Editor’s Note: Speaking at the Enterprise 2.0 Building Social Business conference in Boston in June, AT&T Enterprise Mobility Executive Director Mobeen Khan joined other panelists to discuss “The Future of Big Data: What’s Next?” The discussion was facilitated by Johna Till Johnson, President and Senior Founding Partner of Nemertes Research.
Our discussion on “The Future of Big Data: What’s Next?” drew an audience of mostly technical and marketing professionals looking to use big data to make smarter decisions in their operations. Attendees were interested in learning more from the streams of data originating from online sources and customer interactions, as well as from social media marketing and sales campaigns.
I spoke about all of the data produced through mobility and about the future of Big Data in general. The future is very exciting, with devices, sensors, appliances, and “things” around us – and our interactions with those things – producing valuable data. For example, there are approximately 4.4 billion or so cell phones in use today, and we expect to see the number of connected endpoints reach more than fifty billion as communication gets embedded into everything we use directly and indirectly.
These devices and our interactions with them will produce a vast amount of data in the future. How do businesses make sense out of this data? How do they interpret it to make near-real-time decisions? How can this data make our businesses smarter? Furthermore, how do we invent new businesses from this opportunity?
Answers to these questions are emerging as companies use technology and disciplines like analytics to make sense of the growing amount of data generated from fixed and mobile devices. In preparing for this panel, a couple of things made an impression on me. First, the volume of data that our customers, society, and businesses are creating is tremendous. The opportunity to extract important intelligence from this data is just as huge.
At AT&T today, 30 petabytes of data crosses our network on an average business day. That’s a humongous amount, almost incomprehensible, especially given that not too long ago that number was one petabyte of data a month. The amount of data crossing the network continues to grow at a tremendous rate.
The second thing that struck me was that the data being produced is not just data that should be stored for reporting purposes. Rather, the opportunity is in finding the intelligence within streams of data in real time—this is the real challenge and where the real opportunity lies.
Analyzing data produced by mobile and fixed assets in real time can provide insight into the supply chain. For example, oil and gas companies have assets and processes scattered all across the world on rigs and at offshore facilities, and so on. Improved tracking, an optimized supply chain, reduced maintenance costs, and lower injuries among workers are now possible due to the flow and real-time analysis of this data. The benefits are virtually endless. Beyond using the data within the supply chain, these organizations can take select data and expose it to partners or their end customers, making entire eco-systems more agile and productive.
For the average individual, there are big data benefits as well. For a diabetic in his home using a health care application that reads his blood glucose results, it can be lifesaving. If those readings are consistently off normal, for example, and the patient hasn’t answered his last four phone calls and texts, or the doorbell (and your location shows the patient is at home), help can be dispatched to look after that person’s well-being.
When our customers implement a mobility solution, whether it’s for their employees, customers, or a machine-to-machine solution, the intelligence extracted from data using analytics is becoming a much more important part of the overall solution. The goal is to enable customers to collect, curate, and expose the right data so that businesses can make real time decisions that improve performance.
From leading companies like AT&T and Oracle (also part of the panel) to technology startups, innovation is underway in this area. I knew about it, but seeing it firsthand at the conference, I was really impressed. I guess those tough courses on graph theory and design of statistical experiments may finally pay off!