The future trends of data visualization

Let’s discuss some of the current and would-be trends in the data visualization arena.

Social first data visualizations

It is seeing higher levels of engagement from followers in social nowadays. Users of this technology all over are making efforts for it to be social media friendly. It is common knowledge that social media users’ attention span is quite low and hence data has to be presented to them in a visually attractive way. Some examples along this kind of visualization include looping animations, youtube short videos and GIFs.

Color trends

What attracts users to the data visualization is because of the colors. Pantone Color Institute picked on Greenery 15-0343 as the 2017’s color of the year. This color is symbolic of the freshness, environmentalism and that of the nature. Obviously data visualization trends will be much affected by these developments. DigitalArts portrays that there would be a rise in colors like maroon, charcoal grey, olive green, khaki and red brick.

Mobile first visualizations

This may seem contrary to the popular opinion about mobiles being not apt for data visualization owing to its limited screen size. The power and capability of mobile phones is increasing with more and more features being added to them. Mobile phones have become ubiquitous and they are clearly the future. Hence inevitably we will witness many innovations in mobile data visualization. Many vendors are adapting desktop experiences to mobile formats to get a mobile first approach in terms of data visualization. Apple acquired Mapsense a data visualization startup for $30 million.

Mobile apps are turning instrumental for controlling remote services, infrastructures and upscale systems with the help of IoT(Internet of Things) and online trading. From stock prices, sensors on athletics and even price performance, data visualization helps in operation monitoring, process optimization and in making sound decisions.

Virtual Reality and Mixed reality

VR has the potential in it to revamp major industries. A 2D screen will do little in making the users understand huge chunks of data. One can garner only limited insights from a 2D figure. With VR however, the perceiver is placed in midst of an immersive space that portrays data with vivid visualized detail. The group corporate meetings in sci-fi movies where there will be data visualization in bar charts, pie charts and so on is actually the concept of MR. When that experience is restricted to a single donning the HMD(head mounted display) then the technology of VR is said to be in play.

Data journalism

With the data availability and apt tools to visualize it we are witnessing some very vivid data visualization all over the globe. We will see increasingly effective data visualization in news reporting and storytelling from popular news rooms. Even when data visualization was just a buzzword the climate and weather news would be delivered in vivid visualizations of various daily temperatures. As more and more media houses see the benefits of this trend they will surely follow.

Complex data sources

The comprehensiveness and the effectiveness of data visualization will actually depend on the type of data that goes into it. It is now possible to collect data using some complex methods and there are a host of methods that can be used for it. This in turn puts us in touch with complex data configurations. This means better insights with goo value which can be passed to those concerned. Data visualizers should therefore choose the right data sources for realizing better data visualization.

Artificial intelligence

AI is going to disrupt each key domain as we will witness in the fourth industrial revolution. The growth of data goes beyond dashboards AI can also help in data visualization. There is a huge plethora of data that should be harnessed as soon as possible for mission critical insights. NLP and machine learning can work together to reveal key insights and can greatly reduce the data visualization workload for humans. AI can in instrumental in identifying anomalies, comparing graphs, finding out key insights which are then put in a way layman can easily understand. There is a possibility when a whole lot of data visualization can’t be interpreted and AI can be a sure shot remedy to that.

Conclusion:

Data visualization can be of great help in a data-focused world. Designers and developers should strap in for experiencing technological advancements which will in turn increase demand for data visualization apps. Data visualization adoption will become integral into managing our day to day tasks as its benefits just can’t be ruled out.

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