important to them. This may mean you have to create multiple reports using the same data, but geared toward your different audiences.

Engage Your Audience with Simple & Clear Visualizations

The New York Times provides an excellent example of using data visualization to clearly and easily present their findings to the general public. The news outlet worked with Youtube’s streaming data to analyze the popularity of the 50 most watched Billboard 100 artists across the United States, and presented their findings through visual heat maps. The map below uses color to gauge the popularity of the music duo The Chainsmokers by region. The different levels of color saturation show that the Northeast and parts of the Midwest are clear hotspots for the band.

music-popularity-heatmap

Based on the trends shown in this graphic alone, you can quickly identify opportunities to leverage the band’s popularity. If you were their tour manager, you might recommend focusing on the hotspots for concerts since they’d likely garner attention. Conversely, you could also identify and develop strategies to target the obvious weak spots. This heat map is simple and easy to understand at a glance, yet powerful–a perfect snapshot that anyone who reads the New York Times can understand.

Define Your Purpose & Goals

Every project has a goal. As you define your audience, you start to identify the key KPIs or insights that are important for your stakeholders to know. And depending on the purpose of your project and the type of data you’re presenting, some visual elements will work better than others. Choosing the right representation is an art in and of itself.

In the example above, quantitative data (i.e. the number of people who listen to The Chainsmokers) is displayed via a heat map. The darker areas signify a higher number of people streaming their music. A bar graph would also work well to display quantitative information like this, where a line graph might help to gauge popularity trends in a certain region over time.

Classify Your Project

Once you understand the goals of your project, you can determine which category it falls into. There are three types of data visualizations: strategic, analytical and operational. Strategic visualizations and dashboards typically reflect high level goals and KPIs, where analytical reports are often more interactive, and allow you to drill down and look at your data from different angles. Operational reports, on the other hand, focus on metrics that are associated with and track business processes. Classifying your data in this way helps to ensure that your visualizations support the overall project goals.

Define Your Visualization Process

Data visualization is an iterative process–you might create hundreds of different graphs and charts for a project and only present a few–but you’ll want to define the schema for your visualizations so that they are consistent. This helps to avoid confusing your audience and also supports quality control and continuous improvement.

Start Visualizing Your Data With Tableau  

Tableau is an industry standard tool for data analysis and visualization. It’s inherently focused on making your data attractive and easy to understand, and not to mention, user-friendly. With a number of different chart types available, you have ample opportunity to explore the system and create exciting and meaningful visuals. You can even attend workshops specifically devoted to learning data visualization with Tableau!

A picture is worth 1000 words, and that applies to data too. Interested in learning more about data visualization and analytics? Check out our data analytics courses that cover the full suite of programs, tools and techniques.

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