Data Visualization is an integral part of Big Data and Analytics as intelligent visuals help scientists and laymen alike to wade through racks of data with ease and arrive at critical business decisions. The method of visually exploring data has also enabled breaking up complex patterns into manageable chunks and as a result the markets are now brimming with intelligent visualization tools.
The future of Big Data cannot be predicted without talking about Data Visualization as a science for the future; Gartner even predicts that by 2018, Hadoop, search and visual-based data discovery would “converge into a single form of next-generation data discovery”. Therefore it is important for any enterprise to understand the trends and possibilities of Data Visualization for years to come.
Trend-setting Visualizations- 2016
The charm in data visualization lies in the fact that this field allows anybody to prepare, process and read data on their own. So before we look into the future, here is the list of top examples from 2016 that exemplified the essence of visualizing data in understanding them.
- My top pick for one of the most elaborate and eloquent data visualization comes as a video, courtesy of American Museum of Natural History. In 6:24 minutes, this video explains the evolution and growth of Homo sapiens in stunning detail.
- While we are still reeling from the results of 2016 US presidential elections, here is tableau public’s interactive infographic titled “Look back at US Presidential Election Results from 1920-2012 utilizing a small multiples approach” (now including the results from 2016 elections as well).
- This infographic by guardian revealing the most googled characters per episode per season is brilliant, to say the least. Check the rest of the infographic here (Warning: Spoilers ahead!)
Trends for the future
Just like art in general, classic trends, like creating a highly tidy infographic with neat patterns and crisp colors, will never lose its craze among the data purists. Almost every successful visualization giant operates with this baseline and the growing plethora of intelligent tools has empowered anyone to create an explosion of art and data, literally.
2017 is anticipated to take humanity closer in realizing the dream of seamlessly converting raw bits to monetizable patterns. The top 3 trends that experts vouch for are as follows.
- Visualization through stories
“Numbers have an important story to tell. They rely on you to give them a clear and convincing voice”
-Stephen Few, Data Visualization Guru
The future of storytelling through data visualization seems promising because it adds so much life and value to simple bytes. To be fair to the early adopters, stories and data visualizations have always been around; the discovery of cave paintings from 30,000 BC tells us today, in great detail, the lives of people of the prehistoric era.
In 2017, with growing trends like interactive 3D infographics, animated visuals etc., visualizing data using storyboards and timelines will help enterprises take their message much more effectively to the masses. Organizations would further evolve in employing master data story tellers who would bridge the gap between enormous data and engaging narratives with exciting visuals thereby imprinting their stories in the Interweb for generations to come.
- Tackling Complex Data Sources
The data universe is exploding at the rate of Quintillion bytes of data and the common man has become a walking-talking data source for the enterprises. To tame such volumes, the industry has adopted several complex data-rearing processes that render multitudes of complex data types. The majority of existing data visualization tools is struck amidst unlocking current data complexities and updating themselves for the ever-evolving data types.
Experts believe that 2017 will further the industries advancement in developing tools that will be more suited to extract data out of complex, unknown data sources, map relationships rapidly and extract useful patterns of intriguing visualizations.
- Self-servicing Data Visualization Capabilities
Going forward, in 2017, the general theme would be to create self-servicing visualization packages that combine powerful algorithms and simple UI and could be deployed anywhere on demand. The rise of self-servicing visualization tools would not just empower ordinary users to play with data sources of their choice, it would also push the boundaries of data science beyond the walls of high-end research centers and open avenues for more active data exploration by the masses.
The ultimate aim any scientific solution would be to innovate to the extent that any user would be able to arrive at meaningful results with minimal efforts. Data Visualization, being at the crossroads of art and science, is undoubtedly in a unique position in making data science accessible to everybody and solving complexities in data analytics, one graphical representation at a time.
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