It’s no secret that data can be very powerful — when you can actually understand what it’s telling you, that is.

It’s not easy to get clear takeaways by looking at a slew of numbers and stats. You need to have the data presented in a logical, easy-to-understand way so you can apply your discovers in an effective way. That’s where data visualization comes in.

Download Now: An Introduction to Data Visualization for Marketers [Free Guide]

In this article, we’ll offer you relevant ways to ensure your data visualization is effective, and provide examples for brainchild along the way.

What is data visualization?

Data visualization allows you to organize data in a way that’s both urging and easy to digest.

It’s about representing data in a visual framework, such as a graph or a planned, to help anyone viewing it better understand the significance of that data.

How does data visualization act?

Whereas data shared via textbook can be confusing( not to mention bland ), data referred to in a visual format can help people extract definition from that report more quickly and easily.

Data visualization can be used to expose decorations, tends, and correlations that may otherwise run undetected, too.

Static vs. Interactive Data Visualization

Data visualization is likely to be static or interactive. For centuries, people have been using static data visualization like charts and maps.

Interactive data visualization is a little bit newer: It causes parties drill down into the dirty details of these charts and graphs exercising their computers and mobile devices, and then interactively modify which data they construe and how it’s processed.

Day Sequences Visualization

In addition to static and interactive data visualization, you may also hear the call era serials visualization. Time series visualization is what it sounds like — visuals that line data, or operation, over a period of time.

This is important because a major reason why people want to focus on data visualization is to show changes in variables over time.

Go Serials Data Visualization Examples

There are many ways to use time-series data visualization — you’ll learn more about these below, but here’s a immediate register to give you a better understanding of which visuals are considered time series visuals.

Line chart

Bar chart

Area chart

Bullet graph

Data Visualization Best Rule

While determining how you’ll visualize your data, one of the first things you’ll want to do is keep the following best rehearses in mind.

Choose the best visual for your data and its purpose.

Ensure your data is easily understandable and viewable.

Offer required context for your audience in and around your visual.

Keep your visual as simple and straightforward as possible.

Educate your public with your visuals.

Featured Guide: An Introduced by Data Visualization

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Learn how to apply data visualization best rehearses in your sell with this free guide.

1. Line Chart

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Use a line chart to expose your data over the course of time to view trends and intervals. You can do this with a single, or multiple, data point( s ).

2. Bar Chart

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Use a bar chart to compare radicals or categories while also exposing clear values.

Wondering how you could use this? Say you’ve been using Casted for your content marketing and need to report on which medium is performing best. You can gather presentation of data from the dashboard to envisage the data for key stakeholders.

3. Scatter Chart

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Use a sow chart to show the values of two different variables as phases on a chart.

4. Area Chart

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Use an range graph in a similar way to how you’d use a line chart.

The difference is that the area below the line is filled with color and/ or composition with an area chart. Both locality and string charts expose the evolution of a value.

5. Map

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Use a map to expose data the hell is geographically set and to show the deployment and balance of data in specific areas.

6. Indicator data visualization indicatorImage Source

Use an indicator if you want to expose your data with visuals like a gauge or ticker which is clear that there demonstrate which attitude things are moving over time.

7. Pivot Table

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Use a fulcrum table to summarize a large amount of information while exclusively foreground the most critical data for audience members.

8. Bullet Graph

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Use a missile diagram or plot in a similar way to how you’d use a bar chart. The main difference is that a missile diagram allows you to include more detailed information and data in a way that doesn’t sound or feel cluttered.

9. Box Plot

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Use a carton story to view the rationing of your data — you’ll have one casket planned for each property you’re displaying.

10. Matrix

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Use a matrix to display the relationships between hundreds or thousands of data points, variables, and more to understand their interactions all in one location.

Ready to feel spurred? Let’s take a look at some huge a few examples of interactive and static data visualization.

Examples of Data Visualization

Below are 16 examples of data visualization, split into two major slice: interactive and static data visualization.

Pattern of Interactive Data Visualization 1. Why Buses Bunch

Here’s an example of a complex information and data boiled down in a way that seeks and feels like a game. In this visualization, Setosa is showing how “bus bunching” happens, i.e. when a bus comes retarded and later stimulates multiple buses to arrive at a single stop at the same time.

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Telling this story in multitudes alone would be pretty difficult — instead, they turn it into an interactive recreation that meets the data easier to understand. While the buses rotate along a direction, you can click and hold a button to delay a bus. Then, all you have to do is watch to see how even a short adjournment causes the buses to bunch together.

2. Languages in the World

This interactive by DensityDesign introduces the non-linguist to the many world expressions. All 2,678 of them.

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This piece allows you to explore common conversation kinfolks, discover which expressions are most frequently spoken, and opinion where words are spoken around the world.

This is visual storytelling: taking an in-depth subject and smashing it down in an easy-to-understand way.

3. Percent of U.S. Population by Age Group

This is an example of how to present a single data set in a compelling practice. Pew Research made an enlivened GIF composite to show alterations in population demographics over day. It’s an effective way to tell a larger story in a nifty package.

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Plus, this type of micro-content is easy to share on social or embed in blogs, extending the content’s reach.

If you want to make a GIF of your own exerting Photoshop, here’s a step-by-step tutorial.

4. The Complete History of the NFL

In this interactive visualization below, an “Elo rating” — a simple measure of strength based on game-by-game solutions — has been calculated for every game in the history of the National Football League( NFL ).

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That’s over 30,000 ratings in total. Onlookers can equate each team’s Elo to see how each squad acted across decades of play.

5. U.S. Thanksgiving on Google Flights

This visual is powered by Google Trends. It tracked flights as they flew to, from, and across the United Government on the working day before Thanksgiving.

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The visualization starts at the very beginning of the day and plays like a movie as term goes on, picturing flights moving around the country.

Without showing any figures besides the time, spectators can see which times were most popular for international flights, domestic flights, and flights to/ from different centres around the country.

6. What’s Really Warming the World ?

Ever heard a edition of the advice, “Don’t simply demonstrate the data tell a story with it”? That’s exactly what this visualization from Bloomberg Business does — and it’s the interactive part that draws the tale move along from beginning to end. The visual contradicts philosophies that claim that global warming can be explained by natural causes.

The first thing you’ll see is the celebrated temperature as it’s risen from 1880 to present day.

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As you scroll down, the visualization takes you through exactly how much different factors contribute to global warming in comparison to what’s been observed, adding a richer coating of storytelling. The conclusion the authors crave viewers to draw is realise very clear.

7. Most Valuable Sports Franchises

Here’s an example of telling a deeper floor by adding data.

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The interactive visual lets users verify the number of years each team has played, as well as the number of championships won. This offers a more comprehensive view of each team’s history and success as a franchise.

8. U.S. Wind Map

Here’s a visual same that shows the wind fasts and future directions in the U.S. in real-time back in 2015.

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It’s a great example of instinctive intend: Speed is represented by directions moving slowly or abruptly, and direction is represented by which way the lines are moving. It’s immediately clear what the overall trend are without any is essential for figures unless you click into the map itself. Plus, capping the number of variables at two impels it even easier to follow.

Pattern of Static Data Visualization 9) Where News Audiences Fit on the Political Spectrum

This visual depicts data organised in a rationing planned — this is an effective visual option because it allows viewers to see where each media outlet is available on a spectrum.

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On a range, the length between each media outlet is significant. If these channels were just listed one after the other in a table, witness wouldn’t be able to see where each one stood in context.

10. The Daily Routines of Famous Creative People

Using information from the book Daily Rituals by Mason Currey, the site showcases the daily schedules of notorious creatives broken down by meter and activity.

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Not exclusively is this an example of locking data( you can explore the schedules by individual pleasure ), it’s also an effective editorial piece for a brand.

11. The Year in News

Echelon Insights generated this visual to image the most talked-about news tales of 2014 on Twitter.

What do 184.5 million tweets definitely sounds like? Cool spin art!

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12. The Depth of the Problem

When you want to illustrate scale, static data visualization can be a great way to represent your point. The infographic below from The Washington Post is incredibly long … and that’s on purpose.

In this case, they’re showing how crazy far a deep-sea signal from an airplane can be detected by comparing that penetration to tall constructs, the maximum depth of known mammals, the depth of the Titanic wreck, and so on.

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It’s a great use of simple visuals and emblazon gradients. Finally, contributing data to a news story( in such cases, the missing Malaysian airliner) equips necessary context.

13. Funding the Final Frontier

While the infographic above is pretty simple, there are ways to create well-designed infographics that deliver a large amount of data. The mystery? A simple and clean format that shapes it easy for readers to understand the data.

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This infographic, created by GOOD Magazine and Column Five, breaks down NASA’s five-year budget to show how and where the money will be deplete. Plus, it has an on-theme design — an all-around win.

14. Caritas Kontaktladen Annual Report

Not all data visualizations need to be animated. When real-world data is envisaged with real-life examples, the results can be stunning. The decorator of this visual take a unique approaching to the data contained in the annual report.

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The organization provides support to drug addicts in Austria, so Luttenberger focused on communicating the mission through real-life visuals. For example, this patronize cart visualization represents how much of life’s necessities a aid recipient can open each day.

15. Austria Solar Annual Report

While there are many ways to visualize data, exerting the information subject to actually procreate the data visualization can be quite profound.

This annual report from Austria Solar exploits actual solar power to generate the company’s data to life through solar-activated inks on the page.

The good examples of data visualization above are great to reference while you develop your approach. Nonetheless, it’s also important we consider the less effective ways to go about data visualization so you know what to avoid — so, let’s cover some bad lessons next.

Poor Data Visualization Examples

There are many actions in which data visualization can go wrong.

For instance, look at this data visualization example of MLS stipends in 2013. The sheer extent of information on this chart does it difficult to read.

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Additionally, the scale of the variables requires audience members to zoom in greatly to read the data. Some of the boxes that are being used to depict data appear to be vertical while most are horizontal — this also reaches the information confusing to read.

When you include a number of completely different variables within a single visual, it also becomes complicated for public members to understand — the following chart is an example of this.

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Something else you’ll want to do is make sure you’re not reaching your visual more complicated than it needs to be. For example, this chart has a number of variables that are depicted by 3D bars. This graph doesn’t need to be 3D — in fact, it simply obliges the information more difficult to understand and view.

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Lastly, let’s revaluation some data visualization tools to help make this process simpler.

Data Visualization Tools

There are a number of data visualization reserves available today but the following list is here to help get you started. Don’t be afraid to test out a few cases alternatives to determine which alternative suits your needs( and data) best.

1. HubSpot

HubSpot offers several options for data visualization, precisely within Reports. You can create diagrams and graphs in many ways depending on your preference.

There’s likewise a Dashboard and Reporting add-on that they are able serenity the process of data visualization. Lastly, HubSpot allows you to manage your data and dashboards, as well as customize them, in a manner that suits your specific needs.

2. Tableau Desktop

Tableau Desktop’s data visualization application offers live analytics with interactive dashboards so you’re able to easily spot tends, blueprints, and insights.

There are easy-to-make maps, indicators, and many more visuals, as well as straightforward analytics which allow you to derive actionable datum from figurings, invoke pipelines, and prognosis as a result of your visuals.

3. Chartio

Chartio’s data visualization tools offer users 15 types of shows to choose from with variou discrepancies, and even more alternatives if you know how to use data programming languages.

With Chartio, you can bring all your data together from locales like Amazon Redshift, browsing your data with the Visual SQL solution, create and manage customized charts and visuals, and readily share them( via web page, Slack, PDF reports for email, etc .).

4. Databox

Databox accommodates a number of ways to upload your data and efficiently create visuals to derive conclusions.

There are over 70 integrations that can help you quickly and readily form visuals with pre-built dashboards and reports. You are also welcome to cause patronage metrics. Databox then allows you to connect to Google Expanse or an SQL database, or you can push it via API to consider and share your data.

5. Google Chart Tools

Google Chart Tools allow you to visualize live data relating to your website( and mobile) with the help of a number of interactive, customizable charts and data tools. The most common way to use Google Charts is with simple JavaScript that you embed in your web page. And by using the DataTable class, you can easily switch between show types.

Originate Better With Data Visualization

With data visualization, you’ll be able to identify, discuss, and act on revelations in an easier and more effective way.

So, look to the patterns above for brainchild( and as a cite for what to avoid, very !) and experiment with the many tools available to determine what works best for your needs and goals.

Editor’s Note: This post was originally published in March 2015 and has been modernized for comprehensiveness.

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