Data scientists can use data visualizations to make their information more actionable. Illustrations, graphs, charts and spreadsheets can turn dull reports into something illuminating, where it’s easier to gather insight and actionable results.
Fortunately, modern technology — ranging from laptops to smartphones — has a variety of available applications that make visualizations easier than ever.
As a result, society is growing increasingly familiar with data visualization and its beneficial impact on data analysis and actionability.
Best Methods to Depict Various Data
The power of analysis is largely contingent on the presentation of data. The best forms of data visualization convey useful insights, while poor efforts can distract from actionable insight.
One good practice to implement is the use of round numbers. For example, instead of having 10,000,000 and 15,000,000 on a graph’s y-axis, use 10 and 15 instead, while clarifying beside those numbers that it’s in millions. It’s a practical strategy that makes the data quicker to understand, increasing its actionable potential.
Additionally, it’s always prudent to provide context for data, comparing metrics with set goals. Color-coded metrics are a great way to concisely showcase when values are over a goal (green), short of that goal (red) or somewhere in between (yellow).
It’s crucial to keep your purpose in mind as you select your visual. If you’re aiming to show the relationship between two or more variables, line charts make sense, since they track changes over time.
Bar charts are useful for comparing quantities of different categories, while bubble charts show joint variation for three points of data. It may take some playing around with various data visualization methods to determine the most relevant for your analysis.
Visualization and Understanding Actionable Data
Actionable data tends to be more prevalent when visualization techniques are incorporated. This is because data visualization can present an entire visual field at once, which can be an ultimate time-saver when dealing with unstructured data.
Properly visualized data makes picking out the crucial details considerably easier. Data visualization can help get answers fast by simplifying the process and providing context for separating the actionable data from the irrelevant data. Visualization unlocks more value from data.
Data visualization also aids in bringing teams together for collaborative problem-solving. Whereas data with visualization may help some team members, others may struggle or lack the time to sift through all that unnecessary data. Visualization helps bring everyone on the same page by clearly defining actionable data and relevant metrics.
Avoiding Data Visualization Mistakes
Artsy and beautiful visualizations can have a wow factor. Still, there is a risk of failing to present information effectively. Favoring color and striking design over efficient data presentation is a mistake that can derail a project.
As a result, it’s vital to remove noise from data visualization. Get rid of irrelevant features, like over-labeling, excessive background or grid lines. Keep data-ink ratio in mind, striving to avoid elements that reduce white space without the addition of analytic value.
Always be aware of potential data malpractice and misinforming data. There’s the potential for transparent misinformation, which can lead to the creation of non-zero baselines, misleading colors, incomplete graphs and other deviations from standard practices. Useful data visualization relies on simplicity, a relation to users’ needs and accurate contexts.
It’s also prudent to avoid using pie charts and graphs with unique effects like 3-D. These type of charts can impair the ability to analyze size and length with precision, leading to potentially harmful bias in data analysis.
Pie charts can prove useful in some instances, like when four data points are generally comparable, though there is often an ideal solution with less potential for visual bias.
The effective use of data visualization can really drive your information home. Use it to your best advantage to make your points pop off the page.
About the Author
Contributed by: Kayla Matthews, a technology writer and blogger covering big data topics for websites like Productivity Bytes, CloudTweaks, SandHill and VMblog.
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