WEB & TECH / MAY. 24, 2014
version 2, draft 2

Big Data Visualized: Making Complex Information Easy To Read

big data

Do you feel overwhelmed when looking at a full spreadsheet? You’re not alone.

It’s a common problem that people have, which has a simple solution.

The interpretation of big data goes beyond words and numbers. These days, companies use creative visuals to showcase big data in order to better understand large amounts of information. Let’s take a closer look at why data and visuals go together.

Why does big data need to be visualized?

There are many components of big data that are being mined on a daily basis. It can be difficult to make the necessary connections using thoughts alone. One could leave out specific elements, or lack the imagination to make different combinations out of all the information. More importantly, big data visualization bridges the gap between complex components.

Interpretation is a lot easier when information is laid out using visuals. When presenting big data to clients, graphs can clear the confusion faster than a long explanation. It also adds meaning to values that otherwise would seem lacking and dull. Overall, big data visualization is a communication tool between statistics and humans.

Do visualization tools really work?

Imagine your favorite infographic without the visuals, plotted in an Excel spreadsheet. You would have to take the initiative to make connections to various points, making interpretation varied. Big data visuals ensure that everyone who is viewing the graphic is on the same page, which is important during discussions, meetings and conferences.

Businesses use infographics to help visitors and clients understand complicated information. Infographics are friendly, and straightforward. In most cases, the information found in infographics has been trimmed down to the essentials or the bare minimum. People can relate to them easily, making them very popular. Visually, they make information approachable and easy to digest.

Big data visualization is designed for simplicity. For companies that need answers immediately, the right visualization tools can help them address underlying issues without digging deep into piles of information.

Types of big data visualization

Effective big data visualization makes use of several components at one time using one display. For example, circles could represent a specific demographic, which varies in size, indicating its relevance against other components. The transparency of colors could indicate the number of visits to a website (darker circles mean the demographic visits the site often, while light circles show the opposite).

Based on the example above, big data visuals have the ability to display details with ease. This can streamline the problem solving process, making it less frustrating. As a result, making references to support one’s decisions can be done by simply referring to different parts of the visual.

Interactive visuals: going a step further

Showcasing big data in an appealing manner is one of the main objectives of the practice. Some big data visuals even make their charts interactive. This can make the association of different elements more effective.

Interactive visuals are used for problems with several solutions. Examples of this are online ad campaigns. These types of concerns require numerous variables to be put together, from sets of target audiences to social media platforms.

To conclude, don’t let loads of information prevent you from analyzing big data. With the right tools and visuals, you can get the information you need without spending countless hours looking at a spreadsheet.

Do you have a favorite chart of graph? Share your professional experience with us.


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