What is data visualization? Commentary with examples of success and failure

Modern society is overflowing with data, and some of the data is published in its original state and cannot be understood at a glance.

It’s not easy to get a clear point just by looking at huge numbers and statistics. To effectively convey the meaning of your data, you need to present it in a logical and understandable way.

The human brain can process graphical information more quickly than written information . That’s why data visualization with charts, graphs, and design elements makes trends and statistics easier to understand. On the other hand, not all data should be visualized in the same way ( see this blog post to see what I mean). In this article, I will introduce a reliable method for effectively visualizing data and many practical examples that can be used as hints.

data visualization

Table of Contents

What is data visualization?

Data visualization is the process of shaping and visualizing large amounts of complex data in an easy-to-grasp, convincing format .

Specifically, it refers to expressing data in ways such as charts and maps so that the viewer can deeply understand the meaning of the data. For example, rather than looking at sales data as a table, you can see at a glance the increase or decrease in sales by looking at a line graph.

In today’s world, where a huge amount of data is overflowing, simply leaving out information not only wastes the viewer’s time, but it may also prevent the person who wants to see it from seeing it. Data visualization allows you to instantly understand what the data means.

An example of data visualization is a “dashboard” that displays various data on a single screen in an easy-to-understand manner. The dashboard is explained in detail in the column below.

What are the benefits of data visualization?

It goes without saying that text-only data is dull, but it also makes it difficult to convey your intentions. Data presented in a visual format, on the other hand, makes sense quickly and easily. Data visualization can reveal patterns, trends, and correlations you might not find otherwise.

“Static data visualization” and “Interactive data visualization”

Data visualizations fall into two broad categories: static and interactive .

Once upon a time, static data visualizations such as charts and maps were used for centuries. Interactive data visualization with easy-to-understand motion is relatively new. With a PC or mobile device, you can use movement to delve into the murkiness of charts and graphs and interactively change what data you see and how you process it.

Time series data visualization

In addition to “static data visualization” and “interactive data visualization”, there is also the term ” time series visualization “.

A time series visualization, as the name suggests, is a visualization of the results of tracking data or performance over time. This is mainly important when visualizing types of data that change over time or time.

How to visualize data in chronological order?

There are many ways to visualize data over time. We’ll go into more detail in the sections that follow, but as a quick note, the time series visualization uses a graph like the one below.

  • line graph
  • bar graph
  • Area chart
  • bullet graph

 

Data visualization best practices

As a best practice, be sure to keep the following points in mind when deciding on your data visualization approach:

  1. Choose the best visual for your data and its purpose
  2. Make sure your data is easy to understand and presentable
  3. Provide necessary background information for and around visuals
  4. Keep visuals as simple and straightforward as possible
  5. Reliably communicate important information through visual appeal

With these best practices in mind, let’s take a look at how you can actually display your data in an effective way.

Well, there are various types of data visualization as follows .

  • chart
  • table
  • graph
  • map
  • Infographic
  • Dashboard

These are broad categories, each of which can be subdivided into more detailed forms. From among the wide variety of formats, this time I would like to introduce 10 types that are especially recommended for beginners.

10 Recommended Data Visualization Formats

  • line graph
  • bar graph
  • scatter drawing
  • graph map
  • indicator
  • pivot table
  • bullet graph
  • boxplot
  • matrix

 

1. Line graph

line graphLine charts are effective for showing trends and fluctuations in continuous data over time. Can be represented using single or multiple data points.

2. Bar graph

bar graph

Bar charts are good for comparing multiple groups or categories while displaying distinct values.

3. Scatter chart

Scatter plot

A scatterplot shows two distinct components on the horizontal and vertical axes, with observations as points on the chart.

4. Area chart

Area chart

Area charts are similar to line charts, except that the spaces between the lines are filled in to represent quantitative changes. Both line and area charts represent changes in values.

5. Map

mapMaps are good for displaying geographical data, or for showing distributions and proportions within a particular region.

6. Indicator

indicator

Indicators display data using visuals, such as gauges or clocks, to clearly show where things are going over time.

7. Pivot table

pivot table

PivotTables are great for presenting large amounts of information together while highlighting the most important data.

8. Bullet graph

bullet graph

Bullet charts are used like bar charts. The big difference from bar charts is that they can contain detailed information and data without being visually intrusive.

9. Boxplot

Boxplots show the distribution of the data. One box is created for each attribute you are viewing.

10. Matrix

 

A matrix shows the relationships between hundreds or thousands of data points, elements, etc. and lets you see their interactions all in one place.

So how do we actually use them? Here are some real-world examples of interactive and static data visualization.

Data visualization success stories

From here, let’s introduce a total of 10 cases, roughly divided into two sections: “Interactive Data Visualization” and “Static Data Visualization”.

An example of interactive data visualization

 

1. Languages ​​around the world

Data visualization by DensityDesign allows non-linguists to immediately see languages ​​spoken around the world. The number of target languages ​​is 2,678.languages ​​around the world

In this example, you can explore common language families, see which languages ​​are most spoken and where each language is spoken. This is visual storytelling . We will take up deep themes and unravel them in an easy-to-understand manner.

2. All NFL History

This example visualizes the results of calculating the “Elo Rating” for all games since the beginning of the National Football League (NFL). An Elo rating is a simple metric that measures strength based on match-by-match results.Full NFL HistoryThe total number of ratings is over 30,000. Compare each team’s Elo rating and learn how they’ve fared over decades of history.

3. Thanksgiving in the United States on Google Flights

This image, courtesy of Google Trends, captures flight activity to and from the United States the day before Thanksgiving.Thanksgiving in the United States on Google Flights

From the start of the day, you’ll be shown a video-like view of your flight across the country. The figures shown are only hours, but you can see the most popular time slots for international flights, domestic flights, and flights to and from domestic hub airports.

4. The real cause of global warming

Have you ever heard advice like “Don’t just show the data and try to explain it”? Data visualization by Bloomberg Businessweek follows exactly that best practice and tells the story in an interactive way from start to finish. This example disproves the theory that global warming can be explained by natural factors.

First displayed is the observed temperature rise data from 1880 to the present.The real cause of global warming

As you scroll down, you’ll see new storytelling information added against the temperature data to see exactly how much each factor contributes to global warming. The conclusion that the creator wants to convey is very clearly indicated.

5. Composition of the conflict in the Syrian civil war

Understanding the relationships between many groups is not easy. Moreover, if there are 11 groups, we can see a phenomenon in which many groups that are normally in opposition become allies, and vice versa. But Slate has created tables with friendly red, yellow, and green colored emojis to bring complex data together in a simple, easy-to-understand interactive format.Composition of the conflict in the Syrian civil war

Click on the emoji to see a short description of the relationship between the two groups.Composition of the conflict in the Syrian Civil War_2

6. Sports Team Values

Here are some examples of adding data to tell a deeper story.sports team valueThis interactive visualization shows each team’s age and tournament wins, giving you a comprehensive view of the history and success of each team in the franchise.

7. U.S. Wind Map

This is a display of wind speed and direction in the United States as of 2015.U.S. wind direction and speed mapThe speed of the line movement expresses the wind speed, and the direction in which the lines move expresses the direction of the wind. This is a good example of intuitive design. If you click on the map, the numerical value of the place will be displayed, but you can understand the general trend at a glance without looking at the specific numerical value. Furthermore, it is easier to understand by restricting it to two types of factors, wind speed and wind direction.

Static data visualization example

8. The political spectrum of the press

In this example, the use of scatterplots effectively visualizes data on where each news outlet sits on the spectrum.The political spectrum of the press

On the spectrum, the spacing between the points of each press also has significance. If this was just a list of each news agency, it would not have been easy to understand the position of each company.

9. Daily life of artists

This website is based on Mason Currey’s book “Daily Rituals: How Artists Work” and introduces the daily schedules of famous writers and musicians by time of day and activity category. I’m here.Daily life of artists

This is an example that is not only very interesting as data (you can see the schedule by activity category), but it can also be used effectively as editorial content for your brand.

10. News highlights of the year

Echelon Insights visualized which news stories were the most talked about on Twitter in 2014. 184.5 million tweets looks like an amazing piece of art.News highlights of the yearSo far, we have seen some examples of effective data visualization. I believe that these will be very helpful in considering what approach to take.

On the other hand, it is also important to know and avoid the less effective methods of data visualization. Here are some examples of low impact.

Data visualization failure example

There are many reasons why data visualization is not effective. For example, see the 2013 MLS (Major League Soccer) salary data visualization example . Too much information makes it hard to read.Data visualization failure exampleIn addition, the display of each element is so small that the data cannot be read without considerable magnification. Most of the boxes representing each player’s data are horizontal, but some are vertical, which can also cause confusion.

Having too many disparate elements in one visual can be confusing and difficult for your audience to understand. The graph below is an example.Data visualization failure example_2You also need to make sure your visuals aren’t overly complex. For example, in the graph below, many elements are represented by 3D bars, but they didn’t seem to need to be 3D. The information is simply difficult to understand and difficult to see.Data visualization failure example_3

Finally, I will introduce some useful tools for data visualization.

Helpful tools for data visualization

There are many data visualization resources available today , but here are some tools to help you get started with data visualization. We encourage you to try a few to find the best tool for your needs (and your data).

why you need a tool

It is necessary to understand what the data visualized means at a glance. If you want to create a design that is easy for humans to see and understand instantly, you first need to learn the know-how, and programming and design skills are also required. Data visualization tools, on the other hand, can quickly create human-friendly designs.

Visualization is easily possible with data visualization tools, but it is important to clarify the purpose, such as who, what data, for what purpose, and how you want it to be understood .

1. HubSpot

HubSpot has many features for data visualization , especially within reportsYou can create graphs and charts in a variety of ways , depending on your preferencesThere is also the ability to add dashboards and reports that simplify the process of data visualizationYou can manage and customize your data and dashboards in HubSpot to meet your unique needs

2. Tableau Desktop

Tableau Desktop data visualization software enables live analysis with interactive dashboards to easily spot trends, patterns and insights. Easily create rich visuals such as maps, indicators, and post-creation with easy analytics to derive actionable information based on calculations, baselines, and forecasts.

3. Chartio

Chartio’s data visualization tools offer 15 different charts with multiple variations to choose from, and even more options if you know how to use a data programming language. With Chartio, you can bring together all your data from places like Amazon Redshift , browse your data in Visual SQL solutions , customize and manage charts and visuals (web pages, Slack, PDF reports for email, etc.) ) can be easily shared.

4. Databox

Databox is a tool that allows you to upload data in various ways to efficiently create visuals and derive insights. With over 70 integrations available, you can create visuals quickly and easily with pre-built dashboards and reports. Custom metrics can also be created. Databox allows you to connect to Google Sheets, SQL databases or push via API to view and share data.

5. Google Chart Tools

Google Chart Tools lets you visualize live data on your website (and mobile) with dozens of interactive and customizable charts and data tools. The most common way to use Google Charts is with a simple JavaScript embedded in your webpage . Also, the DataTable class makes it easy to switch between chart types.

Use data visualization to grow your business

Data visualization makes it easier and more effective to extract insights, discuss them, and put them into action than looking at raw data .

We hope these great ideas will help you (avoid the less effective ones) and experiment with different data visualization tools to find the best fit for your company’s needs and goals.

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