How CIO Roles Will Change: The Future of Work
On the IT side, CIOs sent workers home with laptops and video conferencing
software last year. But it's time to reexamine whether those simple tools are
adequate. Do workers need bigger displays? Do they need more than one monitor?
What about webcams and better microphones, particularly if they are representing
the corporate brand in virtual meetings with external partners and customers.
Other technologies that are getting more attention include anything to do with
security in this age of distributed work such as edge security, and VPNs.
Companies are also reevaluating their unified collaboration and communications
technologies as they look to enhance collaboration in a virtual setting.
Employees are spending more time using software such as Microsoft Teams, Cisco
Webex, and Zoom. How can those tools be improved? "CIOs have moved from
infrastructure officers to innovation officers," Banting said. "CIOs are finding
out what technology can do for the business, how it meets their needs, and how
it makes them more agile by promoting distributed working. Technology can be
used as an asset rather than a liability on the books. That's quite a
fundamental shift in the IT department and the roles that CIOs play."
Composable commerce: building agility with innovation
Composable commerce is a microservices and modularised architecture that
provides organisations with agility through quick, application programming
interface (API) driven integrations, from catalogues and product searches, to
order submissions, inventory, and recommendations. It provides seamless
communication between various applications, giving customers new ways to
interact and connect with brands on a personal level. Development teams can
focus their efforts on speed and innovation, while operations can make time for
back-end updates, compliance releases, and testing. All this can be done without
affecting front or back-end operations. It provides collaboration between
departments so development, operations, marketing, ecommerce, data, finance, and
other areas can align and become an agile platform. Everything can work together
cohesively and with siloes no longer existing, products can be brought to market
quickly and efficiently without manual intervention.
New approaches for a new era: the mission-critical tools for post-Covid business success
Taking an agile approach enables workforces – especially project management
teams – to adapt quickly and easily, promoting creative, out-of-the-box
thinking throughout the business. Businesses that have embraced business
agility have found that teams work better together, and their decision-making
processes often become much quicker than would have been possible otherwise.
To enable adaptability, employers need to find ways to drive employee
engagement and efficiency regardless of where people are. ... The uptake of
innovative technologies that drive true workplace collaboration spans broader
work management platforms offered by a range of global providers,
communication apps such as Microsoft Teams and Slack, and toolchains for
developing and deploying software such as Azure DevOps. Their use has been
made easier because they can often be integrated, allowing teams to use the
tools they want for various purposes while still keeping collaborative efforts
connected. These types of intuitive solutions enable enterprises to rapidly
adjust tactics, resources and personnel to keep operations on course when
business conditions shift dramatically – providing organizations with a
competitive edge through the current health and economic crisis and in a
post-Covid world.
Microsoft and Google prepare to battle again after ending six-year truce
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The pact was reportedly forged to avoid legal battles and complaints to
regulators. It meant we haven’t seen Microsoft and Google complaining publicly
about each other since the days of Scroogled, a campaign that attacked
Google’s privacy policies. Now the gloves appear to be off once again, and
we’ve seen some evidence of that recently. Google slammed Microsoft for trying
to “break the way the open web works” earlier this year, after Microsoft
publicly supported a law in Australia that forced Google to pay news
publishers for their content. Microsoft also criticized Google’s control of
the ad market, claiming publishers are forced to use Google’s tools that feed
Google’s revenues. The rivalry between the two has been unusually quiet over
the past five years, thanks to this legal truce. Microsoft was notably silent
during the US government’s antitrust suit against Google last year, despite
being the number two search engine at the time. The Financial Times reports
that the agreement between Microsoft and Google was also supposed to improve
cooperation between the two firms, and Microsoft was hoping to find a way to
run Android apps on Windows.
Continuous Integration and Deployment for Machine Learning Online Serving and Models
One thing to note is we have continuous integration (CI)/continuous deployment
(CD) for models and services, as shown above in Figure 1. We arrived at this
solution after several iterations to address some of MLOps challenges, as the
number of models trained and deployed grew rapidly. The first challenge was to
support a large volume of model deployments on a daily basis, while keeping
the Real-time Prediction Service highly available. We will discuss our
solution in the Model Deployment section. The memory footprint associated with
a Real-time Prediction Service instance grows as newly retrained models get
deployed, which presented our second challenge. A large number of models also
increases the amount of time required for model downloading and loading during
instance (re)start. We observed a great portion of older models received no
traffic as newer models were deployed. We will discuss our solution in the
Model Auto-Retirement section. The third challenge is associated with model
rollout strategies. Machine learning engineers may choose to roll out models
through different stages, such as shadow, testing, or
experimentation.
After EI, DI?
In thinking through what a practical model of digital intelligence might look
like, we thought it would be useful to identify three elements that make up
best practices for operating in a digital environment. One is the analytical
and cognitive component — in essence, how to make sense of the welter of
information and data that the digital world offers. The second is the need to
collaborate with others in new ways and new mediums. The third is the
practical mastery and application we need to demonstrate. This third element
is akin to how Robert J. Sternberg, James C. Kaufman and Elena L. Grigorenko
describe “practical intelligence”; that is to say, how we manage real world
situations or, in our case, navigate the digital world successfully. This is
an ability, we would argue, that entails a different or least greatly modified
set of skills from that we use in face-to-face environments. ... We aren’t
proposing that digital intelligence be treated as true intelligence, but
rather as a loose framework to help us identify the knowledge, skills,
attitudes and behaviors that make up the “digital sensibility” needed to
operate and succeed in increasingly digital organizations and
marketplaces.
SRE vs DevOps: Comparing Two Distinct Yet Similar Software Practices
CTOs, product managers, software executives, process specialists are looking
for newer ways to enhance the trustworthiness of their software systems
without any compromise on the speed and quality. SRE and DevOps are two such
software methodologies that are popular today, in the world of software
development. What does SRE stand for? SRE stands for Site Reliability
Engineering. Both these procedures are supposed to be sharing a similar line
of principles and goals that makes them compete. They look like two sides of
the same coin, targeting to lessen the gap between the development and
operation teams. Yet, they have their own distinct characteristics that make
them contrast. Rather than being two competing procedures for software
operations, SRE and DevOps are more like pals that work together to solve
organizational hurdles and deliver software in a fast manner. It is
interesting to understand what these concepts individually mean, what they
have in common, how they differ from each other, and how they fit each other
like missing pieces of any puzzle.
How to support collaboration between security and developers
Like everyone else, security people want to see the company succeed, and see
cool stuff happen. Developers also care about more than just delivery of
code; plus they know that if something bad happens, there are significant
implications that they want to avoid. While open lines of communication and
mutual understanding are key it is equally important that DevSecOps teams
have a toolset that is similarly integrated and capable of tracking and
addressing the changes that might be happening in your organization. Whether
we’re talking about changes in cloud providers, the deployment stack, or
something else, there is a clear need to have a platform that will work
where you are—in the cloud or on-premises. ... While tools are an essential
element of enabling DevSecOps, there remain other challenges to be resolved.
These include the “unknown unknowns” that organizations encounter as they
speed up their digital transformation. For example, organizations across the
board rushed to scale up their cloud environments in response to the
pandemic last year. However, when rushing to do so many did not scale up
their security and governance processes at the same time and rate.
5 Mistakes I Wish I Had Avoided in My Data Science Career
Do I want to be a data engineer or a data scientist? Do I want to work with
marketing & sales data, or do the geospatial analysis? You may have
noticed that I have been using the term DS so far in this article as a
general term for a lot of data-related career paths (e.g. data engineer,
data scientist, data analyst, etc.); that’s because the lines are so blurred
between these titles in the data world these days, especially in smaller
companies. I have observed a lot of data scientists see themselves as ONLY
data scientists building models and don’t pay attention to any business
aspects, or data engineers who only focus on data pipelining and don’t want
to know anything about the modeling that’s going on in the company. The best
data talents are the ones who can wear multiple hats or are at least able to
understand the processes of other data roles. This comes in especially handy
if you want to work in an early stage or growth stage startup, where
functions might not be as specialized yet and you are expected to be
flexible and cover a variety of data-related responsibilities.
Responsible applications of technology drive real change
Thanks to the Digital Revolution, many things that seemed impossible just a
few years ago are now commonplace. No one can deny that our productivity –
and indeed, enjoyment – has been dramatically improved by technologies
ranging from AI to Big Data, 5G and the IoT. While new applications for
these technologies are being found seemingly every day, it’s increasingly
important to ask how we can utilise technology in a responsible way, to
change and improve people’s lives in critical areas like education,
healthcare and the environment. The good news is that work is already
underway to apply technology in meaningful ways. Take, for instance, the
support being provided for young African women programmers in marginalised
communities. They are benefitting from free online training and free access
to cloud computing resources. The aim of this project is to create one
million female coders by 2030 with the objective of improving their life
outcomes by helping them along a career path in engineering and other
practical subjects. The iamtheCODE initiative provides them with tailored
courses on a range of technical topics including cloud computing, data
analysis, machine learning and security.
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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