7 ways to ruin your IT leadership reputation
Be mindful of the decisions you make. “One careless choice can ruin your
reputation and your career,” warns Jim Durham, CIO of Solar Panels Network USA,
a national solar panel installation company. “By being aware of the risks and
taking responsibility for your actions, you can minimize the damage and learn
from your mistakes,” he advises. A careless decision can be anything from
selecting the wrong technology to mishandling sensitive data. “Not only are
these actions career-destructive, but they can also have lasting negative
effects on your enterprise,” Durham notes. CIOs are always pressured by
management to make the right decision. It’s important to remember, however, that
even the best strategies and intentions can sometimes lead to disastrous
results. “If you’re unsure about a decision, it’s always better to err on the
side of caution and consult with your team before making a final call,” Durham
suggests. Failure is never an option, particularly major failures. “It
shows that you’re not capable of handling important tasks,” Durham
states.
Cyber Skills Shortage is Caused by Analyst Burnout
Data shows skilled and experienced professionals are leaving the industry due to
burnout and disillusionment. In the UK, the cybersecurity workforce reportedly
shrank by 65,000 last year, and according to a recent study, one in three
current cybersecurity professionals are planning to change professions.
According to ISACA’s State of Cybersecurity 2022 report, the top reasons for
cybersecurity professionals leaving include being recruited by other companies
(59%), poor financial incentives (48%), limited promotion and development
opportunities (47%), high levels of work-related stress (45%) and lack of
management support (34%). When discussing the skills shortage, many, by default,
think of businesses struggling to recruit for their internal cybersecurity
vacancies. However, this is equally challenging for specialist providers of
consulting and managed cybersecurity services. Businesses increasingly rely on
third-party managed services, particularly mid-size organizations, where
outsourcing to a Managed Security Service Provider (MSSP) represents a much more
commercially viable solution with considerably less up-front investment.
Data privacy is expensive — here’s how to manage costs
“The true cost of data privacy, broadly, is their trust with their customers,”
said Akbar Mohammed, lead data scientist, Fractal AI. “In this era of customers
increasingly becoming tech-savvy, as soon as they realize that their data isn’t
secure, the company will risk loss of trust from consumers. This eventually
results in a lot of business disruption.” Almost all companies that need to
collect data for their operations should have a data privacy infrastructure in
place. Companies should also set up dedicated security and compliance teams
surveying data and technology assets along with maintaining an aggressive threat
detection policy. It’s imperative for companies today to have a data strategy
and have policy and procedures governed by a data governance entity. “For large
organizations, it’s best to have regular audits or assessments and get
privacy-related certifications,” Mohammad said. “Lastly, train your people and
make the entire organization aware of your activities, your policies.”
Architectural Patterns for Microservices With Kubernetes
Kubernetes provides many constructs and abstractions to support service and
application Deployment. While applications differ, there are foundational
concepts that help drive a well-defined microservices deployment strategy.
Well-designed microservices deployment patterns play into an often-overlooked
Kubernetes strength. Kubernetes is independent of runtime environments. Runtime
environments include Kubernetes clusters running on cloud providers, in-house,
bare metal, virtual machines, and developer workstations. When Kubernetes
Deployments are designed properly, deploying to each of these and other
environments is accomplished with the same exact configuration. In grasping the
platform independence offered by Kubernetes, developing and testing the
deployment of microservices can begin with the development team and evolve
through to production. Each iteration contributes to the overall deployment
pattern. A production deployment definition is no different than a developer's
workstation configuration.
High data quality key to reducing supply chain disruption
With so many obstacles to overcome, the supply chain needs a saviour – and many
experts are pointing to big data to fill the role. Prince believes data will
become more important in this new era. He says that after Brexit, “there is
uniquely new importance placed on master data, given the customs and other
regulatory impacts of moving goods between the two markets”. Also, the greater
risks posed in global trade and the need to be resilient mean that the
predictive capabilities of data could be crucial. ... The potential of big data
is clear – but to get the best results, the data involved needs to be accurate.
“Data quality takes on many forms, including accuracy, completeness, timeliness,
precision, and granularity,” says Laney. He points out that most organisations
don’t have n-tier visibility in their supply chain, which means they don’t
understand what is happening beyond the first tier of suppliers in the chain.
They may also have incomplete data on where items are in the supply chain or
when disruptions will happen.
Privacy assembly in Istanbul calls for adaptation to new necessities
Explaining that new challenges and needs emerged with the development of
artificial intelligence (AI) and the metaverse, Koç underlined that protecting
personal data should be a requirement. "Unfortunately, we pay the price for the
comfort and efficiency provided by technology in the age of data, with privacy,"
he said. KVKK Chair Faruk Bilir, for his part, said that since the foundation's
membership to the assembly, Türkiye has given significant importance to
international efforts in the field. KVKK leads initiatives for the protection
and awareness of personal data and privacy in line with the laws and regulations
adopted since 2016, he added. "The protection of individuals' privacy emerges as
an unchanging fact of the changing world," Bilir said. The protection of privacy
is an indicator of civilization, Bilir said underlining the importance of a
human-oriented approach. Law and ethics are complementary elements to the
human-oriented approach, he added. "Technology is indispensable for us, our
privacy is our priority," Bilir said.
CISA Releases Performance Goals for Critical Infrastructure
Among the newly recommended measures are implementation of multifactor
authentication, making sure to revoke the login credentials of former employees,
disabling Microsoft Office macros and prohibiting the connection of unauthorized
devices, perhaps by disabling AutoRun. The document also recommends that the
operational technology side have a single leader responsible for cybersecurity
and that OT and IT staff work to improve their relationship. Organizations
should "sponsor at least one 'pizza party' or equivalent social gathering per
year" to be attended by the two cybersecurity teams. DHS says it will actively
solicit feedback about the goals in the coming months and has set up a GitHub
discussions page. The department's next plan is to roll out cybersecurity goals
tailored to each sector of critical infrastructure in conjunction with the
agencies closest to each sector, such as the Environmental Protection Agency for
water systems.
Will Twitter Sink or Swim Under Elon Musk's Direction?
Musk's accompanying "let that sink in" tweet could be, in terms of bang for the
buck, the most groan-inducing dad joke of all time. But it shouldn't hide the
very real business and security challenges facing Musk, who's already CEO of
Tesla and SpaceX, as he takes the helm of a social network sporting 230 million
customers. "The bird is freed," Musk tweeted late Thursday, before the $44
billion deal closed Friday, and Twitter filed for delisting from the New York
Stock Exchange as it goes private. Like so much with Musk, commentators have
been attempting to deduce his planned intentions on numerous fronts. Musk styles
himself as a showman, having once tweeted - apparently about nothing in
particular - that "the most entertaining outcome is the most likely." ... What
state Twitter might be in once Musk is done with it remains unclear. Then again,
when you're the richest person in the world, what's a few billion here or there,
especially if it keeps people talking about you and guessing at your next
move?
How to turbocharge collaboration in innovation ecosystems
Whether you call it socialization or use any other term, the human dimension of
innovation is often overlooked or obscured. In part, this is because technology
and the covid-19–induced migration to online platforms have garnered a great
deal of attention. It’s important to remind managers that innovating as a
special form of problem-solving is best tackled by empowering the workforce.
Collaboration can be jump-started from many directions, but it can be only as
vibrant as the company’s underlying culture of curiosity, learning, and
continuous adaptation. In the Veezoo–AXA story, the formal process failed to
reach a breakthrough. It was the involvement of specific individuals who were
keen to see the collaboration through—often on their own terms—that led to
success in building an innovation ecosystem. In fact, it is often through the
behaviors and work of certain people that effective structure and discipline
emerge across an ecosystem.
Data Quality as the Centerpiece of Data Mesh
After all, data quality is always context-dependent and the domain teams will
best know the business context of the data. From a data quality perspective,
data mesh makes good sense as it allows data quality to be defined in a
context-specific way–for example, the same data point can be considered “good”
for one team but “bad” for another, depending on the context. As an example,
let’s take a subscription price column with a fair amount of anomalies in it.
Team A is working on cost optimization while Team B is working on churn
prediction. As such, price anomalies will be more of an important data quality
issue for Team B than for Team A. To make it easier to facilitate ownership
between data products (which can be database tables, views, streams, CSV files,
visualization dashboards, etc.), the data mesh framework suggests each product
should have a Service Level Objective. This will act as a data contract, to
establish and enforce the quality of the data it provides: timeliness, error
rates, data types, etc.
Quote for the day:
"Humility is a great quality of
leadership which derives respect and not just fear or hatred." --
Yousef Munayyer
No comments:
Post a Comment