Data Visualization Techniques and Tools for Various Data
You know what they say: a good data visualization technique answers all the essential questions, while a great one answers questions you didn't even know you had.
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Think about it: weather forecasts, medical equipment, vehicles, house utilities were all improved over the years, and data visualization techniques are what contributed to it.
In today's article, we'll dive deep into the visualization methods used by companies to create data visualization reports. If you pick the correct visualization type you can successfully deliver critical information, making the decision-making process more effective.
Different Data Visualization Techniques
It goes without saying, but the data visualization type isn’t always interchangeable. The type of data and your audience should influence your choice of data visualization technique. Depending on these two, you should choose the data visualization method. Typically, these methods include charts, infographics, graphs, or reports.
These visualization methods are used to track performance, calculate expenses or ROI, and measure other business-related metrics.
Goals and Audience
Your approach to data visualization mainly depends on your goals and audience. To present the information engagingly and make viewers stick around, you should go with an infographic.
Meanwhile, if your audience is a board of busy people, you should use a pie or a bar chart – this way, they'll be able to understand the information quickly. With that said, you should get to know your audience first, then decide on the data visualization technique.
At the same time, the goals you set dictate what type of elements you'll be adding to your KPIs report. Also, you should use a color scheme that matches the topic of your data report. For instance, if you're building a data report on carbon emission, it would be effective to use red shades: your reader will feel alarmed.
Furthermore, you should be consistent with the type of your selected color scheme. Utilize contrasting colors to present different or opposing elements: typically, positive values are in a green color and negative ones are in red.
Among all the data visualization techniques, using charts seems to be the most common type. There are different chart visualization sub-categories, each one of them having a specific use.
- Line charts - Using a line chart is one of the most visually-appealing ways to demonstrate change or impact over several periods. With a line chart, you can add multiple data elements and compare their performance during a selected time frame.
- Bar charts - Similarly to line charts, bar charts are used to compare different data elements and their performance over time.
- Number charts - Whenever specific data stats play a major role in KPIs, it would be best if you go with a number chart and percentages.
- Pie charts - To compare multiple metrics and assets, or illustrate proportional comparisons, pick a pie chart. Information, presented in a pie chart, was proven to be easier to read and understand.
- Gauge charts - To represent a single data point or its relations to other performance indicators, choose a gauge chart. For instance, it allows showing the expanse ration and how it correlates with turning around profit.
Visualization Techniques for Large Data
When it comes to representing large data you need to have a few critical aspects in mind. It would be best if you also create a decision tree analysis.
- Ensure your information source is reliable. Pick a relevant date range to incorporate it into the full display.
- Although it shouldn't be the focal point of your visual, let your audience know about the process you collect and store the data.
- Place the key data takeaways at the top of your data report to help the reader get to it first.
- Go that extra mile and make your display interactive: allow filtering some of the data components to see how they affect the results.
In general, you should display the data elements in the hierarchy, breakdown the derived results, and provide the method used to obtain the information. Keep in mind that appealing visualizations are as worth as its credibility.
Tools for Data Visualization
Designers use a few visualization tools to create a presentation for their company or build a road map. The most common visualization tools used are Photoshop or Adobe Illustrator but there are a number of free alternatives to Photoshop too. But, to create a map or a presentation report using one of these design tools, you still need aggregated data.
Luckily, there are many tools for data visualization out there, allowing anyone with little-to-no design knowledge to build a visual data chart.
Whatagraph here is one of the best examples: it’s an effective visualization tool that helps you create multi-source data reports using pre-made templates, so you don't have to do anything from scratch. Here's one of our Facebook data report examples:
The Whatagraph platform provides multiple integration options, including most of the major analytic tools. So, if you're already using some of the tools, building an aesthetically pleasing data report will be a piece of cake. You’ll be able to choose between line, bar, pie charts, and other types of visualizations.
In case the software you're using isn't available on our platform, you can upload a CSV or an Excel file. Best of it, you can use the white-label those reports function to make a custom data report with brand colors and logos, which shows you put extra care into your work.
Published on Apr 04 2020
WRITTEN BYGintaras Baltusevičius
Gintaras is an experienced marketing professional who is always eager to explore the most up-to-date issues in data marketing. Having worked as an SEO manager at several companies, he's a valuable addition to the Whatagraph writers' pool.
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