Data visualization is one of the must-haves of the big data and business intelligence world. This is a crucial element of data analytics because it provides an intelligible way to see and understand trends and patterns in data. And, as its name indicates, it is a graphical representation of information and data. In this article, we will focus on such issues as: What is data visualization? Why is data visualization important? How to create data visualization? How is data visualization used? Let’s begin!
Before we move on, we should address the first significant question. What is data visualization? It is a set of tools and techniques used to communicate data or information by presenting it as visual objects (e.g., points, lines or bars) contained in graphics. Every diagram is a data visualization tool. So is every infographic, chart, dashboard and, in many cases, map as well. There is plenty of data visualization almost everywhere you go and what you watch. In a shop, on an airport or train station, on a news report, in a corporate periodical or operational report, in a prospect. Everywhere. Why is it so popular and essential in our business and day-to-day scenery?
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Why is data visualization important?
The answer lies in the way we are constructed. Most people are visualizers, although we lack precise information about how many exactly. This means that it is easier for most of us to read and interpret graphic presentation than just ordinary text. It helps in the decision-making process and allows us to memorize what we see more efficiently. If we can see something, we internalize it quickly. This is the way our brain works. Have you ever stared at a massive spreadsheet of data and couldn’t see a trend? Everything has changed when you visualized it, hasn’t it?
A good visualization removes the noise from data and highlights the useful information. It clarifies the picture. It makes you understand what you see, even if you’re not a data scientist. Data visualization brings big data to ordinary people. It’s a necessity, while the current world is simply drowning with data. In one of our previous texts, we wrote that over 2.5 quintillion bytes of data are created every single day. By 2020, it’s estimated that 1.7MB of data will be created every second for every person on earth. That’s why data visualization is so essential. Without it, it would be almost impossible to harness that masses of data that are being produced every second.
Data visualization is a stage when the data scientists and the visuals and graphics work together, and there’s a whiff of art in combining great analysis with great graphic representation. You see, data visualization is not merely about putting excel entries and make a graph out of them. It has to combine transparency and exactness. The graphic has to decide each time which way of presentation will be the most accurate and the data scientist have to provide data that will be a source for future graph or chart.
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What are data visualization tools?
There are plenty of different applications and software to visualize data. The simplest and simultaneously the first is a pencil and a piece of paper. And in fact, these two tools were used for one of the very first data visualizations. In 1869, Charles Joseph Minard created a diagram or rather a chart showing the number of men in Napoleon’s 1812 Russian campaign army. The diagram showed their movements, as well as the temperature they encountered on the return path.
Charles Minard (1781-1870)
Today, a piece of paper and a pencil still can be used for data visualization, but we have much more sophisticated and advanced tools. There’s a whole wide selection of visualization methods to present data. Among them, most common are charts, tables, graphs, maps and heatmaps, infographics, dashboards, cartograms, histograms, timelines, pictograms, and several others. These forms are often divided into sub-forms, for instance, consider charts. You can create an area chart, bar chart, Gantt chart, or pie chart.
Available tools and software
Knowing that, let’s switch to available tools and software. Many of you will think of MS Excel first, and it is a correct shot. Indeed it allows us to create charts and graphs based on data entered into its sheet. But the list goes on. You can start with the most straightforward online free tools like Canva, but for a more advanced user, such tools will not be sufficient. Other proposals are Microstrategy, D3.js, HighCharts, Echarts, Leaflet, Vega, Deck.gl, PowerBI, Tableau, and FineReport. All these tools are far more sophisticated and allow creating complex charts and infographics. However, at a price. All of them are paid and usually require at least basic coding knowledge.
How to create data visualization?
When it comes to data visualization, simplicity is the key. Of course, it might be tempting to create a cool-looking 3D exploding pie chart to impress your boss, but there is no point in doing that. The whole idea of data visualization is to present it accurately and legibly. Your graphs and charts ought to have a neat, clear formatting and easily distinguishable colors.
Now, we are going to examine some of the basic rules that apply to data visualization. Don’t try to put too much information into just one graph. A useful graph or chart should show as much as several paragraphs of words, not more. If you want to show numbers and values that are independent of each other–go for a bar graph. If you want to depict one whole entity that is divided into different parts, a pie chart is your best bet. Sometimes you need to show how numbers change in time. A line graph is exactly for such purposes. And last but not least, at times, you have to show how one factor affects the other. The Cartesian graphs are a perfect solution for this issue.
Graphs have two axes. These are the lines that run across the bottom and up the side. The line along the bottom is called the X-axis, and the line up the side is called the Y-axis. X-axis typically contains categories or numbers, while Y-axis almost in all cases includes numbers. A bar graph gives you a clear picture of which category is the largest and which is the smallest. Histograms show combined continuous data. In histograms, both X and Y-axis comprise a range of numbers. And then, you also have pictograms. It is a type of graphs primarily used in infographics. Pictograms use icons to represent a particular number of items.
How is data visualization used?
As you might expect, we can find data visualization examples almost everywhere. There are five primary disciplines where data visualization finds application, but, of course, the list is much longer.
Almost every marketing analytics tool uses data visualization, no matter if we talk about Google Ads, Facebook Ads or other, commercial solutions. Marketers and their clients adore statistics, charts, and graphs. If you cooperate with a marketing agency of any kind, it is likely that you receive reports that consist of many graphs and diagrams.
Every stock exchange uses data visualization to show the current stock valuations. Candlestick visualization charts are the most common type of data visualization in finances. They show how the price has changed over time, and the finance professionals can use it to spot trends and predict future bull or bear markets. Data visualization can communicate the change in price more quickly than a grid of data points.
Every single time, before elections, there are lots of geographic maps on the Internet and news shows with support bars for each candidate or party. After the elections, research companies present districts or states, and how did each one of them vote.
All of the shipping companies use visualization software to understand and plan global shipping routes. World maps with marked routes are often used to present possible connections between countries and cities (many airlines do that) or to track a given package or a vehicle (courier services companies and fleet management companies use such tools).
Healthcare companies and institutions often use choropleth visualizations to visualize valid health data. For example, how an epidemic grows and develops in time.
The benefits of data visualization
You already know that without data visualization, it would be almost impossible to harness that masses of data that are being produced every second. Why is it beneficial? And why is data visualization the tool we use? Somehow, brains most of the people, struggle with comparing large datasets written in plain texts. That doesn’t refer to people called synesthetes. In one common form of synesthesia, known as grapheme-color synesthesia or color-graphemic synesthesia, letters or numbers are perceived as inherently colored. Synesthetes perceive characters and digits with more senses than just sight. The rest of us definitely prefer when numbers are turned into a graphic representation. This allows us to understand what we are looking at, spot correlations, and trends much quicker and more accurately. So improved insight is our first major benefit.
Another valid benefit is a faster decision-making process. Companies that can gather and quickly act on their data are more competitive because they can make informed decisions sooner than the competition. Speed is the key to success, and data visualization is the quickest way to analyze vast quantities of data. So basically, data visualization speeds up the pace the company grows. Partly, that’s the reason why every modern business intelligence and marketing analysis platform automatically presents all the statistics in charts and graphs.
Does your company use data visualization?
What about you? Does your company use data visualization? We bet it does! Possibly, you’re thinking now of various ways to make it even more efficient and profitable to your business? Thankfully, you’re in the right place! Give us a call and let’s chat about your ideas. And not just regarding data visualization. Addepto is a business intelligence consulting company. We will gladly help you with everything your business needs that’s related to artificial intelligence and big data.
 Irfan Ahmad. How Much Data Is Generated Every Minute?, Jun 15, 2018. URL: https://www.socialmediatoday.com/news/how-much-data-is-generated-every-minute-infographic-1/525692/. Accessed Dec 17, 2019.
 Wikipedia. Synesthesia. URL: https://en.wikipedia.org/wiki/Synesthesia. Accessed Dec 17, 2019.