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We cannot stress enough how important big data visualization really is. In fact, it’s the most straightforward way to get as much as possible from big data. Today, you have tons of data visualization tools at your disposal. In this article, we are going to analyze some of them and see how they can be used to push your agenda forward.
The entire idea behind data visualization is based on a simple truth: Most of us process information based on what we see. According to the Social Science Research Network[1] study, 65% of us are visual learners. That’s why we need a tool that helps us comprehend big data. And actually, big data visualization is the most effective and straightforward way to achieve this goal. A good big data visualization removes the noise from data and highlights useful information. It clarifies the picture. It makes you understand what you see, even if you’re not a data scientist. Furthermore, visualized data is easier to remember, which is another significant advantage.
Modern big data and data engineering services are teamed with big data visualization features. In many instances, you have a ready-made dashboard that allows you to understand what you see. Take a look at this example. It’s a Google Analytics dashboard. We frequently mention this tool because it’s extremely helpful for every website owner, and it’s really neatly made:
Image source: https://neilpatel.com/blog/how-to-get-actionable-data-from-google-analytics-in-10-minutes/
Everything is legible and organized. Mind you; Google uses multiple big data visualization techniques within one tool. On this one screen, we can see several line charts and a pie chart. Later in the text, we will analyze these big data visualization techniques.
At this point, we want to show you our own big data visualization dashboard.
As you can see, our dashboard, just like Google Analytics, utilizes various visualization tools. Our clients have access to:
To make everything more legible, our dashboard is divided into several sections. As a result, you have access to all relevant information about customer churn in just one picture. Our clients are always keen to use this dashboard and praise it for quick access to necessary data.
Take a look at the table in the lower right corner. Even here, we managed to make the presented information more transparent. Our customer churn dashboard indicates how much your customers have spent and the approximate churn risk index. When it exceeds 50%, the number turns red, which draws attention and tells you to focus on this risky customer.
That’s another vital issue. When you have a chart or a map that shows a lot of information, it’s best to hide them and make this map interactive. This way, the user can move the cursor to the requested field and highlight just the necessary element. This solution is standard in big data visualization tools, and many users find it extremely helpful.
As you can see, we are huge fans of big data visualization tools, and so are our clients. These tools can really make a difference! Unfortunately, raw big data is typically difficult to read, not to mention understand and draw a useful conclusion. No one likes to watch a wall of digits, right? That’s why in our everyday work, we try to visualize everything we can. Big data visualization comes in handy primarily in the following situations:
On many occasions, our clients use business intelligence solutions to spot trends and patterns in the data they process. Frequently, this knowledge is of significant importance. It helps make accurate business decisions and can influence the entire company. In such a situation, big data visualization tools help understand these patterns in data.
Our clients frequently write to us and ask us to help them find the source of problems. Everything was going well, and suddenly, crisis. Why? In many instances, the answer lies in big data. All you have to do is get it. It’s one of the crucial situations where big data visualization is indispensable.
Big data visualization tools can help you understand not only what happens within your organization but on the entire market as well. Consider the presidential election example. When an election is on, every TV network and every internet news portal show a map of the United States showing how did the given state vote:
Similar maps can be used to present almost any social, environmental, political, and industrial index or occurrence. This way, you can get a quick idea of the situation. You don’t have to spend hours analyzing data to draw conclusions. It’s a considerable simplification, and it saves time.
There are several principles you have to stick to if you want to create legible and useful big data visualization.
Big data visualization is not merely about putting excel entries and making a graph out of them. It has to combine transparency and exactness. Bear in mind that big data visualization tools are not interchangeable. Your first step ought to be to analyze the data you want to visualize and choose the most appropriate big data visualization tool.
For instance, if you want to:
In case you have doubts, simply use Google: “how to visualize X”.
Admittedly, it might be tempting to create a cool-looking 3D pie chart to impress your boss. But that’s not the point. Your main goal is to make everything transparent and understandable.
Don’t try to put too much information into one graph or chart. A useful graph should visualize as much as just two-three paragraphs of text, not more.
Usually, it’s best to limit yourself to just several colors. Moreover, they have to be easily distinguishable. Also, we recommend you avoid super-bright colors and stick with pastel tones.
Now, let’s analyze the most popular big data visualization tools. In many instances, the tools we show below are perfectly sufficient:
You can use bar charts to compare the values of different variables or present how one variable is dependent on the other. Bar charts are used to show how the churn risk index depends on customer spending, to analyze sales by category, to compare various marketing channels, etc.
Keep in mind that charts usually have two axes. These are the lines that run across the bottom (X-axis) and up the side (Y-axis). X-axis typically contains categories or numbers, while Y-axis almost in all cases includes numbers exclusively. A bar graph gives you a clear picture of which class is the largest/best/most profitable and which is the smallest/worst/least profitable.
Pie charts show different elements/aspects of one greater whole. Pie charts are perfect for comparing different customer segments (within one greater whole–one company) or various market shares (again, here, the larger whole is the market). Typically, all the elements in a pie chart sum up to 100%.
Line charts are used to analyze the behavior of one or more variables over time. They come in handy especially when it comes to identifying trends and patterns in data. For instance, line charts can be used to show how the sales level changed over the past year. Or to present the number of complaints that happened over the same period.
Do you remember our election example? It’s a perfect occasion to use a map to visualize data. Maps can be interactive or not. They show various variables and social/political occurrences depending on a country, state, or region. If you want to present data that applies to the whole country or continent and is dependent on a region/country–go for a map. Additionally, maps should have marked borders of states/countries.
Today, big data visualization is at hand. There are several open-source online applications that help you design legible graphs and charts. For instance, take a look at:
Naturally, there are also much more advanced big data visualization tools, like, for example, Microsoft PowerBI, but they are paid and frequently require at least basic coding knowledge.
If you are interested in big data consulting services or business intelligence – drop us a line! We are always happy to help you visualize and analyze big data your company processes. We have experienced business intelligence professionals and data visualization experts who are at your service!
[1] TJ McCue. Why Infographics Rule. Jan 8, 2013. URL: https://www.forbes.com/sites/tjmccue/2013/01/08/what-is-an-infographic-and-ways-to-make-it-go-viral/?sh=54d1c1ea7272. Accessed Dec 10, 2020.
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