New startups are springing up with interesting solutions to problems in big data as we know it. They're cooking up an interesting list of the potential next big things in big data.
While the business world has recently experienced a rapid growth in data and discovered ways to manage and use it, the new tools have yet to fully measure up to handling the mega-data scientists are still trying to get a handle on.
Check out this infographic for tips on explaining big data to people who work anywhere and with anything other than big data.
Wearables are sensors dedicated to interpreting you and the world from your perspective. Pervasive sensors, on the other hand, sit in places throughout the environment where they study and respond to you when you're in the vicinity.
Bernard Marr has a good post in SmartDataCollective on the four key layers of the big data system.
There are plenty of examples of how big data tools deliver rotten results--not due to a fault in the tool, but rather a shortcoming in the strategy, algorithm and/or data sets behind its use.
The United States Postal Service is seeking proposals from suppliers that can rocket its "Internet of Postal Things Project" into reality.
UN Global Pulse relies on social media data analysis to alert them to emerging crises such as food shortages, conflict, and disease outbreaks. Now they've partnered with DataSift to help on the big data end of things.
Chicago has been all aboard the big data train since it pulled up to the station. But Chicago isn't just along for the ride. The city is striving to create an embedded sensor network dubbed the "Array of Things" to lay the track to its future as the reigning "City of Big Data."
$795 per user per year--that's the sticker price for Revolution Analytics' new support service for the open-source statistical programming language R.