Man and machine are converging. On the one hand you have man with his Web-enabled mobile smartphones and tablets. On the other hand you have Big Data, servers and ubiquitous connectivity. Put them together and you have opportunity. Low-power, networked microprocessors and microcontrollers are great, it's the big data behind them that makes them powerful in ways besides technology. With billions of IPv6 devices sending bits of data everywhere, somebody is going to have to make sense of it all. Developers and engineers will need to figure out how to sort and analyze this information in a productive manner, then make decisions that affect everyday life. Marshall Kirkpatrick notes in his article How Big Data From Connected Machines Gets Used that sensors married to smartphone apps are saving time, money and effort maintaining medical equipment. If you're a mobile developer, it might be a good time to start brushing up on your “deep analytical” skills (like math and statistics), so you can build that great new Android app on the user facing side. Then you can crunch the numbers from all those machines streaming data from sensors on the server side. If you're really ambitious, managing that type of a project would be quite challenging -- and probably pretty lucrative. Of course, you'd need the business and people skills, along with the technical chops, to pull it off. Lots of startups are doing exactly this. New York Times technology reporter Steve Lohr says that Big Data is nothing short of a revolution. He contends that a great deal of these massive mountains of data are unstructured. Programmers who know natural-language processing, pattern recognition and machine learning will certainly be needed to write the algorithms that organize the data in meaningful and productive ways. We aren't quite to the point of ubiquitous connectivity, where people are seamlessly connected to the Internet everywhere, all the time, on every device. The flood gates aren't fully open, but it's coming. Data volumes will only grow as each device connects to the Web. The obscure, large data set, statistical analysis language R, has been in the spotlight lately. Could these trends lead to great prosperity and meaningful work for motivated innovators? I think so. Mobile, Big Data and Developer Opportunities
Man and machine are converging. On the one hand you have man with his Web-enabled mobile smartphones and tablets. On the other hand you have Big Data, servers and ubiquitous connectivity. Put them together and you have opportunity. Low-power, networked microprocessors and microcontrollers are great, it's the big data behind them that makes them powerful in ways besides technology. With billions of IPv6 devices sending bits of data everywhere, somebody is going to have to make sense of it all. Developers and engineers will need to figure out how to sort and analyze this information in a productive manner, then make decisions that affect everyday life. Marshall Kirkpatrick notes in his article How Big Data From Connected Machines Gets Used that sensors married to smartphone apps are saving time, money and effort maintaining medical equipment. If you're a mobile developer, it might be a good time to start brushing up on your “deep analytical” skills (like math and statistics), so you can build that great new Android app on the user facing side. Then you can crunch the numbers from all those machines streaming data from sensors on the server side. If you're really ambitious, managing that type of a project would be quite challenging -- and probably pretty lucrative. Of course, you'd need the business and people skills, along with the technical chops, to pull it off. Lots of startups are doing exactly this. New York Times technology reporter Steve Lohr says that Big Data is nothing short of a revolution. He contends that a great deal of these massive mountains of data are unstructured. Programmers who know natural-language processing, pattern recognition and machine learning will certainly be needed to write the algorithms that organize the data in meaningful and productive ways. We aren't quite to the point of ubiquitous connectivity, where people are seamlessly connected to the Internet everywhere, all the time, on every device. The flood gates aren't fully open, but it's coming. Data volumes will only grow as each device connects to the Web. The obscure, large data set, statistical analysis language R, has been in the spotlight lately. Could these trends lead to great prosperity and meaningful work for motivated innovators? I think so. 
