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You’ve got data and you’ve got questions. You know there’s a chart or graph out there that will find the answer you’re looking for, but it’s not always easy knowing which one is best without some trial and error.
This paper pairs appropriate charts with the type of data you’re analyzing and questions you want to answer. But it won’t stop there.
Stranding your data in isolated, static graphs limits the number and depth of questions you can answer. Let your analysis become your organization’s centerpiece by using it to fuel exploration. Combine related charts. Add a map. Provide filters to dig deeper. The impact? Immediate business insight and answers to questions that actually drive decisions.
So, which chart is right for you? Transforming data into an effective visualization (any kind of chart or graph) or dashboard is the first step towards making your data make an impact. Here are some best practices for conducting meaningful visual analysis:
Bar charts are one of the most common data visualizations. With them, you can quickly highlight differences between categories, clearly show trends and outliers, and reveal historical highs and lows at a glance. Bar charts are especially effective when you have data that can be split into multiple categories.
This Pareto chart shows that roughly 20% of all sales are coming from the state of California.
In this example, the bar chart quickly shows when inflation rates rose and dropped. In the first half of the century, the drops were more dramatic than in more recent history.
Tableau is one of the best tools out there for creating really powerful and insightful visuals. We’re using it for analytics that require great data visuals to help us tell the stories we’re trying to tell to our executive management team.
Dana Zuber, Vice President - Strategic Planning Manager
The line chart, or line graph, is another familiar method for displaying data. It connects several distinct data points, presenting them as one continuous evolution. The result is a simple, straightforward way to visualize changes in one value relative to another.
This line chart show which slot machines have the largest winning amount while also showing the seasonality.
Pie charts are powerful for adding detail to other visualizations. Alone, a pie chart doesn’t give the viewer a way to quickly and accurately compare information. Since the viewer has to create context on their own, key points from your data are missed. Instead of making a pie chart the focus of your dashboard, try using them to drill down on other visualizations. This approach uses the pie chart’s simplicity to add information, without distracting from the larger picture.
Adding the pie charts to the map allows the viewer to quickly see how particular states are profiting from different product categories.
Maps are a no-brainer for visualizing any kind of location information, whether it’s postal codes, state abbreviations, country names, or your own custom geocoding. Maps highlight geographic trends in a format everyone knows and understands.
Read Maps: The Power of Where to learn how using maps effectively helps drive better business decisions.
By layering the magnitude of an earthquake on top of the map, the viewer can see where bigger earthquake occur.
Scatter plots are an effective way to give you a sense of trends, concentrations, and outliers that facilitate deeper investigations of your data. A scatter plot presents lots of distinct data points on a single chart. The chart can then be enhanced with analytics like cluster analysis or trend lines.
This scatter plot shows how sales and profit compare across department, and it quickly lets you see any outliers.
Gantt charts are purpose-built for illustrating the start and finish dates of steps in a process or project. A Gantt chart shows steps that need to be completed before others can begin, or which resources are overcommitted.
Gantt charts aren’t limited to projects, though: Represent any time series data with this chart type. Try using a Gantt chart to show how a multi-step process has performed over time. Color can be used to show which steps are under- or over performing.
Using this Gantt chart, the team knows which pieces of content are on schedule and which are running late.
Although bubbles aren’t technically their own type of visualization, using them as a technique adds great detail to scatter plots or maps. Varying the size and color of circles creates visually compelling charts that present large volumes of data at once.
In this example, the bubble chart can be used as a filter for the line chart to better understand how sales for a particular product have performed over time.
Histograms show how your data is distributed across distinct groups. By grouping your data into specific categories (also known as “bins”), then plotting the number of records in a category as a vertical bar, you can quickly see which bins the majority of your data falls in.
The histogram gives a breakdown of the distribution of rental prices throughout the United States.
Bullet charts show progress against a goal by comparing measures. At its core, a bullet graph is a variation of a bar chart. Designed to replace dashboard gauges, meters, and thermometers, a bullet chart shows more information while using less space.
In this dashboard, the view can see that the Central region has not yet hit quota. By using the bullet graph as a filter for the map, the viewer can see where there is more opportunity to sell.
Heat maps are a great way to compare data across two or more categories using color. Patterns guide viewers around the chart, quickly showing them where the intersection of categories is strongest and weakest.
To discover more tips for optimizing your dashboard layout, read The Do’s and Don’ts of Dashboards.
The heat map gives the viewer a quick summary of how different product categories are performing compared to each other per month.
A heat map, which would take 40 man hours before Tableau, now takes us less than a day. That’s a reduction of almost 80 percent.”
Practice Lead, Business Analytics, CRIF High Mark Information Services
Highlight tables take heat maps one step further. In addition to showing how data intersects by using color, highlight tables display number by cell, providing additional detail.
The highlight table draws the eye to see the biggest percent changes in population per state.
Treemaps relate different segments of your data to the whole. By nesting rectangles within others, treemaps show how individual data points fit in a hierarchy. As the name of the chart suggests, each rectangle is subdivided into smaller rectangles, or sub-branches, based on its proportion to the whole. They make efficient use of space to show percent total for each category.
The use of the treemap within each bar lets the viewer see which regions had the highest GDP each year.
Box-and-whisker plots, or boxplots, are a common way to show distributions of data. The name refers to the two parts of the diagram: the box, which contains the median of the data along with the 1st and 3rd quartiles (25% greater and less than the median), and the whiskers, which typically represents data within 1.5 times the interquartile range (the difference between the 1st and 3rd quartiles). The whiskers can also be used to also show the maximum and minimum points within the data.
In this example, the viewer can quickly see how the profit distribution has changed over time.
Candlestick charts are commonly used for financial analysis, showing metrics about a financial instrument over a period of time. This chart type shows the open, close, high, and low values of an instrument over time, in an easy to understand format.
Candlestick charts enable you to perform price and volatility analysis in one view. In this example, track Coke or Pepsi’s stock prices in one compact view.
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