Todd Charron has been a speaker at numerous conferences, is the lead mentor for Lean Startup Machine Toronto and is the founder of Follow Your Fear Day. Todd combines his background in Improv with over 15 years of experience in the software industry as a Developer, Manager, Agile Coach, and Lean Startup Mentor to help organizations and teams be bolder and more creative. ... Todd Charron argues that for success it is necessary to go beyond a change of processes and tools, to change how people in an organization see themselves and their role in it.
One error organizations used to make when implementing hybrid cloud architecture, said David Linthicum, a consultant at Cloud Technology Partners Inc. and author of numerous books on IT, started with OpenStack. IT organizations use the open source cloud software platform to build a private cloud, which offers advantages similar to public cloud but uses in-house architecture. It's a perfectly reasonable endeavor, except many organizations didn't fully understand what they're getting into. "It was too much of an engineering challenge for them to take on, and they ended up going over budget or just abandoning it quickly," Linthicum said. The problem for many was that they believed the hype on private cloud as a bulletproof and easy-to-implement alternative to public cloud, Linthicum said, citing 2013 as the banner year for vendor bunk.
We've all seen plenty of comedy -- or tragedy -- result when two people who don't speak the same language attempt to converse. Even when they do, misinterpretations and misperceptions abound, and our workplaces prove it. Job interviews and talks with recruiters are even more susceptible to these roadblocks, since they occur between people who probably don't know each other and don't have similar pasts (professional or personal), and when one party (you) is in the especially tense situation of seeking new employment. A review of best practices in recruiting and interviewing reveals that listening, defined as a means to this end, has finally earned a spot in the curriculum on how to ace this critical skill. Start by being careful. Instruction on listening typically centers on the ability to reflect feeling or paraphrase feedback.
Thanks to broadband, web browsers, and the cloud, we now do everything over the Internet. With Chromebooks, Google has shown us that we don't need local programs at all. It's not just Google, a company born of the Web. Microsoft, which made its billions from the standalone PC, is now moving its fortunes to cloud-based applications such as Office 365. Today, our friends and office mates are scattered around the globe, but they're only a keystroke away on social networks, VoIP, or videoconferencing. Unless you're working at Yahoo, you can pretty much work anywhere in the world. Thanks to the rise of smartphones and tablets, we're no longer even tied to desktops or laptops. So long as you have power and Wi-Fi, there's nowhere you can't work or play. And, it all goes back to the Web.
Of course, something needs to take its place. But instead of the customer-hostile, Mordac-the-Preventer-of-IT-Services, consider the "us means all of us, not just IT" model of digital services. Digital services will necessarily be a huge change. We'll need our organization's best technologists. We'll need great communicators, awesome project managers, fantastic marketing pros, skilled negotiators, and the cream of our data scientists. Sure, we'll need security and infrastructure folks, but a lot fewer of them (read: the collaborative, friendly ones), because we'll standardize and be using lots of pay-as-you-go cloud services for maximum flexibility. We can't have control freaks. No sociopaths are allowed who think that technology is only for technologists.
The speed of digital transformation and short life-cycles of device and services is increasing the importance and pressure on quality assurance testing. Additional conclusions highlights that a seamless customer experience is a key driver for QA testing, the shorter lifecycles demand greater agility and new roles are being created to meet testing demand. ... Key recommendations from this year’s report: Refocus QA and Testing on customer experience and business assurance; Transform the traditional Test Center of Excellence (TCOE) using agile and DevOps practices; Make continuous and automated security testing a key strategy; Prioritize testing with predictive analytics and continuous feedback; and Expand testing teams’ skills beyond manual and test automation.
One of the first problems confronting any IoT developer is the industry's distinct lack of standards. In a report, McKinsey & Co. notes that "Interoperability between IoT systems is critical," but goes on to lament the mishmash of conflicting "standards" that plague IoT's market potential. As I've suggested, though vendors dominate the more than 400 competing standards, the battle for developer hearts is more likely going to be won by de facto open source standards. Even so, the problems with IoT development don't end there. More unfortunate still, IoT development can appear deceptively simple, as Cohen stresses:
Safe Harbor's failure will have a minimal effect at the high level. The groups responsible for dealing with organizations that do not follow data security and management procedures are the same ones that can't reach agreement on a new Safe Harbor. Organizations compliant to the requirements of the old Safe Harbor are unlikely to be taken to court, as the countries that drew up the EU Directive 95/46/EC on the protection of personal data agreed that Safe Harbor was compatible with the directive. If an international data protection trial does arise, pointing out that your organization is compliant with current laws in place should be a clincher.
Before we talk about technical challenges, I would like to point out the difference between two classes of analytic workloads that often get grouped under “streaming” or “real-time analytics”. The first and perhaps more challenging workload deals with analytics at large scale on stored data but where new data may be coming in very fast, in micro-batches. In this workload, challenges are twofold – the first challenge is about reducing the latency between ingest and analysis, in other words, ensuring that data can be made available for analysis soon after it arrives, and the second challenge is about offering rich, fast analytics on the entire data set, not just the latest batch.
“The biggest and most universal problem [with information sharing] is that trust tends to happen between individuals, and not between organizations,” says Wendy Nather, R-CISC research director. “When we talk to people, we find that they already have information sharing going on – it’s just with individuals that they trust. Getting them to shift that trust to an organizational relationship and keeping that going when the original person moves on (which happens a lot in security) is the biggest challenge.” R-CISC already has about 50 corporate members, and some of them come from outside the retail industry, Nather says. Oil and gas companies have joined the retail group, for instance, because most gas stations also operate convenience stores.
Quote for the day:
"A culture of discipline is not a principle of business; it is a principle of greatness." -- Jim Collins