January 10, 2016

Open Source as a Driver of Internet of Things

The zero entry barrier provided by the use of open source, with several toolkits, libraries, and open source hardware like Arduino and Raspberry Pi, is the foundation for it turning up in small devices sprinkled all over the globe, from home security to energy management systems, from automobile telematics to health monitors. Because open source helps lower the cost of the device itself, companies can now experiment and stitch together solutions that would otherwise have been ignored because they would have required upfront purchasing of expensive licenses for development tools and environments, specific libraries and software components. Open source is a very effective way to ride the IoT wave at high speed while keeping the risks and costs to do so under control.

Cisco's global cloud projections may blow your mind

Annual global cloud IP traffic is expected to reach 8.6 ZB by the end of 2019, up from 2.1 ZB per year in 2014. In an interesting glimpse into how new technologies are helping drive efficiencies in spite of this massive increase in traffic, networking technologies such as SDN and NFV are expected to streamline data center traffic flows such that the traffic volumes reaching the highest tier (core) of the data center may fall below 10.4 ZB per year, and lower data center tiers could carry over 40 ZB of traffic per year. In terms of how this traffic looks on a regional basis, perhaps unsurprisingly North America will have the highest cloud traffic volume (3.6 ZB) by 2019, followed by Asia Pacific (2.3 ZB) and Western Europe (1.5 ZB). North America will also have the highest data center traffic volume (4.5 ZB) by 2019, followed by Asia Pacific (2.7 ZB) and Western Europe (1.8 ZB).

What makes a great company? Let’s talk information flow

The flow of information between employees is important across all levels and titles. Too often, executive teams hold intelligence close to their chest in fear of having competitive knowledge or financial earnings exposed outside of the company. We want to lead by example — and transparency and trust are huge components. With that goal in mind, we host a Datameer Radio session each month so everyone can get an update on the company and participate in a candid Q&A with the executive team. We’ve found that not only do our employees respect the confidentiality of the information that is shared, but also knowing what is going on strengthens their commitment to being a part of helping us grow. It’s clear that the workplace is in need of disruption with new models of motivation to drive inspiration and enhance well-being.

Internet Of Things Extends Business' Ability To Sense And Respond

Call it fallout from the Google effect, he explains. “One of the things that Google and search has done for us is it has infinitely expanded the capacity of the human memory,” says Hoover. “I don’t have to memorize all the facts in the world. I can go out and look them up and find it if I want to learn about reinforcement learning. It’s expanded my brain, my memory to nearly infinite capacity.” By analogy, the billions of sensors across the planet is expanding our awareness of our surrounding. The Internet of Things is “about Googling reality,” Hoover explains. “I see things, I hear things, I sense the world around me. To sense something at the time it occurs, it no longer has to be near my body. I want to understand the state of pollution in Beijing; I go and find it on the internet.

Dutch government says no to 'encryption backdoors'

The Netherlands began reviewing its policies after the recent Paris terrorist attacks. But this week it said "restrictive" measures would put citizens at risk. Encryption is a way of protecting communications or data so that it is incomprehensible without the correct passcode or key. Advocates say it protects users by preventing criminals and spies from prying into private conversations. But security agencies have said they struggled to bypass encrypted messaging platforms used by groups such as so-called Islamic State to plan attacks. "We are not some kind of maniacs who are ideologues against encryption," FBI director James Comey said in November: "But we have a problem that encryption is crashing into public safety and we have to figure out, as people who care about both, how to resolve it."

Big Data Security and Compliance Issues in the Cloud

It’s a quandary. Businesses want to be able to conduct deep, flexible analytics on complete data sets. That’s the essence of big data. You don’t want to omit any data that might contribute to finding business-facing insights. You want the cloud for flexibility and economics. But, you also don’t want to run afoul of compliance regimens or increase your exposure to security risks. What can you do? Don’t worry. As I said, it can be worked out. Getting on top of public cloud big data security and compliance challenges takes effort on two fronts. First, there has to be a coherent, disciplined set of data governance policies at work in the cloud. Platforms also matter. The two work together, with the platform enabling the definition and enforcement of governance policies.

Symantec Adds Deep Learning to Anti-Malware Tools to Detect Zero-Days

Until recently, deep learning has been locked away in the software development labs. A few companies have realized that they can spot malware by its components and its behavior to ferret out most zero-day attacks before they have a chance to cause damage. Because of this, deep learning is now being deployed on the cyber-security battleground. ... Symantec has their sights set on bigger goals in the enterprise. The next target will be enterprise email, especially cloud-based email. "We process a lot of the world's email," Gardner said. "A lot of attacks enter the enterprise through email. They're insidious." He said that by attacking company email systems, cyber-criminals are able to seize critical information and, in addition, able to steal a lot of money through phishing schemes that install malware on company networks.

The DIFA Framework for evaluating data science projects

A situation that many CIOs or data science departments will face today is that the list of possible analytics projects is sheer endless. The range of project candidates usually begins with analyzing customers and ends somewhere at utilizing social media data. Needless to say that not all project candidates will make sense from a business and especially ROI perspective. Also, some projects will run into dead ends because some fundamental bits turn out to be missing. Even though experimentation and some vagueness about eventual monetary success in the context of data science projects is normal, there are some hard facts that heavily influence the success of a data science project. These facts are structured in the DIFA framework which is explained below.

Tracking Cloud Services: An Essential Security Step

Not knowing who's responsible within an enterprise for managing cloud serviceclouds contracts could result in the inventorying of cloud services falling through the cracks. "The decentralized procurement model of cloud creates situations where individuals and business units may use a cloud service outside of the purview of the central IT organization," says Jim Reavis, CEO of the Cloud Security Alliance, a not-for-profit that promotes use of cloud security best practices. Confusion about who is responsible for cloud services contracts within the enterprise could lead to the failure to inventory each agreement. "Organizations fail to inventory their cloud services and other cloud-accessible devices because they fail to appreciate that cloud computing is not a technology decision," says Kevin Jackson, founder of the cloud computing consultancy GovCloud Network.

How Digital Disruptors use Data Science

Digital disruptors are fast and relentless. They are constantly releasing new functionality. They try things - they experiment. In order to do this, digital disruptors need a feedback loop. They use the data from their customers’ use of their product to get fast and accurate feedback on how these products are being used. Lets look at examples of how they do this using data science. On race days, Nascar analyses all the tweets and fan site activity relating to the race. It uses data science to bucket this human interaction data into topics, and for each topic it automatically determines sentiment. It then addresses any concerns thru information on its fan site, information at the event, or feeds to it broadcast partner, Fox Broadcasting.

Quote for the day:

Technological change is not additive; it's ecological. A new technology does not merely add something; it changes everything. -- Neil Postman

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