Many businesses track data like their website conversion figures. Compare Figures In Big Data Sets Quickly: You don’t have to own a big business to generate a lot of data.Analyze And Understand Hidden Trends In Your Business Data: While some trends are obvious by looking at a dataset, many datasets are too large to interpret without visualizations.įor example, if you were analyzing your ad retargeting results from a whole year, a data visualization would show you seasonal spikes that you likely couldn’t notice by looking at week-on-week results.Convey Complicated Or Detailed Results To Others: Visualizations can help you explain what your data says to your boss, investors, coworkers, or the media - as they reduce complex data into easily digestible graphics.įor example, if you were doing A/B testing on your WordPress site, you could use data visualization to display results for both the “A” and “B” outcomes so that they are easy to understand.The insight will likely influence which platform you use. Discover BI Insights: Business Intelligence (BI) insights are vital pieces of information that inform your decisions.įor example, if you analyzed your email open rate, it’d be a BI insight to say that your click-through rate (CTR) was higher on emails sent through MailChimp instead of GetResponse.Seeing is believing ✨□ Check out 11 great options for data visualization right here ⬇️ Click to Tweet Why Data Visualization Is Importantĭata visualizations are very useful, as they can help you: “Reliability” refers to how well your data and the methodology behind it measures the thing you’re evaluating, while “validity” refers to how accurate your data itself is. When discussing data, it’s important to note that “reliability” and “validity” are separate things. Step 5: Assess the reliability and validity of your visualization and use the chart as you please.Step 4: Use the software to generate visualizations.Step 3: Export your dataset into your data visualization software.Step 2: “Clean” your data to ensure it’s consistent and error-free.There’s no “one” way to create a data visualization, though the general process of creating one looks like this: Bar charts, which show the distribution of data in two categories (like the results of A/B tests).Scatter plots, which show a relationship between two sets of data (like height vs.Box-and-whisker plots, which offer a dataset’s five-number summary (which includes the minimum, first quartile, median, third quartile, and maximum figures).Gantt charts, which show the timeline of a project.Histograms, which show the distribution of a dataset made up of continuous or discrete data.Timelines, which offer a sequence of events over time.Tables, which show data that’s too complicated for text.Pie charts, which show percentage breakdowns. ![]() Some of the most popular visualizations include: Though you may not work with data every day, you’ve likely used many different types of data visualizations before. ![]() A data visualization tool is software that helps you create a visualization. Data visualization is the process of creating a visual representation of a data set’s trends, patterns, and critical insights.
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