The choice of a network technology depends largely on the geographical range to be covered. When data have to be transferred over short distances (for example, inside a room), devices can use wireless personal area network (PAN) technologies such as Bluetooth and ZigBee as well as wired connections through technologies such as Universal Serial Bus (USB). When data have to be transferred over a relatively bigger area such as an office, devices could use local area network (LAN) technologies. Examples of wired LAN technologies include Ethernet and fiber optics. Wireless LAN networks include technologies such as Wi-Fi.
The new unified architecture is being billed as the first ever designed to bridge traditional and cloud-native applications into fluid resource pools that can be deployed at "cloud speed." That could eliminate the big advantage that Amazon Web Services has had over internal IT departments that have struggled to provision workloads instantly like AWS can. At the heart of the Synergy infrastructure, which will be available starting in the second quarter next year, is a set of open APIs that bring software intelligence to deploying workloads based on the business demands of the application. Hence the term "composable" infrastructure.
While autonomous business will enrich our lives, it also raises concerns about the impact on human employment. As with all technologies there will be an impact as it replaces jobs in some areas, and creates new jobs in others. However, the elimination of all, or most, employees is not a plausible scenario for most organizations in the future. “The dehumanized organization may be efficient, but it will fail to foster the emotional loyalty that characterizes the most successful organizations of our time,” Mr. Prentice said. “It’s likely that the role of humans will shift to less routine work that requires creativity and emotional intelligence, or involves complex motor skills that machines struggle to master.”
CIOs are in a race to redefine the role of IT in an era of digital transformation. While this change occurs, it is important to remain clear that the perception of business benefit is a primary reference point against which IT is evaluated. In other words, corporate functions and lines of business expect IT to deliver practical and useful benefit. Given the importance of business perceptions toward IT and the CIO, it is worthwhile to examine data on this topic. Unfortunately, the results clearly show that IT must improve its image and reputation as a provider of business value. While looking at the data, one surprising trend emerged. Although the CIO and folks in IT view themselves positively, the self-perception of IT is still extremely low. Self-loathing in IT seems to be a reality, unfortunately.
“That was considered to be a bit too negative. So I’ve changed it to ‘stairway to heaven,'” said Waite, a Gartner analyst, at the research shop’s 2015Catalyst convention in San Diego. “Anyway, my points are exactly the same.” The truth is, Waite said, public cloud providers like Amazon Web Services and Microsoft Azure can host most everything far more efficiently than you can — no matter what size organization you run. So before anything else, think carefully about your data and whether it needs to be in a private cloud. When you’re crystal-clear on that, start climbing the stairway. Here are Waite’s milestones on the way to private cloud success.
Conventional BI analytics can’t give you those answers to help optimize distribution and merchandizing. You need real-time analytics that can examine millions of questions, build hundreds of models and help you understand the subtle differences. Conventional prediction models take too long to manually craft and update. If your predictive modeling takes a month to complete and mine takes a day, I could decide based on the latest data possible, while you are deciding based on months-old data. And, since we know that consumer behavior is fickle, every extra day of data matters. When a model can be created, updated and acted upon faster—in days or hours, not weeks or months, you end up acting based on more current data.
... many of these regs and rules were pre-mobile, pre-eCommerce, pre-Internet. Because many of the fintech models are introducing innovative and new methods of delivering financial services, it can create confusion on the applicability of which regs/rules apply. ... the number of fintech startups has increased significantly as more investment dollars have poured into this sector. Venture investing in fintech has gone up approximately three times in the past 18-24 months, so the sheer number of new startups in this sector has created more regulatory concerns. ... there has been a lot of new financial services regulation introduced in recent years such as Dodd-Frank, the Foreign Account Tax Compliance Act, Durbin amendment and other new regs and even banks are challenged with keeping up with all the new regulations that they need to be in compliance with.
In addition to machine learning, Jain is interested in the growing IoT market. "Making smart watches, and buildings, and all kinds of little things is really going to be very helpful—not just as a business, but I think in our daily work lives these things are going to make a big difference," she said. When asked for her thoughts on some of the biggest issues affecting enterprise IT, Jain said it's a matter of relevant information. Even with advances in technology, finding information on the internet is still easier than finding information within an organization, she said. We have some of the technology available, but it has to be secure and properly managed because of the sensitive nature of enterprise data.
It all means that organizations deal with more complex problems in a rapidly changing environment. It demands intelligence and mobility. This leads to so many changes within the organizations! Command and control barely work for intelligent people, so you have to invent new ways. ... The company strategy can't be created by a single person, since he or she doesn't know everything, it should emerge from successful initiatives at the lowest levels. Flatness is just one characteristic of a “new generation” companies. It helps to make decisions faster, run more experiments, fail faster and find new solutions faster. The truth is that we don't have proven best practices how to create flat organizations and what "new generation" means in general. We have just some working examples and many critique quarrels.
At the time, the IT team was struggling with its own legacy, homemade system and teams had to wait in line for their data extractions. Those needing more data had to wait again, causing a bottleneck in the IT department. "The systems were not agile and queries were slow to be resolved," she says. Frustrated, it was this experience as a young, female controller who had to "wrestle with an all-male IT department over unfettered access to fresh data" that led her to start her own business. "I had to do something to modernise business intelligence and create the product of my dreams," she says. What she was about to learn, and fast, was that her struggle lay not just in being a woman in a male-dominated industry, but it was also because her vision of business intelligence as a service ran against the grain.
Quote for the day:
"None of my inventions came by accident. I see a worthwhile need to be met and I make trial after trial." -- Thomas Edison