In today’s world, consumer attention is constantly being fought for. It has been shown that visual representations of data aid in capturing attention and keeping it for a longer period time. In order to be successful, it is important for businesses to be identifiable and easily separated and differentiated from other businesses. A great way to for businesses to set themselves apart is to use unique and innovative data visualizations. These types of visualizations help communicate different types of information effectively and plainly through engaging graphics.
What is a Data Visualization?
Plainly stated, data visualization is a method of merging data into an easy and exciting graphic representation. Visual representations of data have mainly been used for quantitative information, like statistical analysis, but today, are being used more and more to represent qualitative information as well.
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Using visual information helps simplify complex and arduous information and can be used to convey many different types of data, ranging from statistical numbers to survey results. These types of visualizations can be functional as well as simultaneously aesthetic and interesting. Conveying ideas effectively takes functionality and aesthetic design. Many businesses fail to find a balance between functionality and aesthetics; over-the-top data visualizations are not effective if the data used to create them is unreliable or insufficient.
Visual Data has Created a New Competitive Business Market
A new competitive business market has emerged through the innovation of visual data. Companies worldwide have recognized the worth of representing data in a visual, easily understandable way. Companies have emerged simply for the purposes of visual data representation. These types of businesses bring together statisticians, marketing gurus, designers and businesses who need to share their data. Common business intelligence (BI) is to turn data into visual content to more likely engage with many populations of people (researchers, consumers, potential clients, etc.), helping make business more successful and marketable. Visual content is also easier to share via social networking websites, enabling a business to have more potential consumer contact.
It is important for business to also know that not all visual representations of data are actually helpful. There are ways for data visualizations to be confusing and sometimes even misleading. Using visual data to purposefully mislead is unethical, and businesses should avoid this type of representation at all costs.
What Makes the Best Visualizations?
When it comes to visual data representations, the best ones seem to expose something new about the data being represented. Clean and simplified results are more effective than complex text, and appeal to a much wider audience than the printed word alone. Understanding the intricate connections and relationships between data points, and being able to represent them effectively, is a great way for businesses and the consumers to make good, sound decisions.
Explaining VS. Exploring with Visual Data
There are myriad ways to represent data, and not all visualizations are created equal. There are typically two reasons data visualizations are created: for explaining data and exploring data. The distinction between these two reasons is quite important. Visual data used for exploring is, in its nature, imprecise. It is typically used when researchers don’t know what conclusions their data is showing them. Exploring data with visualizations helps elucidate patterns and relationships contained within the data. Visual data used for explaining is used to quickly and efficiently illustrate known conclusions and patterns that are shown by data. This type of representation is clean and to the point.
Using data visuals to explain research results and patterns aids potential customer exploration, helping them better understand the business itself. This one reason is why many companies, from big to small, are starting to allocate a significant amount of monetary resources to creating visualizations based on hard data.
As data becomes a more important part of successful business and an integral part of BI, data visualizations will become even more important. In this age of research and knowledge, consumers and even the general public expect complex information to be pared down to the bottom line and presented in a visually understandable and aesthetic way.