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The Future of Data Visualization

All great data visualizations tell a story.

They keep in mind their audience, they’re bias-free, they don’t censor what the data is telling them, and they’re meticulously crafted by someone who understands how to present it in a manner that lets the data speak for itself.

 

The Past | Information Design

Visualizing data isn’t a new practice. For thousands of years, we’ve been trying to create visuals to understand data, track trends, and make sense of the world around us. From star charts to Charles Minard’s famous visualization of Napoleon’s March on Moscow, we’ve come a long way.

However, data and the visuals to go along with it were restricted to a select few. To obtain this information you’d have to be literate and have ready access to this particular kind of documentation. If you wanted access to data, many circumstances needed to align for you to get your hands on it.

The Present | Data to the People


With the dawn of the internet came a new way of doing things – bringing data to the people.

Rather than being a passive part of the background visible to a select few, data has become an everyday part of life. Mostly used as a tool to augment journalism; it’s designed in a manner that encourages exploration and a more engaged and aware public. Any news site you visit will most likely have an interactive visualization, providing you with tangible proof of the point they’re trying to prove.

The barrier of entry for accessing and asking questions with data is lower than ever. Business Intelligence questions can be answered by a savvy user in minutes instead of days, and the cost to access visualization tools has been substantially reduced.

The Future | Self-Service Analytics

Thanks to tools such as natural language processing (NLP), and chatbots; data is becoming increasingly more accessible by the day. Instead of configuring charts, you can type a question you need an answer to in Power BI and have it create a response using your pre-existing data.

As Virtual and Augmented reality become increasingly more popular, we’re seeing a trend of visualizing data using interactive, 3D spaces. The value of analyzing in higher dimensions comes with the ability to find more complex relationships between data.

Going forward, the line between Data Science and Data Visualization will become increasingly blurred. These practices are slowly becoming more complementary and interdependent. Data Visualization can give us the resources to understand what’s happening inside a neural network as it attempts to recognize handwritten characters. We can visualize the individual neurons firing as information is placed in front of it, and even visualize all the characters it identifies as a particular number or letter.

Data Scientists can even use visualizations to double-check their work, indicating if they’re on the right track.

Why Bother with Data Visualization?

Why not just use a spreadsheet?

First, you need to have an understanding of how the human mind makes sense of information.

When you look at a dataset in a spreadsheet, attentive processing makes you scan the document, and make conscious comparisons. Spotting trends, identifying abnormalities, and points of interest from numbers is hard work.

When we look at data visualizations use preattentive processing. This means your brain’s natural ability to spot patterns, trends, and things that are out of place begins to sort out what’s important, and what’s not. 90% of the information our brains process is visual, and using a data visualization versus numbers allows for us to process and understand what’s in front of us with minimal effort relative to attentive processing.

What Now?

The practice of data visualization is constantly evolving and the technical barrier for entry into the world of Data Visualization is lower than ever.

Many thanks to Brad Gagne, Lixar Data Visualization Specialist.