Daily Tech Digest - June 06, 2018

Avoid these digital transformation false starts

Avoid these digital transformation false starts
Discussing “bi-modal IT” or “run the business vs. grow the business” may actually jeopardize your digital transformation. “By segregating legacy technologies from next-gen solutions, you are labeling one team as the past and another as the future,” says Lee. “When you identify one set of technologies — and one team — as something to get rid of, not only do you hurt the morale of half of your team, but you fail to innovate at the very foundation of your transformation. It’s not just customer-centric mobile apps that deserve innovation.” ... “There needs to be a collective agreement of whether your role is to transform the very foundations of your business or deliver new capabilities that the business will choose if and how to adopt,” says Lee. “You need to understand those expectations, especially when you are new to the company.” ... “The stakes of traditional IT disciplines: stability, security, software quality, and capacity are magnified during a digital transformation,” says Lee. “Those basics are only getting more important as your digital transformation takes technology closer to the customer and the core of what your company does.”

Blockchain’s Role in Securing Data Privacy

Blockchains make it easier to trace data, but they don’t enable you to control the flow of data once you’ve given away access. Since blockchains exist on a distributed network, there’s no central authority to stop someone from sharing the data you just shared. Blockchain doesn’t solve the issue of data leaks and re-sharing sensitive data. It only makes those leaks easier to trace. There’s still a need for privacy tools that encrypt and create access controls on blockchain data. A hybrid approach of a private, closed blockchain along with custom-developed privacy solutions may prove to be the best bet to gain the benefits of blockchain without losing the control of more centralised systems. draglet, a German blockchain development company, works in this field of private blockchain development, amongst other blockchain projects. With the right customisation, private blockchains could provide an easy to audit, low-risk way to store and manage customer data without sacrificing data controls. Additionally, smart contracts written on the blockchain could automate much of the access controls, sharing agreements, and data management tasks. 

Unpacking the event-driven microservices approach

When you use microservices with CEP outputs, you should think in terms of API managers, brokers and service buses. In this situation, microservices are invoked like service-oriented architecture or REST components in order for the developers to know the message formats needed, the nature of stateless or stateful processing and the way that microservices are sequenced along the workflows. Traditional programming practices that optimize the reuse of the smaller components can be effective here. Component reuse is an explicit benefit for microservices, and it has to be addressed in your design. Component reuse is facilitated by the fact that the sizing, in the functional terms of a microservice, used behind a CEP front end is almost totally controlled by the development team. Microservices with larger functional scopes aren't easily reused but are more efficient because there are fewer network paths to transit. Noncontextualized events are usually processed by microservices, lambdas or functional components. They are then orchestrated in an orderly way by a separate component; this is referred to as orchestration, workflow engine or step function.

Most businesses still struggling with mobile working and security

mobile working security
Fifty-three percent cited that one of their top three biggest problems with remote working is due to the complexity and management of the technology that employees need and use. Over half (54%) say that while their organisation’s mobile workers are willing to comply with requests relating to security measures, employees lack the necessary skills or technologies required to keep data safe. Nearly a third (29%) take the radical approach of physically blocking all removable media, and a further 22% ask employees not to use removable media although they have no technology to enforce this. “The number of organisations blocking removable media has increased compared with responses to the same question in 2017, when 18% said they were physically blocking all removable devices. A unilateral ban is not the solution and ignores the problem altogether whilst presenting a barrier to effective working. Instead, businesses should identify corporately approved, hardware encrypted devices that are only provided to staff with a justified business case. The approved devices should then be whitelisted on the IT infrastructure, blocking access to all non-approved media.” said Jon Fielding, Managing Director, EMEA, Apricorn.

What is TensorFlow? The machine learning library explained

What is TensorFlow? The deep learning library explained
The single biggest benefit TensorFlow provides for machine learning development is abstraction. Instead of dealing with the nitty-gritty details of implementing algorithms, or figuring out proper ways to hitch the output of one function to the input of another, the developer can focus on the overall logic of the application. TensorFlow takes care of the details behind the scenes. TensorFlow offers additional conveniences for developers who need to debug and gain introspection into TensorFlow apps. The eager execution mode lets you evaluate and modify each graph operation separately and transparently, instead of constructing the entire graph as a single opaque object and evaluating it all at once. The TensorBoard visualization suite lets you inspect and profile the way graphs run by way of an interactive, web-based dashboard. And of course TensorFlow gains many advantages from the backing of an A-list commercial outfit in Google. Google has not only fueled the rapid pace of development behind the project, but created many significant offerings around TensorFlow that make it easier to deploy and easier to use: the above-mentioned TPU silicon for accelerated performance in Google’s cloud

Now that everything can be tokenized, banks are taking notice

Now that everything can be tokenized, banks are taking notice
The key, according to Krauwer, is to further shape this future vision and learn how individuals can benefit from such a proposition. Even though the realization of a bank managing customers’ immaterial assets may still be far away, it’s not science fiction either, she states. “The past couple of years, individuals have become more and more empowered to get the most out of their assets,” Krauwer added. “Whether you make extra money by renting out your house through Airbnb or get free clothing by promoting a brand through your Instagram account, there’s no denying that a whole new economy has emerged with significantly lower entry barriers than in the pre-platform era.” ... One example is social network Earn.com, which allows its members to earn tokens whenever they respond to a message from a fellow community member. Yet, with an array of opportunities coming to the fore, a solution may be called upon that enables a person to get the most out of their assets with the least amount of friction involved that still maintains a person’s privacy.

Machine Learning in Finance – Present and Future Applications

Machine Learning in Finance - Present and Future Applications
Combine more accessible computing power, internet becoming more commonly used, and an increasing amount of valuable company data being stored online, and you have a “perfect storm” for data security risk. While previous financial fraud detection systems depended heavily on complex and robust sets of rules, modern fraud detection goes beyond following a checklist of risk factors – it actively learns and calibrates to new potential (or real) security threats. This is the place of machine learning in finance for fraud – but the same principles hold true for other data security problems. Using machine learning, systems can detect unique activities or behaviors (“anomalies”) and flag them for security teams. The challenge for these systems is to avoid false-positives – situations where “risks” are flagged that were never risks in the first place. Here at TechEmergence we’ve interviewed half a dozen fraud and security AI executives, all of whom seem convinced that given the incalculably high number of ways that security can be breached, genuinely “learning” systems will be a necessity in the five to ten years ahead.

Boards not asking right security questions

Harding said the second lesson relates to the fact that the most difficult decision throughout the cyber breach was deciding when to bring its customer-facing systems back online. “My question to the engineers was: What risks will we be taking if we put those systems back online? I realised that we could only go ahead when the cyber risk was lower than the business risk of being offline and that cyber risk needs to be a board decision,” she said. The third important lesson, said Harding, was that engineers really can communicate in English when they have to. “We learned that when engineers explain what they do in a way that non-technical people understand, that is when the magic really happens,” she said. In conclusion, Harding said it is extremely important that cyber security is not allowed to become a scary taboo. “We can’t make the digital world 100% safe, but we can make it civilised by building the necessary social, moral and legal scaffolding by having the right debates as a society to agree and set the rules of the road,” she said.

Embracing agile software methodologies to improve workflows

It is also important to keep a sustainable pace. While agility is the goal in these types of software development environments, the most efficient and effective method for creating software is keeping a realistic timetable. Having bouts of productivity is actually counter to the process. A steady, consistent pace is of the utmost importance. In order to keep pace, you will need to have consistent meetings with your team. Daily meetings, or scrum meetings, are the goal for software development teams in an agile environment. In these daily meetings software developers, engineers, and business people outside of the technical team go over all that has been accomplished and all that will be accomplished in the 24 hours to come. These daily meetings are structured around larger timetables. These time periods are punctuated with certain goals and usually last around 30 days. At the end of this 30 day period is when big reviews happen of the software product, major revisions are proposed, and timetables are revised.

Recruiting talent for digital cultures: Tips from McKinsey, Korn Ferry

When searching for digital talent, the wrong people are often the right people, said Swift, global leader for digital solutions at the global consulting firm Korn Ferry Hay Group. It's a conundrum her group takes pains to explain to clients seeking advice on creating digital cultures. "We actually do an exercise with executives where we have them list all the reasons they might not hire somebody," she said, citing as an example a common red flag -- the "jumpy resume." Prospective employees with a history of moving from job to job are often dismissed as bad bets, she said, but great digital candidates often do just that. "So, instead of saying, 'Well this person can't commit and they're flaky'," Korn Ferry asks clients to consider an alternative: i.e., "that this person is curious and adaptable, which are two of the traits in our research by the way that pop as being very predictive of success in digital talent," Swift said. But Swift warned it "takes a massive effort for some of these large organizations to say, 'OK, I'm not going to hire in my own image anymore" and practice what she calls reverse onboarding.

Quote for the day:

"It is amazing what you can accomplish if you do not care who gets the credit." -- Harry S. Truman

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