Big Data Visualization Trends for 2016
One of the biggest hurdles that comes with collecting trillions of bytes of data is figuring out what to do with it. A rule of thumb that organizations will need to start adopting in the near future is the idea that not all data is created equal. For the past year and a half, the conversation among digital marketers and industry leaders has focused mainly on the idea of "big data" and how to harness its potential business implementations.Silos of collected data are virtually sitting in digital storage, waiting for someone to come along and interpret it all. As 2015 comes to a close, though, it's good to look forward and determine how visualization will play a major role in the synthesis of big data.Here is a collection of trends and preliminary predictions, as it pertains to big data visualization, that you can anticipate for 2016:
Quality Over Quantity
One of the biggest hurdles that comes with collecting trillions of bytes of data is figuring out what to do with it. A rule of thumb that organizations will need to start adopting in the near future is the idea that not all data is created equal.In reality, a good amount of data is disjointed and potentially useless if your organization has specific needs that don't coincide with said data. Although there are platforms, like MySQL and Hadoop, that are designed to handle the organized chaos of big data, more emphasis should and will be placed on pinpointing which types of data visualizations work best for your organization.A centralized focus on the quality of data collected will become a major element of successful digital strategy going into 2016. Big data seeks to drive digital strategy by helping to make more thoughtful decisions based on collected data.
Situational Analytics
Conversely, as less emphasis is placed on the sheer volume of data being consumed, more attention will go towards finding ways to de-standardize the way in which big data is analyzed. It's already happening at over 20 percent of big-data firms, but experimentation will see a tremendous rise in 2016.This is doubly true for organizations that already have a head start on fine tuning which types of data they plan on working with.In addition to focusing more on customized analytics, there will also be an upswing in its predictiveness, too. This will help to provide higher insights on probability outcomes, while allowing analysts the ability to pinpoint the most desirable of said outcomes for future instances.
Advanced Data Security Measures
There are plenty of large and small organizations that fell victim to data breaches over the last five years or so, which helped exacerbate the growing concerns over big data privacy issues. Thankfully, over the last year, fears have been quelled with major advances in data encryption measures that will continue to proliferate well into 2016.Companies have also taken more of a proactive approach towards the implementation of data storage frameworks and the installation of proper data management controls. The combination of the two will result in tighter security and a restored peace of mind among shareholders and users alike.
Emphasis on Storage
Cloud-based storage and warehousing will play a significant role in how big data is both transferred and synthesized by organizations. Companies like HP, Amazon and more have already created flagship data storage services for enterprise-level companies.In 2016, though, you're going to see an increase in boutique-style, big-data alternatives that will work with companies that may not want to have their data bumping elbows with competitors' data within the same mainstream, cloud-storage provider.A great deal of emphasis has been placed on the collection of data, but not nearly as much on how to synthesize it into successful, lucrative business opportunities. This is especially going to become the main responsibility for executive-level staff in the next year.There will undoubtedly need to be a push from both major and minor companies to think dynamically about big data, its advantages and limitations, and how it will all play in shaping the way cultures and organizations process the world around them.