Having the final user in mind is the first skill of a good developer. Make sure you know the problems of your end users. Make sure to know their needs. Then develop the product that solves their problems and fills their needs. Software development is all about that. The second skill concerns the quality of what you deliver. Delivering with zero defects is a skill. Obviously, it is hard to reach — but it’s not impossible. ... The third skill is about simplicity and not fearing inherent and accidental complexity. This skill is about decomposition and abstraction: your ability to break down complex systems/problems into smaller ones, contrast those smaller parts to make them independent, and organise those smaller parts to make them understandable at the right level of abstraction
For Sinclair, the leadership training has had as much, if not more, of an impact than the technical training. “I’ve grown tremendously working under Mr. Loveless and Ms. Longs, as well as others, but definitely my leadership skills have grown tremendously,” he says. “The first day I started, I would’ve been scared to read a report in front of my parents. But now, I can give a speech on the spot to a room of 50 people, confidently, that I don’t even know.” If Prince George’s County’s approach to internship and young professional training in IT pays off in the long run, it can hopefully shift perceptions about the county and get young people to realize that they don’t have to move to Silicon Valley or Manhattan to do challenging and rewarding IT work.
Oliver’s fake printer, which he calls the Stealth Cell Tower, could potentially eavesdrop on the voice calls and SMS messages of any phone that’s fooled into automatically connecting to it. Since it sits indoors near its victims, Oliver says it can easily overpower the signal of real, outdoor cell towers. But instead of spying, the printer merely starts a text message conversation with the phone, pretending to be an unidentified contact with a generic message like “Come over when you’re ready,” or the more playful “I’m printing the details for you now.” If the confused victim writes back, the printer spits out their response on paper as a creepy proof of concept. It’s also programmed to make calls to connected phones and, if the owner answers, to play an mp3 of the Stevie Wonder song “I Just Called to Say I Love You.”
It can be difficult to retrofit governance into existing systems. Often, the focus is on the initial data migration to the new operational application or analytics, where a simple bulk data loader is employed in the interest of speed and agility. ... Once the new applications have gone live, focus shifts to ensuring data consistency. Moving between cloud and on-premise systems and cloud-to-cloud brings new challenges, and leave fewer resources dedicated to overall data management. If you don’t want to slow down the business initiatives that are driving the new applications, but still want to prevent that data complexity or chaos, it will pay to have a data management architecture and best practices in place before-hand.
Enterprise mobility continues to serve as a driving force in boosting company productivity and flexibility. The ubiquity of mobile devices ensures that the business apps running on them can reach large-scale audiences and address an array of organizational needs. This driving force will only increase as wearables and the Internet of Things (IoT) become more mainstream. It's a common trend now for employees to choose the business apps they feel best meet their needs, and this in turn challenges enterprises to produce mobile apps to solve these needs. With that trend in mind, Adobe conducted a recent survey to examine the state of mobile apps in the enterprise, with a focus on the opportunities for organizations seeking to leverage apps to stoke productivity and remain competitive.
Many of us in Information Governance already know plenty about this group because we’re part of them! Like it or not, most organizations consider that Information Governance comes under the purview of the Information Technology. The one thing that many Information Governance professionals fail to understand is that the job of Information Technology is to keep the computers running. They are mechanics, highly skilled and very adaptive, but they want to solve problems and keep the trains running. They can find new software, add new servers to solve business issues, and implement it faster than you can keep up with. The best way to solve this is to get involved! Do what you can to become an active part of your organization’s procurement process.
Many alarms have sounded on the potential for artificial intelligence (AI) technologies to upend the workforce, especially for easy-to-automate jobs. But managers at all levels will have to adapt to the world of smart machines. The fact is, artificial intelligence will soon be able to do the administrative tasks that consume much of managers’ time faster, better, and at a lower cost. How can managers — from the front lines to the C-suite — thrive in the age of AI? To find out, we surveyed 1,770 managers from 14 countries and interviewed 37 executives in charge of digital transformation at their organizations. Using this data, we identified five practices that successful managers will need to master.
"I describe it as the extinction phase," said Stephen Bird, Citigroup's CEO of global consumer banking, to Fortune.com in June. "What happens in an extinction phase is that you either rapidly adapt and new means of competition are created, or you go extinct.""The future of banking is about focusing on advisory and consultation rather than transactions," said Baxter. "We need to take cost out of the middle and back office of doing simple repetitive rules transactions and move those people into other roles." Citibank plans to do this by retraining their employees through a range of educational classes to help them expand their skill sets to be more relevant as the bank expands the remits of its staple employees.
Current funding for smart city initiatives is only good enough for proof-of-concept trials, which would lead, at best, to a piecemeal approach to smart city construction. The reluctance is understandable — Songdo cost roughly $35 billion to build from scratch — but without genuine investment in changing the infrastructure of a city to fit smart city needs, widespread deployment will be riddled with integration and adoption issues. Maybe the biggest obstacle to its full deployment is one question: Are smart cities profitable? There have been compelling waste-reduction efforts based on smart city sensor technology, like using sensors in the water supply to mitigate waste. While these efforts have resulted in corking budget leaks, they haven’t appeared to bleed over into other aspects of smart city deployments.
“Most of the time and effort of building machine learning systems goes into configuring them, collecting these massive amounts of data that these algorithms need, doing feature engineering, extracting the features that you need, tuning that, and then running it through machine learning, then doing the verification, using tools to make sure that you’re managing all these resources that you have. “The hard part of this is really all the other stuff that goes around it, not necessarily running the algorithm. So how do we democratize this?” The company first released the Open Source TensorFrames - a software library that enables the Google’s Tensorflow deep learning framework to run on Spark – in March.
Quote for the day:
"Beginnings are scary, endings are usually sad, but it's the middle that counts the most." -- Birdee Pruitt