April 23, 2016

How IoT security can benefit from machine learning

“Machine learning is a critical component to developing Artificial Intelligence for IoT security,” says Uday Veeramachaneni, co-founder and CEO at PatternEx. “The problem is that the IoT’s will be distributed massively and if there is an attack you have to react in real-time.” Most systems relying on machine learning and behavior analysis will gather information about the network and connected devices and subsequently seek everything that is out of normal. The problem with this primitive method is that it produces too many false alarms and false positives. The approach suggested by PatternEx is to develop a solution that incorporates machine learning and augments it with human analyst insight for greater attack detection.


Blockchain - Legal and regulatory issues around distributed ledger technology

As with any potentially transformative new technology, distributed ledgers raise a number of questions for policy makers and regulators at both national and international levels. Regulators are certainly closely analysing and monitoring distributed ledger developments and, for now, appear cautiously optimistic about its potential, especially because of the potential that distributed ledgers could actually help to improve regulatory compliance tracking and reporting. But, guess what?: most authorities are taking a "wait and see" approach. Blockchain and distributed ledger technology is not without its challenges, including scalability and latency, lack of mainstream understanding, lack of readiness in some sectors to rely exclusively on data in digital form, over-reliance on out-dated legacy systems which would need to be overhauled before distributed ledger technology could be implemented.


What can a toothbrush instruct us about IoT business styles?

Let’s make a Bluetooth-related toothbrush that comes with a smartphone app. Now the “smart” toothbrush helps Oral-B do a improved task in protecting dental well being by “focusing, tracking, motivating and sensing”. The toothbrush is smarter, but the business product is not. The related solution supposedly generates extra worth for buyers, but all the other things of the business product continue being the same. The worth is nevertheless shipped by way of a toothbrush unit, captured by sales by way of retail channels access to the retail shelf-room is nevertheless the essential competitive edge. Not a great deal business product innovation here. ... Sceptics, of course, will ask, “Who wants builders to extend the toothbrush?” But moms of youthful kids will see a sea of opportunity here


EU charges Google with foisting its search and browser on smartphone makers

This is the second set of charges against Google by the commission. On April 15 last year, it announced a “statement of objections” against the search giant in an investigation into charges that its Internet search in Europe favored its own comparison shopping product. The commission announced on the same day an investigation into Google’s conduct with regard to the Android operating system that would look, among other things, into whether Google had illegally hindered the development and market access of rival mobile applications or services by requiring or providing incentives to smartphone and tablet manufacturers to exclusively pre-install Google’s own applications or services.


10 Important Predictions for the Future of IoT

"A recurring theme in the IoT space is the immaturity of technologies and services and of the vendors providing them. Architecting for this immaturity and managing the risk it creates will be a key challenge for organizations exploiting the IoT. In many technology areas, lack of skills will also pose significant challenges." In the coming years, IoT will look completely different than it does today. IoT is a greenfield market. New players, with new business models, approaches, and solutions, can appear out of nowhere and overtake incumbents. But business is the key market. While there is talk about wearable devices and connected homes, the real value and immediate market for IoT is with businesses and enterprises.


A digital crack in banking’s business model

Across the emerging fintech landscape, the customers most susceptible to cherry-picking are millennials, small businesses, and the underbanked—three segments particularly sensitive to costs and to the enhanced consumer experience that digital delivery and distribution afford. For instance, Alipay, the Chinese payments service (a unit of e-commerce giant Alibaba), makes online finance simpler and more intuitive by turning savings strategies into a game and comparing users’ returns with those of others. It also makes peer-to-peer transfers fun by adding voice messages and emoticons. From an incumbent’s perspective, emerging fintechs in corporate and investment banking (including asset and cash management) appear to be less disruptive than retail innovators are.


When Does Deep Learning Work Better Than SVMs or Random Forests?

Random forests may require more data but they almost always come up with a pretty robust model. And deep learning algorithms... well, they require "relatively" large datasets to work well, and you also need the infrastructure to train them in reasonable time. Also, deep learning algorithms require much more experience: Setting up a neural network using deep learning algorithms is much more tedious than using an off-the-shelf classifiers such as random forests and SVMs. On the other hand, deep learning really shines when it comes to complex problems such as image classification, natural language processing, and speech recognition. Another advantage is that you have to worry less about the feature engineering part.


Digital data and the fine line between you and your government

The question before consumers and the courts today is three-fold: What kinds of valuabledata is the IoT generating; who should have access to and control over that data; and who can be legally compelled to share that information with law enforcement. In the recent Apple encryption case, the FBI went directly to the manufacturer of a product to gain access to digitized information residing on that device. In our digitally connected future before us, will law enforcement simply bypass end users like you and me and compel companies to turn on our Nest cameras, unlock our August Smart Locks or tune in to our Echos? The Apple encryption case and its predecessors have broad implications for the entire tech community — not just those building smartphones and running data centers. The way in which we’ll interact with technology in the future has been turned on its head.


Build Your Own Container Using Less than 100 Lines of Go

To really understand what a container is in the world of software, we need to understand what goes into making one. And that's what this article is explains. In the process we’ll talk about containers vs containerisation, linux containers (including namespaces, cgroups and layered filesystems), then we’ll walk through some code to build a simple container from scratch, and finally talk about what this all really means. ... Caching is what makes Docker images so much more effective than vmdks or vagrantfiles. It lets us ship the deltas over some common base images rather than moving whole images around. It means we can afford to ship the entire environment from one place to another. It’s why when you `docker run whatever` it starts close to immediately even though whatever described the entirety of an operating system image.


Ransomware, Everywhere: What’s The Science Behind It?

Money isn’t just a motive; money is the enabler. Cybercriminals whose crimes make money can invest in new attacks, invest in defeating countermeasures, and invest in developing new targets. Until recently, attacks on critical infrastructure and the Internet of Things have also been rarely-realized theoretical concerns. There are many hackers who would think that bringing down a power station with a cyberattack is cool, but making that happen would require a group effort to build the necessary hacker tool chain. Ransomware delivers both the motive and the resources to make that happen. And once that ransomware-funded tool chain exists, it will be launched for many other purposes, ranging from idle curiosity to political vengeance.



Quote for the day:


"If a cluttered desk is a sign of a cluttered mind, of what, then, is an empty desk a sign of?" -- Albert Einstein


April 22, 2016

The 4 Stages of Better Technology Adoption

Every business is at a different stage in their technology evolution. For some, they’re just starting to see that the break-fix relationship with their provider isn’t serving them properly. For others, they have a fully integrated technology strategy, but need a way to take it to the next level. So often we discuss topics that involve technology innovation without paying as much attention to topics that cater to the initial stages of businesses improving technology. This is important because a small business owners need to understand how they can improve and innovate their technology just as much as a more sophisticated business that is farther along in their technology process. Here are the four stages of better technology adoption to help you get a better idea of where you stand and what the next steps might be for you to innovate your technology at a pace that’s right for you.


How to be More Productive as a Data Scientist

Greater productivity can be gained beyond avoiding unnecessary repeated tasks. The cloud has become an indispensable tool for all sorts of businesses and industries, with one of its greatest strengths being increased productivity. This holds true for a field as complex and new as data science. Various cloud services and tools have been developed designed to help data scientists conduct their analyses, clean data, and visualize their results. With the cloud, data scientists can perform their duties from nearly anywhere while having access to vast stores of data they would otherwise not be able to use. Many productivity tips are much simpler than using cloud services or getting rid of unhealthy iterations.


Why enterprise developers could save Windows 10 Mobile

Microsoft is well aware of its market share problem and the related shortage of quality mobile apps, of course, and it purchased Xamarin in February to make it simpler, and thus cheaper, for Windows developers to port their desktop applications to iOS, Android or Windows 10 Mobile. "This is not for people who write iOS or Android apps, but if you are a corporate Windows developer and you have held back on mobile applications, now you have the possibility of building your applications for third party mobile platforms," according to Wes Miller, an analyst at Directions on Microsoft, who spoke with CIO.com last month.  Windows no longer rules the business software world unchallenged, but a huge install base of Microsoft applications still exists within in midsize and large businesses.


The tech industry’s “diversity” focus favors one group over pretty much any other

Rarely, though, will you ever hear white people lamenting about working conditions that their black or brown children, spouses and siblings might have to endure. They rarely have those relationships, so they aren’t forced to develop empathy for brown and black people. Colorless diversity is okay with spending tens of millions of dollars on conferences, summits, retreats, and outreach for and about white women, but finds it distasteful when others point out the disparity in spending for people of color. Colorless diversity would have black and brown people sit down and wait their turn. Let me be clear: I’m not writing this because I think it’s bad that companies are spending money on diversity programs for women. These programs are necessary.


The Era of the Intelligent Cloud Has Arrived

The more enterprises seek out insights to drive greater business outcomes, the more it becomes evident the era of the Intelligent Cloud has arrived. C-level execs are looking to scale beyond descriptive analytics that defines past performance patterns. What many are after is an entirely new level of insights that are prescriptive and cognitive. Getting greater insight that leads to more favorable business outcomes is what the Intelligent Cloud is all about. The following Intelligent Cloud Maturity Model summarizes the maturity levels of enterprises attempting to gain greater insights and drive more profitable business outcomes. Line-of-business leaders across all industries want more from their cloud apps than they are getting today.


Microsoft’s Nadella taps potential of industrial internet of things

With more of the value in industrial products shifting from hardware to software, it is no surprise that many industrial companies are reconsidering their software strategies. According to GE, the industrial internet as a whole will be a $225bn market in terms of annual revenues by 2020 — dwarfing the expected $170bn for the consumer internet of things, which has attracted more public attention, and bigger even than the enterprise cloud computing market which is predicted to hit $206bn. Of the new industrial software market, GE estimates that some $100bn will go to a small handful of companies that provide the central platforms for the industrial internet — the software that collects and aggregates data, acts as the foundation for higher-level applications and creates shop windows for developers to reach an audience in the industrial world


Why HTC may be the next Motorola of Android

HTC's been moving in the right direction for a while now, with an impressive and ever-improving focus on overall user experience and post-sales support. It's been climbing higher every year on my Android upgrade report card and this year came in with stronger scores than ever -- an 86% overall, following only Google's Nexus devices in terms of all-around upgrade reliability.  HTC may earn its profits from hardware sales like everyone else, but where it differs is that it actually seems to place value on positive long-term relationships with the people who buy its devices. ... It's not just timely upgrades that make HTC the new consumer-friendly king of Android manufacturers: It's things like stepping up and answering my call for a guaranteed two full years of upgrades for flagship phones, long before any other manufacturer was willing to make such a commitment.


9 Free Windows Apps That Can Solve Wi-Fi Woes

As we all know, life isn't quite that easy. Your home or office network can have dead spots where devices can't seem to connect, or where the connections get slow or flaky. Public hotspots can make you prey for hackers and snoopers. And when you are at a hotspot, you might need to share your connection with your other devices, including smartphones and tablets. While there is no way to immediately solve all the problems associated with wireless connectivity, there are applications that can make things better -- and many of them are free. I've rounded up nine free pieces of Windows software that can go a long way toward helping you solve your Wi-Fi issues at home, in your office or on the go.


Google's problem with the cloud is that it's too innovative and not practical enough

Google practically invented the cloud, yet struggles to translate its benefits to more earth-bound enterprises. Even at GCP Next, which was essentially an enterprise love-in, Google couldn't help but tout its science fiction bona fides. Sure, Google started well. Chairman Eric Schmidt intoned that "Cloud is about automating the tedious details and empowering people." Tedious...enterprise...so far, so good! But then, Google started into machine learning, an area where it's heads and shoulders above its competition, with Google senior fellow Jeff Dean telling the crowd, "Machine learning is one of the most important topics in computing." The company went on to blog that "now any application can take advantage of the same deep learning techniques that power many of Google's services."


SEC Warns More Cyber Enforcement Actions Coming

"Cyber is obviously a focus of ours, as I know it is for the other divisions, and we've brought a number of cases there relating to Reg S-P and failure to have policies and procedures relating to safeguarding information," Ceresney said, citing the case the commission brought against R.T. Jones, a St. Louis-based RIA, this past summer. "There'll be others coming down the pike," Ceresney cautioned. The SEC is reviewing the cybersecurity policies in place at advisors and broker-dealers. Separately, the commission has been shifting exam personnel from the BD side of the Office of Compliance Inspections and Examinations to the unit that oversees RIAs. But even with those moves, commission officials acknowledge that they can't keep up with the rapid growth of the RIA sector. The SEC is only able to examine about 10% of registered advisors in a given year



Quote for the day:


"The older I get the less I listen to what people say and the more I look at what they do." — -- Andrew Carnegie


April 21, 2016

Why Machine Learning Is The New BI

Whether it’s IoT, big data or analytics, companies have a lot more data to base their decisions on, and data-driven decision making sounds obvious. And the next step beyond data-driven decisions is decision support systems and even automation. Are we ready for intelligent assistants with business advice? While a recent study of 50,000 American manufacturing organizations found that the use of data-driven decisions had almost tripled between 2005 and 2010, that was still only 30 percent of plants. And when telecom provider Colt surveyed senior IT leaders in Europe in 2015, 71 percent of them said intuition and personal experience works better for making decisions than using data (even though 76 percent of them say their intuition doesn’t always match the data they get).


Fintech explosion demands joint effort on oversight, report says

“There is an urgent need both for the private sector and financial supervisors to collaborate,” the group said in the report, whose contributors include investment bank executives, international economists and entrepreneurs from Asia, the U.K. and the U.S. The forum’s aim is “to foster competition between traditional financial players and new entrants while also preserving system stability,” it said. Fintech was a central theme this year at the group’s annual meeting in Davos, Switzerland, and the report draws on discussions that took place there. It incorporates views of members including executives from UBS Group AG, Deutsche Bank AG and JPMorgan Chase & Co.; tech firms such as IEX Group Inc. and On Deck Capital Inc.; and regulators including the U.S. Securities and Exchange Commission and the Bank of England.


How to create a strategic analytics culture in your organization

One of the real values of utilizing data is that it can uncover questions or ideas that aren't currently being considered in your organization. A data science team will need specific tasks to accomplish, but they also need a certain degree of autonomy to explore the data and experiment with it. "If you want to build a culture, set them free," Davis said. Change is hard, especially in a large organization with many moving parts. As someone arguing for an analytics culture, you are a change agent, and you have to determine how resistant to, or accepting of, change your organization is. Try asking yourself the following questions:


Back to the future: It's all about appliances again

While that converged infrastructure move flies in the face of the promise of our server-less future, Sangster posits that the value that converged infrastructure delivers -- by taking a group of technologies that can be difficult to use on their own (much less together) and combining them into a prescriptive, pre-integrated solution -- is eternally attractive. Sangster points out that OpenStack has, until recently, been viewed as software for innovators and early adopters. This is the realm of proud DIYers blazing the trail ahead. They love to experiment, doing all the hardware and software engineering possible as they work to understand, implement and eventually deploy a new system like OpenStack. This is, of course, fun for the tinkerers, but unhelpful for the mainstream organizations that simply want to use a solution. For those folks, converged infrastructure makes sense.


The bots are coming … but they are not taking over.

The magic sauce in the march of the bots is in the deep background: the democratization and implementation of artificial intelligence systems on a large scale. Millions of software developers build interesting products and systems across the world every day. But only a handful of computer engineers know how to actually build, train and deploy advanced computing functions like machine learning, computer vision or neural networks. The companies and organizations that know how to do such things are incredibly limited: Facebook, Google, Microsoft, IBM, Oracle (to a certain extent), think tanks and university research departments like MIT, Stanford and Carnegie Mellon. The average software developer writing JavaScript Web apps probably doesn’t know the first thing about how to build artificially intelligent systems.


Is Mobile Commerce Growth Really Happening?

The shift from e-commerce to m-commerce happened quite rapidly, too rapidly for many retailers actually. Another new paradigm in 2016 is the move from shopping in mobile browsers to shopping in mobile apps. A combination of well-designed mobile apps with good UI, enhanced smartphone capabilities, push notifications, and new mobile payment tools have led to an explosion in mobile shopping. This also brought a new agenda in sales (retail) strategies for businesses to keep customers engaged and retain to come back. ... Mobile apps play a vital role in mobile commerce growth, but still struggle. 85% of mobile time is spent in apps, which is obviously stunning. On the other hand, most of the app time is solely spent in an individual’s top 3 apps. While mobile web drives double the traffic of apps across industries.


Whaling Emerges As Major Cybersecurity Threat

Vendors such as Microsoft, Proofpoint, Cloudmark and Mimecast are building tools to help companies defend against these attack. Mimecast, which makes cloud software designed to spot and quarantine phishing emails with malicious attachments and URLs, has just launched a tool designed to harpoon whaling. Called Impersonation Protect, the software's algorithms analyze the language content of emails as they come in through a corporate server. It looks for key indicators, beginning with whether the source name actually works for the company. The software will then parse the email content for requests that includes keywords and phrases such as "W2" or "wire transfer," and provides a probability score that a target email is either safe or malicious. "One indicator in isolation is not bad, but two together could be fishy," Malone says.


Dear CISOs and Legal Counsel: We Can’t Wait for the Privacy Regulators

The Issue is Clear: Why Should Anyone Trust Anyone? We could leave this issue to privacy officers, internal and external legal counsel, governments, data protection authorities, politicians, regulators, and technology companies to sort out. We could wait for the ultimate answer to solve the privacy question once and for all. And wait. And wait some more. And wait for another review, debate, newsworthy event (such as needing information from another critical terrorist phone). Or wait for the next cloud service to be hacked, exposing photos that violate an individual’s right to privacy. The reality is we just don’t trust each other—person to person or country to country. The reality is also, we have to trust each other at some level to interact personally or conduct business with each other.


Better Web Testing With Selenium

WebDriver has a few different ways to temporarily pause a script in the middle of a run. The easiest, and worst way, is an explicit wait. This is when you tell the script to hang out for some amount of time, maybe 15 seconds. Explicit waits hide real problems. A lot of the time, we see the wait fail and bump the time up a few more seconds in hopes that it will work next time. Eventually we have padded enough time in the script so that the page loads completely before trying to perform the next step. But, how long is too long? These explicit waits can conceal performance problems if we aren’t careful. The smarter way to handle waits is to base them on the specific element you want to use next. WebDriver calls these explicit waits. I have had the most luck in improving stability of a check by stacking explicit waits.


Lambda Functions versus Infrastructure - Are we Trading Apples for Oranges?

Some refer to this as stateless computing or serverless computing. Personally I prefer the second term, as there is clearly a state somewhere-probably in a database service that the function may leverage— but the function itself is essentially stateless. The same argument could be held against the serverless term, clearly there are servers floating around in the cloudy background but their existence is implicit and automatic rather than explicit and manual. The next area of value in AWS Lambda stems from the ability to easily associate your function with all manner of triggers via both web-based and command line tools. There are more than 20 different triggers that can be used—most of them being from other AWS services such as S3, Kinesis and DynamoDB.



Quote for the day:


"Problems are only opportunities in work clothes." -- Henry Kaiser,


April 20, 2016

Making the case for in-house data centers

Leasing data center capacity to another organization is another way for an internal data center to add value. “Our Texas data center has over thirty thousand square feet available which could be developed. We are exploring the possibility of leasing this capacity to another organization,” Connor says. The potential leasing arrangement would be with a single organization which would partner with BlueCross on data center design. If research and development is a priority for the organization, a specialized in house data center makes sense. In 2014, Cambridge University built the West Cambridge data center facility. The data center has delivered cost savings in the form of lower power consumption. Scientific research in chemistry, physics and other departments have increasingly decided to adopt the central data center rather than departmental resources.


European Commission formally objects to Google’s Android dominance

The EC said pre-installing and setting Google as the default, or exclusive, search service on most Android devices sold in Europe, closed off ways for rival search engines to access the market, via competing mobile browsers and operating systems. ... The EC said Google’s actions also harmed consumers by stifling competition and restricting innovation in the wider mobile space. As an example, it said Google's conduct has had a direct impact on consumers, as it has denied them access to innovative smart mobile devices based on alternative, potentially superior, versions of the Android operating system.


Leadership is more powerful than technology

One thing that's interesting is that everyone always asks, 'Well, what happened to your tech and can't you use it?' It's like, 'Well, no. ... The key is to remember always that a lot of [management] stuff comes directly from the candidates themselves. Even though, you know, Barack Obama didn't come to me and say, 'Harper, here is what you should build.' Barack Obama found people that would represent [what he wanted], and it trickled down to me. The candidate determines how software will be built, and what it will do because they choose to organize all these other things. That's how tech works. If the candidate is a terrible person, probably their technology is going to be [supported by] terrible people. That doesn't mean it's going to fail. Those are not related.


Don’t overlook SaaS, the original cloud option

There are often better SaaS alternatives -- not only cheaper, but with better capabilities and better workflows -- for internal applications. And not Salesforce alone. There are SaaS-based HR systems such as the popular Workday, as well as accounting, manufacturing, learning, project management, and even office automation. By my count, there are more than 2,000 SaaS offerings, ranging from niche applications to integrated ERP and CRM systems. Perhaps because SaaS is now 15 years old, IT has stopped thinking about it as cloud -- they confine the term's use to newer offerings like IaaS and PaaS. But SaaS is the original cloud, and it represents the largest part of the cloud market.


Brexit won’t exempt you from new EU data protection obligations

In the long term, the economic argument for the UK adopting the GDPR if we leave – or, indeed, implementing even more stringent measures that would satisfy the Regulation’s data protection requirements – is strong: according to the Office for National Statistics, e-commerce accounted for 20% of UK business turnover in 2014. And, as think tank Chatham House pointed out only last month, “data sharing has an impact on all business with the EU (both online and offline), valued at 45 per cent of UK exports and 53 per cent of UK imports.” In still-straitened economic times, that value is obviously something the Exchequer will be keen preserve.


How compliance can be an excuse to shun the cloud

"When you break down the problem it only governs a specific piece or component of data and only those apps," he says. "They aren't breaking down the problem and laying out the workloads and data sets."  As it turns out, the excuses for not embracing the cloud are numerous. One cause is generational. People have been running internal data centers for decades. Good luck convincing a CIO in his or her 50s who fears being cut out of a job in the first place that data and applications should be moved off-site into a data center somewhere across the country. ... The problem is also dependent on the size of the company. Small firms without a dedicated IT staff can be more reticent because they don't have someone who is fully dedicated to understanding computing services and products, said James Gast


Next up in smart devices: The Internet of shirts and shoes

IoT startup Evrythng is teaming up with packaging company Avery Dennison to give apparel and footwear products unique identities in Evrythng’s software right when they’re manufactured. The companies have high hopes for the Janela Smart Products Platform, seeing a potential to reach 10 billion products in the next three years. The system could put a simple form of IoT into the hands of millions of consumers who weren’t even shopping for technology. Evrythng and Avery Dennison don’t want to make your clothes into online celebrities, they want to make them more useful. What they’re doing may make it harder to counterfeit desirable products and commit fraud at the returns counter. There could be some fun features for consumers, too.


Free Up IT Infrastructure Costs to Fund Transformation

Though few near-term opportunities for savings may be apparent, I&O provides plenty of longer-term room if you‘re willing to address cost optimization with careful scrutiny of every asset. “The most important thing is to make sure you have a strategy in place,” said Ms. Caminos. “Then you can look at cost savings, starting with some areas that will give you some quick wins depending on your existing environment.” Consider each of the four major technology domains that make up I&O: data centre, networking, client computing and service desk. Then evaluate the most impactful methods for reducing costs and prioritise your initiatives. It’s important to understand the total cost of ownership (TCO) for each of these functional areas.


Insurance Giant John Hancock Begins Blockchain Tech Tests

While the company isn’t sharing details around its proofs-of-concept, earlier this year ‘Big Four’ accounting firm Ernst & Young published a report listing peer-to-peer insurance and faster distribution of “regionalized or personalized” products among its list of opportunities for insurers using blockchain. Other possible applications according to the report include fraud detection through creating a decentralized repository of customer information and policies; digital claims management through providing historical third-party transaction data; types of distribution using micro-insurance and micro-finance; and new kinds of products around "cyber liability" for security professionals. But, not all considerations mentioned in the report were positive.


Companies high on virtualization despite fears of security breaches

Adding to the confusion, virtualization has caused a shift in IT responsibilities in many organizations, says Greg Young, research vice president at Gartner. The data center usually includes teams trained in network and server ops, but virtualization projects are typically being led by the server team. “The network security issues are things they haven’t had to deal with before,” Young says. The average cost to remediate a data breach in a virtualized environment tops $800,000, according to Kapersky Labs, and remediation costs bring the average closer to $1 million – nearly double the cost of a physical infrastructure attack. Companies don’t see technology as the sole answer to these security problems just yet, according to the HyTrust survey.



Quote for the day:


"Products are made in the factory, but brands are created in the mind." -- Walter Landor


April 12, 2016

The Future of Economics May Be in the Hands of Machine Learning

Historically, the discipline of economics has always been categorized among the social sciences, which means the word ‘science’ should be understood as somewhat loosely applied. Unlike the natural sciences, which are prescribed as strictly positivist and bound by the ideals of empirical truth to only build theories around quantitative data that can be measured and duplicated, social sciences are often influenced by observations that are open to interpretation. In social sciences, research models can be eclectic, built from combination of qualitative and quantitative data. And conclusions drawn from models like that are prone to the influence of bias and personal ideologies. Not that hard sciences can’t also be prone to bias and ideology. It’s just that the whole point of the strict empirical research model is to limit the potential for bias and interpretive ambiguity.


Collaboration Technology Fuels Innovation for States and Localities

Collaboration forms the cornerstone of the innovative work conducted at the North Carolina Innovation Center, which is run by the state’s Department of Information Technology (DIT). The iCenter both showcases collaborative workspace options and technologies and puts them to work helping the departments the DIT serves. “When Governor Pat McCrory first envisioned the iCenter, it was primarily about creating a culture of collaboration throughout the state to better serve citizens,” says North Carolina CIO Keith Werner. The agency has been fortunate to work with partners to demo equipment and furniture without burdening taxpayers, he adds. Determined to run lean, DIT took advantage of existing resources on both the personnel and the facility side.


From tech supplier to IT service provider, a CIO makes the 'big switch'

"IT is not just an enabler of certain processes but part of the delivery of every product and service we offer," Watkins said. Indeed, the company itself was undergoing a transformation, Watkins said. KAR no longer wanted to be a car auction company that uses technology but "a technology company that sells cars," he said. IT had not kept up with the vision. "With the convergence of these technologies, business demand skyrocketed and created a wide gap between business expectations and IT delivery. Something had to switch," Watkins said. ... "We need our staff to be agents of change. The status quo doesn't get it done. We have to look at things differently. We have to be problem solvers. We have to bridge siloes between IT and operations, between one IT team and another IT team, and between being a technology provider and being a service organization," he said.


Windows XP still powers 181 million PCs two years after support ends

Even though Microsoft retired Windows XP two years ago, an estimated 181 million PCs around the world ran the crippled operating system last month, according to data from a web metrics vendor. Windows XP exited public support on April 8, 2014, amid some panic on the part of corporations that had not yet purged their environments of the 2001 OS. Unless companies paid for custom support, their PCs running XP received no security updates after that date. Consumers were completely cut off from patches, with no alternatives other than to switch to a newer operating system or continue running an insecure machine. But two years after XP’s support demise, nearly 11% of all personal computers continue to run the OS, data for March from U.S.-based analytics vendor Net Applications showed.


The digital effect on the BPM lifecycle

The shift from traditional to digital business goes well beyond incremental improvement. In metaphorical terms, moving from the railroad to the automobile would be incremental change; the transition from traditional to digital business would be more like moving from the automobile to the space shuttle, i.e. whole new game, new players, new rules, new stakeholders, and importantly, new risks and new rewards. ... It is a marvelous instantiation of the chicken and the egg: does the business enable the technology or does the technology enable the business? I will, for now, be comfortable with the simple answer: YES. Let the philosophers amongst us continue to impress their cocktail party friends with the more verbose answers and profound wisdom that can only be found in the third glass of wine.


DataStax believes multi-model databases are the future

DataStax added to its own multi-model capabilities with the announcement of DataStax Enterprise (DSE) Graph, a scaled-out graph database built for cloud applications that need to manage highly connected data. Graph databases are a specialized form of NoSQL database intended to address relational data, but in a much more efficient and scale-out manner. "Graph is an excellent method of evaluating, expressing and analyzing previously unrecognized relationships in data," Gartner's Heudecker and fellow analyst Mark Beyer wrote in their July 2015 report, Making Big Data Normal with Graph Analytics. "Instead of examining and analyzing data as a set of discrete and unrelated atomic elements, graph allows for the exploration of the frequency, strength and direction of relationships in data."


Security researchers defeat reCAPTCHA

The system uses techniques to bypass CAPTCHA security measures such as tokens and cookies as well as machine learning to correctly guess images presented to it. The researchers said the system they had devised was “extremely effective”, automatically solving 70.78 percent of the image reCaptcha challenges, while requiring only 19 seconds per challenge. The trio also applied this attack to the Facebook image captcha and achieved an accuracy of 83.5 percent. The researchers said that the enhanced accuracy of the attack system on Facebook's security was down to the higher-resolution images it used. Google's lower resolution images make it difficult for the automated system to classify images.


Top 5 misconceptions about Big Data

The business opportunities for big data can be significant. One of the more straightforward examples which didn’t involve any exotic new practices or people is Guess Inc. They were able to re-engineer their data pipeline to completely transform the experience of managing their retail stores. In the old world the store managers had a weekly printed report. In the new world they have real-time, dynamic information about their store, their customers, and brand & loyalty programs. So Guess was able to overhaul the process of decision-making. If they’d just focused on doing more of the same, this wouldn’t have happened. ... Some organizations are large enough to bear the cost of being Hadoop experts. Many aren’t. And the degree of expertise required for the care and feeding of Hadoop is highly dependent on how it’s being used.


Why Solving Problems Always Leads to More Problems, and How to Stop the Madness

A problem, once solved, merely restores the status quo. Solving it gets you back to where you were before the problem arose, but brings no lasting difference to the situation. A staff member quits, we recruit a new one, and now we're right back where we were. The customer gets angry, we send them flowers and give them a credit, and we're back on an even keel with them. But nothing has changed. An obstacle, when solved, measurably changes the situation, or even the business as a whole; things are never the same again after we solve it. And because we solved the obstacle, it dramatically reduces the number of problems we will have going forward. That's one way you know you're solving obstacles, because the number of related problems are permanently reduced.


Claire Agutter on IT Service Management and Future Practices

ITSM is defined as an organization’s capabilities to deliver IT services that support the business. It can include people, processes, tools, suppliers…pretty much anything that makes up an IT service. For example, think about your own organization without email, remote working, printing etc. How would it look? IT service management has been developing as long as IT and technology itself. Because IT services support business processes, they need to be dependable, reliable and do the job they are meant to do. If IT is failing, the business suffers. Not many businesses can cope with paper and pens now. Many organizations realized quickly that IT needed to be governed for them to get value.



Quote for the day:


"Obstacles are those frightful things you see when you take your eyes off your goal." -- Henry Ford