Future - machine to machine real time big data

Many of us have heard of IOT (internet of things).  This will happen is a given at this point. Each end point currently generates data and the amount of data will only increase going further. The challenges that need to be resolved are around the consumption of this big data. In real time. Since if big data can provide value in non real time, it can provide a completely different and valuable set of value in real or even pseudo real time.  And this will be a major part of the big data future.

connectivity of devices/people

This important and largely untapped, type of data is the real-time actionable data generated by sources such as devices, sensors and video, which often provide the most value while interacting in real time. The network can provide useful contextual information to data in motion such as a person or device’s location, identity and presence (whether they are “available” or not). This data can be used by applications to make decisions or take actions that are immediately relevant, or even to predict future events. Machine-to-machine communication in factory automation is an example where data in motion could be extremely valuable in optimizing a production process.
According to the Cisco Visual Networking Index Global Mobile Data Traffic Forecast for 2012 to 2017, there will be more than 1.7 billion machine-to-machine connections by 2017.
However, there are a few issues that need to be ironed out before big data becomes mainstream.
On June 11, Gartner Inc. said less than 10% of today’s enterprises have a true information strategy. And while technology is important to big data solutions, people are needed with the special skill sets and creativity—for instance, “data scientists” who transform raw data into information leading to discovery and insight, communicate what they’ve learned in creative and visual ways, and suggest business impact.
On June 5, Gartner said big data will grow past its hype towards 2016 to become “just data” once the technologies mature, and organizations learn how to deal with it. “The bottom line is that not all information requires a big data approach,” said Frank Buytendijk, research vice-president at Gartner. “The new “big data way’ is not going to replace all other forms of information management. There is more room—and need—for experimentation in the area of “information of innovation”, for instance, with social media data, or by making processes more information-centric.”