Daily Tech Digest - April 14, 2019

Ten big global challenges technology could solve


Renewable energy sources like wind and solar are becoming cheap and more widely deployed, but they don’t generate electricity when the sun’s not shining or wind isn’t blowing. That limits how much power these sources can supply, and how quickly we can move away from steady sources like coal and natural gas. The cost of building enough batteries to back up entire grids for the days when renewable generation flags would be astronomical. Various scientists and startups are working to develop cheaper forms of grid-scale storage that can last for longer periods, including flow batteries or tanks of molten salt. ... Pandemic flu is rare but deadly. At least 50 million people died in the 1918 pandemic of H1N1 flu. More recently, about a million people died in the 1957-’58 and 1968 pandemics, while something like half a million died in a 2009 recurrence of H1N1. The recent death tolls are lower in part because the viruses were milder strains. We might not be so lucky next time—a particularly potent strain of the virus could replicate too quickly for any tailor-made vaccine to effectively fight it.



Being an effective cybersecurity leader amid increasing pressure, expectations and threats

Being an effective cybersecurity leader means helping your staff avoid the burnout, guilt, and depression that comes from not getting the headcount needed, the funding for the new project, or worse yet, experiencing a data breach when the inevitable comes to pass. To lead effectively, you as a leader need to employ the principle of ensuring informed decisions happen and residual risk is accounted for and governed. The business doesn’t have to invest in every security solution available (in fact, doing so may impede their ability to effectively operate), so long as you have appropriately informed stakeholders of the bad outcomes that could come to pass from not choosing the more secure option, and having them accept the risk associated with such bad outcomes. Risk acceptance is the cybersecurity leader’s “get out of jail free” card – not in an “I told you so” way, but in a cooperative manner that helps the business view you as a partner, not an impediment, and the cybersecurity staff feel as though their concerns have been addressed.


Taking Sustainability a step further – Marginal Gains


Virtualisation and containerisation is the first step, but they talked in terms of using the whole chain of IT as a process with software defined architecture. You should be paying only for what you use, what you need. Interestingly, with their Greenlake product, that extends the OpEx pay-as-you-go consumption-based approach to on-premise hardware. That, in turn, extends HPE’s hybrid-cloud credentials and means better cashflow for their customers, and the ability to manage the peaks more easily. Capacity on demand in your data centre, as well as the public cloud. This approach to infrastructure goes hand in hand with the shift in focus of data and processing moving to the edge, where we need solutions that provide compute power at or near the source of where the data is generated by a mobile device, a machine on the shop floor or a sensor. This is vital for supporting IoT, for the requirements of autonomous vehicles in the field, or the needs of the smart city. Gartner predicts that 75% of data will computed at the edge rather than in the data centre by 2025, and maybe it’s coming even sooner than that!


Q&A on the Book What’s Your Digital Business Model

The first type of disruption happens when a new entrant—often a start-up like Airbnb—comes into an existing market and offers an exciting new value proposition. In banking, for instance, fin-tech start-ups have gone after profitable parts of banking’s business, like payments and loans. The second form of disruption comes from a traditional competitor within your industry, but that organization changes its business model to become a much more formidable competitor. For example, Nordstrom has evolved from a traditional department store into an attractive omni-channel business, combining the best of place and space. In our research we see industries like banking, insurance, retail and energy companies trying to find the perfect mix of place and space. The third form of disruption involved crossing industry boundaries. It’s what happens when challengers come from completely outside of your industry. For instance, Australian supermarket chain Coles has started selling home insurance, as well as offering other financial services.


6 Innovative Cities Encouraging Tech Innovation

cities
As of March, Shanghai became the world’s first district to use both 5G and a broadband gigabit network. Shanghai’s vice mayor Wu Qing made the network’s first 5G video call using a Huawei Mate X smartphone, which is the company’s first 5G foldable phone. The city’s ambitious project, which aims to build over 10,000 5G base stations by the end of the year, is backed by state run telco China Mobile. Shanghai has been dubbed ‘China’s Silicon Valley’, and is home to the likes of Tencent, Huawei and ZTE. Another recent development is the creation of the Shanghai Technology Innovation Board, created by the government to discover and nurture promising companies in a bid to compete with US tech giants. ... Otherwise known as the Motor City, Detroit has become almost synonymous with mobility solutions. The city is following in the footsteps of other US cities by taking its existing network of automakers and facilitating work on innovative travel and transport. Ford and General Motors are just two of the auto giants based in Detroit, both of which are steering towards autonomous vehicles. In 2015, the Mayor’s Office of International Affairs was created to attract foreign investment and nurture homegrown startups.


The Connection Between Strategy And Enterprise Architecture

Business capabilities are the link connecting the strategy and business model to the enterprise architecture and the underlying technology that executes the strategy. Understanding this link enables a company to align resources, people, and processes to transform itself in response to market dynamics, thereby maintaining a competitive edge. ... A business model is a description of how an enterprise creates and captures value. It describes the customer value proposition. How the company will organize its resources and partner network to produce that value. And how it will structure its revenue streams and cost structure to fund the operations and capture value to its stakeholders. An organization can be described through the nine elements or building blocks of the business model canvas. The business model canvas helps you describe, map, discuss, design, and invent new business models.



Codementor, a startup that connects developers with questions to developers with answers, has attempted to narrow those choices down by creating a list of the worst languages to learn. The 'worst-to-best' ranking creates scores using community engagement, growth, and the job market to determine the list.  Last year the company ruled that Dart, Objective-C, CoffeeScript, Lua, and Erlang were the top five languages not worth learning. This year Codementor focused on "which languages you probably should not learn as a first programming language". For this reason, it excluded the top three most popular languages, including JavaScript, Python, and Java.  The company's data suggests the languages to not bother learning this year are Elm, CoffeeScript, Erlang, and Perl.  Somewhat surprisingly, Kotlin, a popular language for building Android apps, rose from 18th to 11th place on Codementor's worst-to-best list. Microsoft-owned code-hosting site GitHub crowned it the fastest-growing language of 2018 due to the massive growth in projects written in Kotlin.


What Does It Mean To Be A Data-Driven Enterprise Today?

It’s no secret that AI and machine learning have become the top wish-list items among CIOs and CEOs. However, the real potential of AI can be reached only if your organization’s data, which AI relies on, is accurate and business-relevant. You need to trust the source of the data being used to feed AI programs, and the data must be governed properly across the organization. This fundamental piece of the AI and machine-learning puzzle is critical for allowing AI and machine-learning technologies to “learn” how to evolve intelligence and make smarter recommendations for the business. It is also based on the premise that knowledge from the past and present must be preserved, as it ensures valuable reuse and time to market. We’ve seen many examples of CEOs struggling to understand which versions of their data are accurate due to poor data quality and governance. These companies need to establish a trusted source from which their data is managed through best-practice, automated governance, including standardizing data definitions and rules – part numbers, terminology, and so on. 


Enterprise vs. Solution vs. Infrastructure: Understanding the Different Technology Architectures

Enterprise vs. Solution vs. Infrastructure: Understanding the Different Technology Architectures
Enterprise architecture (EA) aligns your organization's IT infrastructure with your overall business goals. It shows you how your technology, information, and business flow together to achieve goals. EA allows for analysis, design, planning, and implementation at an enterprise level. It perceives industry trends and navigates disruptions using a specific set of principles known as enterprise architectural planning (EAP). ... Solution architecture (SA) describes the architecture of a technological solution. It uses different perspectives including information, technical, and business. It also considers the solution from the point of EA. Enterprise architects are best known for taking the "50,000-foot view" of a project. A solutions architect zones in on the details.  ... Infrastructure architecture refers to the sum of the company's hardware and IT capability. Achieving synergy between all the devices is its overarching goal. In the past, infrastructure architecture was the focal point for security. Today, it goes further. It's a structured approach for modeling an enterprise's hardware elements.


Riding the K-wave: Disruptive innovation in the age of sustainability

Disruptive innovation happens more than we realize, and a good question is why we’re routinely late to realize its effects. Schumpeter got some of his insights from the work of a Russian economist, Nicolai Kondratiev, who was an advisor to Vladimir Lenin. Kondratiev’s job was explaining capitalism to the Bolsheviks. During Lenin’s life, Kondratiev had a respected position in academic economics; when Stalin came to power after Lenin’s death, Kondratiev’s theories didn’t fit Stalin’s world view and he was liquidated. Kondratiev observed that really big disruptive innovations begin a 50- to 60-year economic cycle that Schumpeter later called K-waves in his honor. The idea of a K-wave is simple: For the first 25 to 30 years after its introduction, a technological disruption expands the economy, creating jobs and whole industries as massive amounts of capital flow into that new industry. The reason for expansion is simple. Very often a disruption is in high demand, but it requires some form of construction to diffuse the innovation throughout society.



Quote for the day:


"Leaders know the importance of having someone in their lives who will unfailingly and fearlessly tell them the truth." -- Warren G. Bennis


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