It’s the year 2022. Currently reaching for information is becoming less and less of a problem. It’s the opposite way. The amount of data flowing from different sources: informatic systems, e-mails, documents, databases or social media, can be really suffocating and create an informational chaos. This war doesn’t have to look like a Don Kichot fight against windmills. Thanks to the right tools we are able to conquer any amount of data and use it to our advantage, showing it in a clear and distinctive way.
Thanks to the power of data visualization we can make smarter business decisions, based on up-to-date information. In our article we will focus on basics and rules of data visualization, its categories and influence on the analytics. We’ll also answer the questions: what is data visualization and how data visualization can help a company? Enjoy!
What is business data visualization?
Business data visualization in a nutshell means showing the information in the most attractive way possible, at the same time keeping high readability and transparency of data shown. It’s most commonly used by various diagrams, pictograms, maps, pictures or charts. Let’s take a look at a basic example of data visualization. On the left side we have a regular sheet of numbers. On the right side there is a clear, well described chart. Which one of these ways of displaying information tells more?
Most people without a hesitation will pick graphical representation of data in front of just numbers. It’s how we are programmed. The study led by 3M concern shown, that our brain processes visual information 60 thousand times faster than a text one.
How does data visualization work?
Too much information is now valuable unless we generate conclusions out of it. Only after that can we start making decisions or better understand the situation. Naturally there are situations where data should be displayed tabular, without any changes. However in most cases, like creating reports or showing results, our goal is to present the key notes and to underline them as much as possible. And data visualization and reporting fits well together.
The goal will not be the same every time though. Determining it should be the first step. We have to ask ourselves the question: What information do we want to show? Which ones are the most crucial? How do we want to express them? What result would we like to achieve?
Based on our decision, we start carefully picking correct data visualization techniques. It’s worth remembering that we need to use a technique that will allow for best readability. Not every data type will suit every technique. Effective data visualization is aimed to show data in a way so everybody will understand it and remember it. That’s why it’s recommended to choose correct cockpits, colors and ways of transferring information. Maybe it’s worth it to describe charts even more?
Let’s remember to not go over the line, when focusing on attractiveness in the statistical data visualization. We can’t cause the amount of colors, dynamics or creativeness to distract our recipients from the content.
Why is it worth it to visualize business data?
Many people would raise the question: “Is it worth it to visualize business data, when everybody can read the numbers?”. The answer is – Yes, in most of the cases it’s worth it. The way of saying things can be more important than just things itself. A misleading display of information can result in misunderstandings or impression of understanding. And it’s something we truly want to avoid.
Data is a fundamental part of the decision-making in a company. It’s not only used to optimize processes, but also for planning, creating and actualization of strategies and even forecasting development trends. Data lets you see the relations and values imperceptible earlier. Incorrect use of information may heavily cost us, when for a relatively cheap price and work effort we can create multidimensional reports with attractive data presentation.
Data visualization in business allows for effective usage of gathered information, which helps us react faster during dangerous situations. With it, every employee will be able to inform their supervisor about the problem, letting them make decisions at the right moment.
The influence of data visualization on analytics
Data analytics in the era of computer revolution is known for the ridiculous amount of information. The right data selection, especially with the usage of cutting-edge informatic tools has a crucial impact on making work comfortable and easy. Even basic ways of data visualization like diagrams, charts or pictograms allows us to catch anomalies and understand wider perspectives. Data analytics are using these tools to find trends, relations, effectiveness and to research new strategies. It becomes the most handy while doing multidimensional analysis, which without the right visualization is impossible to examine completely.
Categories of data visualization
The ways of data visualization can be separated into categories. One of the most known classification was created by Ben Shmeiderman in the article titled “The eyes have it: A task by data type taxonomy for information visualizations” from 1996. The author divides ways of data visualization to: time visualization, multidimensional visualization, hierarchical visualization, network visualization, geospatial visualization, one-dimensional visualization and three-dimensional visualization.
Time visualization – data visualization that fulfills two requirements: is linear and one dimensional. As the name suggests it is used to observe changes in time.
Multidimensional visualization – they contain at least two variables. The higher level of complexity allows for more creative charts. They often catch attention with the way of presenting the data. They allow for segmenting higher amounts of data at the same time, which can be a big asset for companies.
Hierarchical visualization – arrange data into groups and subgroups. They are used to show information in relation to the whole.
Network visualization – show relations between data by presenting networks of connections. Because of its nature it is one of the least used types of data visualization, but can be used for displaying ex. contact points.
Geospatial visualization – it is one of the most visually attractive types of data visualization. It allows us to present the information with the usage of maps of any kind. It’s great for analyzing sales channels, customer groups or demand.
One-dimensional and three-dimensional visualization – those are respectively: simple data lists (ex. tables) and volumetric visualizations, used mainly in research centers.
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Business data visualization thanks to Business Intelligence
Business Intelligence is a system supporting business analytics. It’s a tool allowing us to effectively gather and process data, create reports and prepare multidimensional analysis. Thanks to ready reports and dashboards even people without experience in data processing are able to create insight conclusions in an understandable manner. That’s what the data visualization in BI is all about. Data analytics also prefer using those tools, because it makes their work much faster and more convenient.
BI systems can download data from a lot of various sources, while keeping an eye if no anomaly or duplication is happening. Thanks to the full digitalization, all the information will be stored in the cloud, guaranteeing complete data safety and accessibility 24 hours a day.
Data visualization Business Intelligence type programs are often expanded with modern Artificial Intelligence algorithms. It’s currently the most effective way of data management. Machine Learning recognizes trends, analyzes information from the web and creates forecasts based on hard, statistical data. Those solutions can be more costly, but they make our business operations statistically the most likely to succeed. According to Nuclear research analysis the potential of BI and data visualization tools together can combine into ROI worth 13,01 USD on every dollar spent.
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Right now is beggining to write his master's thesis in Informational Management at Jagiellonian University. Michał loves playing billiards, board games and is a huge e-sports fan.