Why You Should Consider A Career In Data Science.
Another thing that makes data science so popular is that it accepts people of
all sorts, regardless of their background and domain. People in literally any
industry can move into data science and still do amazing work in their
industry with the help of data science. People from the banking and finance
industry, food and health sector, arts, climate science, engineering, and
physics can all couple their domain knowledge and expertise with data science
and make ground-breaking progress. You do not necessarily need to have a BSc
or MSc in computer science or engineering in order to start a career in data
science but rather couple data science with whatever career you currently
have, find a problem you can solve with the combination of both and do
something. Data science in combination with Artificial Intelligence, Machine
Learning, Robotics, and the Internet of Things has the power to literally
automate anything in order to make lives easy. Automation of tasks can also
bring huge progress to companies since work can now be done faster. Also, when
work is done by humans, there is a natural tendency to be inconsistent and
make human-related errors. Automating tasks handles these problems and gives
us better results in a shorter time.
Top CEOs Agree That Culture Is The Key Before, During And After Crisis
“The One Carnegie approach, starting with myself and our executive team, really means coming together around common values. It doesn’t matter the country, language, race or religion, we wanted people to come together around our strong values. Just like Dale Carnegie would say, ‘Try honestly to see things from the other person’s point of view.’ “The essence is that we want to value each person as an individual and as part of an organization. People value transparency and openness. When the pandemic hit, our One Carnegie foundation helped us tremendously. From a cultural standpoint, there was transparency, and we communicated very clearly what was happening and how we were responding to it. We shifted our entire global in-person training business to live online trainer delivery, and this could not have happened without a culture of working together and moving fast. Our strong culture created alignment in all 86 countries. People felt safe asking questions and working together. The results we are seeing are extraordinary.” CEO Gary Terrinoni of Brooklyn Hospital, founded in 1839 and cited as the number one safety net hospital in America, shared, “We had to move people around to be able to support the issues that we had with COVID-19, and people just stepped up.What to look for when modernizing the Data Lake
Whether a company is born into the digital world or has a more traditional
business, they must invest and excel in tech advances such as mobility, cloud
computing, and most importantly, advancedanalytics and data science. Doing so
will equip them with the right tools to innovate their existing operations and
deliver a seamless experience to customers. However, it isn’t that easy to
achieve this goal. To realize the benefits of advances in technologies,
organizations must leverage all their data. This requires modernizing their
data architectures. In other words, organizations must unlock andmigratetheir
data from multiple, heterogeneous systems including legacy mainframe systems
and enterprise applications, and quickly process and refine it for consumption
in AI and ML initiatives. Modern, cloud-based data lakes provide enterprises
the agility and flexibility they need to store and process massive volumes of
diverse data. Things to keep in mind when architecting a modern data lake.
Data architectures are constantly evolving. Companies are adding new sources
of data, offloading data to new target systems for processing and refining,
and adding new analytical tools and solutions to their technology
infrastructure.
If software architects' soft skills fail, so does the business
The history of software development contains rich lessons, both good and
bad. We assume that current capabilities (like elastic scale) just appeared
one day because of some clever developer, but those ideas were often born of
hard lessons. Pets.com represents an early example of hard lessons learned.
Pets.com appeared in the early days of the internet, hoping to become the
Amazon.com of pet supplies. Fortunately, they had a brilliant marketing
department, which invented a compelling mascot: a sock puppet with a
microphone that said irreverent things. The mascot became a superstar,
appearing in public at parades and national sporting
events. Unfortunately, management at Pets.com apparently spent all the
money on the mascot, not on infrastructure. Once orders started pouring in,
they weren't prepared. The website was slow, transactions were lost,
deliveries delayed, and so on … pretty much the worst-case scenario. So bad,
in fact, that the business closed shortly after its disastrous Christmas
rush, selling the only remaining valuable asset (the mascot) to a
competitor. What the company needed was elastic scale: the ability to spin
up more instances of resources, as needed.
Successful innovation doesn’t have to be disruptive—it’s often small, incremental, and fast
The tension between breakthrough and incremental approaches can be found in
most settings, not just online businesses. For example, medicine has had a
long tradition of searching for interventions that have transformative
outcomes on patients. But perhaps, as surgeon and researcher Atul Gawande
argues, success “is not about episodic, momentary victories, though they do
play a role. It is about the longer view of incremental steps that produce
sustained progress.” That, Gawande continues, “is what making a difference
really looks like. In fact, it is what making a difference looks like in a
range of endeavors.” One endeavor, manufacturing, has known and practiced this
approach for decades. In Toyota’s renowned production system, for example,
real-time experiments by its factory workers to eradicate problems are an
integral part of its continuous improvement system. Even there, people are
expected to form clearly articulated, testable hypotheses and explain their
logic for each attempted improvement. Of course, breakthrough and disruptive
innovation will continue to play an important role in driving growth, as there
are limits to incremental approaches.
Determining and overcoming blockchain fatigue
“Blockchain fatigue sets in mainly due to the fact that not many people fully
understand what this technology offers and so have difficulties trying to
implement it into their business or process. This lack of understanding can
lead to frustration and consequently a dwindling enthusiasm for the
technology. “While still in its infancy, blockchain is perhaps stretching the
patience of those who were initially overly optimistic about the technology.
The continued lack of full-scale implementation of blockchain is creating this
sense of fatigue as there are still no end-to-end fully deployable solutions
available for enterprises. “Most of the work still focuses on small pilot
projects and this, coupled with technology immaturity, lack of standards and a
general misunderstanding of how blockchain technology works and what it
offers, is also contributing to the market feeling fatigued with blockchain.”
While usage of blockchain within various sectors continues to grow and develop
beyond its best known function within cryptocurrencies, a recent study from
Deloitte shows that a rising number of senior executives and practitioners
worldwide are seeing the technology as overhyped, with 55% stating this in
2020. With this in mind, what must organisations do to overcome blockchain
fatigue and continue to keep faith?
How Quantum Mechanics will Change the Tech Industry
In a digital computer, the system requires bits to increase its processing
power. Thus, in order to double the processing power, you would simply double
the amount of bits — this is not at all similar in quantum computers. A
quantum computer uses qubits, the basic unit of quantum information, to
provide processing capabilities unmatched even by the world’s most powerful
supercomputers. How? Superposed qubits can simultaneously tackle a number of
potential outcomes (or states, to be more consistent with our previous
segments). In comparison, a digital computer can only crunch through one
calculation at a time. Furthermore, through entanglement, we are able to
exponentially amplify the power of a quantum computer, particularly when
comparing this to the efficiency of traditional bits in a digital machine. To
visualise the scale, consider the sheer amount of processing power each qubit
provides, and now double it. But there’s a catch — even the slightest
vibrations and temperature changes, referred to by scientists as “noise”, can
cause quantum properties to decay and eventually, disappear altogether. While
you can’t observe this in real time, what you will experience is a
computational error.
Remote work is the new normal. But the tech problems won't go away
Once the technical issues are overcome, there is much to be gained from an
off-premise workforce. Employees themselves seem to draw a better work-life
balance out of telecommuting; in fact, three-quarters of UK employees have
reported not wanting to go back to the office full-time. Half of the business
leaders surveyed by Riverbed named a better work-life balance as a bottom-line
benefit for their employees as a result of remote working. An equal proportion
of respondents also mentioned savings from office space, and 43% said that
they expected flexible working to increase productivity. "In a year's time, I
believe the biggest difference to everyday work will be that people will be
much more available, without all of the complications and logistics that we
have always known, and this will make them more efficient and productive,"
says Bombagi. Since the start of the crisis, he has noticed that he can fit in
up to eight virtual customer meetings on a given day, where he could
previously only do two, and only if they were both based in London. His
working day used to be planned around logistics: "If I'm going to be on the
Tube, I know I can't make a call. If I'm driving somewhere, I can make a call,
but I can't do a presentation. If I'm on a plane, apart from some email, I
can't really do anything," says Bombagi.
Quantum Computing: Looking Ahead To Endless Possibilities
It’s a strange behavior of quantum mechanics whereby the more complex the
calculation is, the more impressive the algorithm becomes. Sometimes the
result of square root acceleration is trumped by completing calculations in a
logarithm of the time — so exponentially faster. Essentially, unlike the
computers we know and use, it’s not a simulation or manufactured programmatic
function that’s doing the calculating — it’s the quantum world, which needs to
be maintained at almost absolute zero temperature with no interruptions or
interactions with its surroundings. We’re so far away from these realities in
an applicatory sense, but the fact that we know they are there — and in a few
special cases, they already exist — is enough of a reason to begin thinking.
If we don’t acknowledge the potential and possibilities now, by the time it
does become application-worthy, the AI contingent will have already missed the
boat. The aforementioned "few special cases" so far include the likes of
Microsoft, IBM and Intel, as well as Google. They are further ahead than
anyone else has been in history to unlocking the scope of quantum computing.
To be able to wade through vast swathes of data laden with millions and
billions of constraints, all in the blink of an eye.
Bringing NetOps Up to Speed With DevOps
Fortunately for NetOps teams, myriad networking vendors today readily offer
pre-built, certified solutions for DevOps platforms, making it easier to get
started on a cloud-native journey by automating activities such as device
onboarding and configuration changes. This way, network administrators can
leverage existing vendor partnerships, in-house knowledge and technology that is
already proven within the larger IT environment. Additionally, network engineers
shouldn’t need—and won’t have the extra time—to become top-notch developers to
take advantage of programmability during their cloud-native journey. Developing
basic programming skills is advantageous, but network management systems that
offer Python scripting, a consistent set of APIs and webhooks can perform the
“heavy lifting” when it comes to enabling extensibility with third-party IT
platforms. Today, this level of extensibility includes being able to integrate
with third-party IT service management tools. A common use case that can realize
significant time savings and greater network and application availability is to
auto-trigger and assign an incident ticket when a performance SLA is breached.
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