While technology has thoroughly infused the workplace, its strategic adoption and meaningful application by the typical worker is actually just beginning. Here's how the digital workplace will develop in 2014.
Trenchless Technology Cities Save Money with System-Wide Approach to Asset Management Trenchless Technology PCWASA technical services division manager Keisha Thorpe added, “Having our system-wide data in ICOM3 allows us to be prudent with our...
The Internet of Things (IoT, for short) is a phrase for when everyday objects are connected to the internet and participating together on a system, though it also means the convergence of conventional connected devices and smart appliances.
The goal is to have people seamlessly retrieve knowledge and function on a day-to-day basis without having to sit down at a computer or talk to another human. It's like ubiquitous computing, but it goes beyond Google Glass and extends to every home, car, business, building and system in the world.
Report from Black & Veatch - link. The era of engineer as data scientist is upon us. This is an important point they make: "New technologies enable operators to measure asset and system conditions, status, performance and ...
As someone who trained as a statistician, I've always struggled with that title. I love the rigor and insight that Statistics brings to data analysis, but let's face it: Statistics — the name — has always had a bit of a branding problem.
For every Amazon, Apple, Facebook, Twitter, Netflix, and Google, there are still thousands of midsized and large organizations that are doing nothing with big data beyond giving it lip service.
One big barrier to implementation is the incessant noise around big data from consultants, vendors, and the media. The din leaves many, if not most, CXOs confused and intimidated. They wonder: Do we start small or large? Is big data just another IT project that can be run by a unit head? And what’s the ROI going to be, anyway?
Computing pioneer Alan Kay had some advice in the 1980s that Steve Jobs clearly took to heart: "People who are really serious about software should make their own hardware." Enough said, right? Kay's prescience came to mind again when Google recently announced it was buying Nest, maker of the smart home thermostat, for $3.2 billion.
That's not pocket change, and it's prompted the digerati to proclaim once again that hardware is the new software. And they're absolutely right. The Internet of Things has gone mainstream. Here are three predictions on what it will do to the way you work:
Rise of the 'Thingernet'
Until now, the conversation around the Internet of Things, a neologism that imagines a future dominated by machine-to-machine communications, has been a low murmur--at least outside of tech circles. But with Google's acquisition of Nest (and its $13 billion buyout of Motorola before that), that buzzing has been amplified into a full-blown chorus. We're no longer talking about automatic syncing between a smartphone and a computer or the on/off switch on a Bluetooth device. It's becoming increasingly obvious that the Internet of Things (or, "Thingernet," as The Economist calls it) is rapidly changing the way we, as humans, interact. Just as important, the Internet of Things is fundamentally reshaping how we work.
Big data, data standards, blah, blah, blah-blah, blah-blah, listen to the rhythm of the failing data-driven anything. Why does leveraging big data or developing industry standards matter when internal processes have no ...
Where is big data heading? In 2013, I spent a lot of time talking about Hadoop's development towards being a central destination for data. Hadoop may enter an organization for a specific use case, but data attracts data.
Much of human inquiry today is focused on collecting massive quantities of data about complex systems, with the underlying assumption that more data leads to more insight into how to solve the challenges facing humanity. However, the questions we wish to address require identifying the impact of interventions on the behavior of a system, and to do this we must know which pieces of information are important and how they fit together. Here we describe why complex systems require different methods than simple systems and provide an overview of the corresponding paradigm shift in physics. We then connect the core ideas of the paradigm shift to information theory and describe how a parallel shift could take place in the study of complex biological and social systems. Finally, we provide a general framework for characterizing the importance of information. Framing scientific inquiry as an effort to objectively determine what is important and unimportant rather than collecting as much information as possible is a means for advancing our understanding and addressing many practical biological and social challenges.
Yaneer Bar-Yam and Maya Bialik, Beyond Big Data: Identifying important information for real world challenges
People like to say, “keep it simple, stupid.” It's a down-home remedy for our overly complex, technology infused modern life. Like much good advice, it is often given, but rarely followed. The problem is that simplicity is not so simple. We live in a complex universe where much that happens is beyond our control. Merely wishing things to be simpler does not make it so. In fact, making facile assumptions often leads to disaster ...