Why Data Visualization Matters in Data Analytics?

What if you wanted to find out how many movies are made each year across different locations worldwide?

You may always browse this information as a black-and-white text spread across numerous pages. Alternatively, you could have a vivid bar chart that shows you which nations are releasing more movies and if the overall number of films produced every year is rising or declining. 

In other words, a bar chart can convey your information merely by glancing at it, whereas you would typically have to read numerous pages of data to comprehend it. 

This is Data Visualization’s true power! It enables us to quickly spot trends and patterns in data that might otherwise be difficult to spot. 

Are you still not sure about Data Visualization and why it matters in Data Analytics? Well then, let’s start from the basics and understand what Data Visualization is. 

What is Data Visualization in Data Analytics? 

We can apply Data Analytics to analyze Big Data and draw valuable insights, but it’s preferable if those results are presented in a way that is easier to understand. This is when Data Visualization comes into play! 

Data visualization is the process of creating graphical displays to showcase data. In some cases, like in a scatterplot, every data point is represented, whereas, in others, like in a histogram, statistical summaries are displayed. 

The graphics are primarily descriptive, focusing on ‘raw’ data and brief summaries. They can contain visualizations of transformed data, sometimes resulting from complex processes. The raw data of one individual may be the statistics of another. 

It would be beneficial to have an agreed-upon framework of concepts and vocabulary to work on, much as with other elements of working with visuals. The main purpose is to view data and statistics and understand the displays to gather information. 

How Does Data Visualization Help in Data Analytics? 

Do data visualization Services benefit your organization? Regardless of the type and size, every organization may benefit from accessible data assets if suitable solutions and procedures are in place. 

The benefits of data visualization in data analytics are so numerous that every decision-maker, whether a local retail shopkeeper or the management board of a big industrial organization, may find a method to extract and apply insights to their benefit. 

Here are some of the most important data visualization advantages that demonstrate how it works. 

The Role of Data Visualization in Data Analytics

Humans Process Visual Data Better:

The human brain has evolved so that we find visual information more fascinating and significant than any other type of information. The brain takes a split second (approximately 250 milliseconds) to receive, analyze, and evaluate information presented in visual form.   

Even a substantial part of our thinking involves visuals. There is a strong link between visual processing and recollection, which means that you are far more likely to recall visual information than written information (approximately ten times).   

A Picture is Worth a Thousand Words:

By visualizing information, we turn it into a landscape that you can explore with your own eyes, a sort of information map. And when you’re lost in information, an information map is kind of useful. — David McCandless 

Famous quotes have a way of taking on their own life. A picture does not replace the need for a thousand words; it necessitates the use of a thousand words (or more). 

Data visualization is the ideal option when you have a lot of data but not enough time since it gives you a window into the wider picture. You may also use data visualization during brainstorming meetings to show what you mean without saying much. 

The context, the source of information, how and why it was acquired, whether more might be collected, the reasons for creating the displays, and how persons with the required background knowledge advise they should be understood are all important for data visualization. 

Saves Precious Time:

The facts and the visuals must complement each other, and combining outstanding analysis with a great narrative is an art.   

According to American Management Association statistics, data visualization may cut short business meetings by 24%.   

According to a Tableau survey, managers who employ visual data recovery solutions retrieve valid data. Whereas more than 48% seek assistance from their IT workers and other individuals.   

Data Visualization tools’ superior analytical capabilities make decision-making 5 times easier than their competitors.   

Visualization Helps Identify Trends & Patterns

When data is demonstrated graphically, it is much easier to find trends and patterns. Of course, some patterns are evident and may be detected right away. But there may be some hidden relationships and practices in the data that you were unaware of.   

Data visualization satisfies our aesthetic demands to perceive bright and colorful patterns and connect the dots between them and business needs by combining art with data.   

Color-coded charts, graphs, animations, maps, diagrams, wordles, pictographs, and infographics, etc., are used to assist us in identifying previously overlooked patterns, connections, gaps, and trends in data. It simplifies and speeds up business and data analytics.   

Data Visualization Increases Traffic

Data visualization may boost online traffic and user interaction and be an efficient approach to do web analytics by allowing you to examine the patterns, trends, and frequencies of traffic flow to your website.

“45 percent more online surfers will click on a link if it has an infographic,” according to one estimate.   

The human attraction with colors, forms, and patterns accomplishes the task. Pinterest, the photo-sharing website, has risen to become the third most popular social networking site due to its visual appeal.    

Data Analytics and Visualization Working Hand-in-Hand 

Data analysis and data visualization are essential BI tools for extracting value from an organization’s enormous data set. They can give key stakeholders the most valuable and relevant information if they work together.   

However, data visualization is only as effective as the analytics it is based on. The insights it portrays are dependent on the quality of the analytics presented, like the decades-old cliché “garbage in, garbage out.” Poor data models and messy or insufficient data, no matter how attractively displayed, help no one.   

Clean, sophisticated, and extensive data analysis, on the other hand, may supply the raw materials for impactful. Whereas vital data visualization tools like dashboards can provide decision-makers with the insights they need to drive their organization.   

To sum it up… 

You’ll want to have high-quality, relevant insight that can easily visualize before you start describing and visually creating your data.

When it comes to data visualization, it’s essential to understand which data format is most suited to the visualization’s unique shape and function. After all, quality is a must. 

Also Read: The Role of AI in Banking and Finance Sector