The age of data visualization is here, and if you aren’t already taking advantage of it, you’re missing out. Data visualization involves the collection and processing of large volumes of data, eventually producing charts, graphs, and other visual depictions that end-users can interact with.
The advantage here is that visual information is much easier to digest, or understand, than raw numbers. Whether you’re a marketer trying to better understand a campaign or a sales manager making a pitch to a client, that faster data recognition will almost certainly make your life easier.
Already, companies like Zoomdata are revolutionizing the industry by putting embedded analytics tools in the hands of app developers and business analysts. But data visualization is still young, and may be about to change in some significant ways.
Data Visualization Growth
So just how might data visualization grow in the next several years?
1. Real-time.
We’re on the precipice of 5G internet, which is predicted to sport speeds of up to 10 gigabytes per second, more than 10 times the amount that 4G networks can support. With speeds at that level, you could feasibly download an entire high-definition movie in a matter of seconds. For data visualization, that means you could download data at a faster rate than ever, possibly drawing information from your surroundings via video or streaming information from one device to another. With fast enough software, you could produce live interpretations of what’s going on in your environment, whether that’s a statistical analysis of a sporting match or a play-by-play of audience reactions to your big speech.
2. Virtual reality.
All of our current data visualization tools render data in two dimensions, relying on conventional modes of information transmission like pie charts, bar graphs, or two-dimensional maps. These are highly effective and efficient at projecting information—but imagine what you’d be able to see and interact with in three dimensions. That’s where virtual reality (VR) comes into play. With a VR headset (and sufficient supporting software), you’d be able to project data into a three-dimensional landscape that responds to your physical forms of interaction and takes a shape that seems more “real,” depending on the application.
3. Interpretations.
For the most part, data visualizations are mere tools to help make interpreting large data sets easier for human beings. But what if those same algorithms could interpret the data themselves? In the next few years, researchers may be able to combine data interpretation with natural language algorithms to articulate key takeaways from various reports—and ones that go beyond a simple relay of numbers from one point to another.
4. Outliers and flaws.
Human-produced data analysis and interpretation algorithms are excellent at making broad generalizations, at finding patterns, and interpreting things as objectively as possible. That sounds perfect, right? Unfortunately, the successful interpretation of data sometimes depends on being able to spot the exceptions from the rule, and the pieces of data that don’t fit the pattern. For example, outliers can sometimes tell you more about your audience than all the rest of your data combined. Also, remember that visualizations are entirely dependent on the value and integrity of the data you input into those visualization algorithms; if the data is bad, you’ll get a bad visualization. Future visualization algorithms may be able to proactively detect data quality, before making an incorrect assumption.
5. User adoption.
Currently, most data visualization tools are targeted toward companies and professionals. As the industry develops, becomes more crowded, and becomes more accessible, expect to see that targeting shift to ordinary consumers. Once data gathering, visualization, and interpretation algorithms are commonly, or even freely available to the public, there will likely be an explosion of data-based content available online. That means more competition, more educated consumers, and an entirely new dynamic for your business to work with (and plan around).
Looking to the Future
If you don’t already have at least one data visualization tool for your organization, it’s time to consider shopping for one—especially for your sales, marketing, and advertising departments. The data visualization industry currently represents about 4.12 billion dollars, and is projected to grow to nearly 7 billion dollars by the end of 2022.