With hundreds of new products and companies jumping into the IoT fray every month, there’s no shortage of innovation. Despite this, McKinsey/VisionMobile data shows "less than 10 percent of IoT developers are making enough to support a reasonably sized team....Oct. 9, 2015 04:00 PM EDT Reads: 238[session] A Cloud and IoT Way of ThinkingBy Liz McMillanThe buzz continues for cloud, data analytics and the Internet of Things (IoT) and their collective impact across all industries. But a new conversation is emerging - how do companies use industry disruption and technology enablers to lead in markets undergoing change, uncertainty and ambiguity? Organizations of all sizes need to evolve and transform, often under massive pressure, as industry lines blur and merge and traditional business models are assaulted and turned upside down. In this new data-driven world, marketplaces reign supreme while interoperability, APIs and applications deliver un...Oct. 9, 2015 04:00 PM EDT Reads: 303[session] Applying IoT to Reduce Power LossesBy Liz McMillanElectric power utilities face relentless pressure on their financial performance, and reducing distribution grid losses is one of the last untapped opportunities to meet their business goals. Combining IoT-enabled sensors and cloud-based data analytics, utilities now are able to find, quantify and reduce losses faster – and with a smaller IT footprint. Solutions exist using Internet-enabled sensors deployed temporarily at strategic locations within the distribution grid to measure actual line loads.Oct. 9, 2015 03:49 PM EDTBusiness Case for Internet of ThingsBy Yeshim DenizToo often with compelling new technologies market participants become overly enamored with that attractiveness of the technology and neglect underlying business drivers. This tendency, what some call the “newest shiny object syndrome,” is understandable given that virtually all of us are heavily engaged in technology. But it is also mistaken. Without concrete business cases driving its deployment, IoT, like many other technologies before it, will fade into obscurity.Oct. 9, 2015 03:45 PM EDT Reads: 141[session] Analysis Engines for IoT DataBy Liz McMillanYou have your devices and your data, but what about the rest of your Internet of Things story? Two popular classes of technologies that nicely handle the Big Data analytics for Internet of Things are Apache Hadoop and NoSQL. Hadoop is designed for parallelizing analytical work across many servers and is ideal for the massive data volumes you create with IoT devices. NoSQL databases such as Apache HBase are ideal for storing and retrieving IoT data as “time series data.” Oct. 9, 2015 03:45 PM EDT Reads: 506[session] How to IoTize and Make MoneyBy Yeshim DenizThe IoT market is on track to hit $7.1 trillion in 2020. The reality is that only a handful of companies are ready for this massive demand. There are a lot of barriers, paint points, traps, and hidden roadblocks. How can we deal with these issues and challenges? The paradigm has changed. Old-style ad-hoc trial-and-error ways will certainly lead you to the dead end. What is mandatory is an overarching and adaptive approach to effectively handle the rapid changes and exponential growth.Oct. 9, 2015 03:00 PM EDT Reads: 207Software Will Power the Internet of ThingsBy AppDynamics BlogToday’s connected world is moving from devices towards things, what this means is that by using increasingly low cost sensors embedded in devices we can create many new use cases. These span across use cases in cities, vehicles, home, offices, factories, retail environments, worksites, health, logistics, and health. These use cases rely on ubiquitous connectivity and generate massive amounts of data at scale. These technologies enable new business opportunities, ways to optimize and automate, along with new ways to engage with users.Oct. 9, 2015 02:00 PM EDT Reads: 188Stop Playing Catch-Up with the IoTBy Elizabeth WhiteThe IoT is upon us, but today’s databases, built on 30-year-old math, require multiple platforms to create a single solution. Data demands of the IoT require Big Data systems that can handle ingest, transactions and analytics concurrently adapting to varied situations as they occur, with speed at scale.