The Future of Healthcare Is in the Cloud
While the idea of making information accessible anywhere and at any time offers
obvious advantages, there are obstacles to overcome. Potential security risks
and concern over compliance has long held back cloud adoption in healthcare. IT
staff need to ensure timely software updates, maintain network availability, and
institute a regular and robust backup routine. Healthcare organizations also
need to consider how data will be processed by a third party, examine with whom
their cloud partners are in business, and ensure security standards extend to
any cloud networks they use. Cloud providers with healthcare experience and an
understanding of the unique compliance landscape will be favored as the industry
rises to meet these challenges. Everyone should take comfort from the fact that
the most advanced healthcare organizations in the world have announced major
cloud initiatives after much deliberation and due diligence. Mayo Clinic’s
announcement of its partnership with Google is one such example. The dream of
global collaboration relies on cloud computing. Healthcare professionals in
different countries can now trade massive data sets easily. While collaboration
like this has typically been reserved for esoteric research projects, it’s now
being employed to tackle global health problems.
Q&A: Telehouse engineering lead discusses AI benefits for data centres
Developments in network management AI and cyber security are allowing us to
detect unusual activity outside of usual traffic patterns. In a typical office
environment, if a company device logs in at 3am and starts taking gigabytes of
data from the business, that will be flagged as atypical behaviour. AI can
analyse this breach quickly and respond by disabling that device’s network
access to stop the possible data loss. That data transfer could also take place
in the middle of the working day, but it might come from a device that would not
normally transfer that volume of data, such as a laptop solely used for
presentations. The AI already understands the typical behaviour patterns of that
device and will flag when there might be inflow or outflow of data that does not
fit its typical usage pattern. In a data centre it is no different. Every server
has its own typical operational pattern, and these can be monitored by the cyber
security systems, and any unusual activity can be flagged. It is possible to
take this further than simple network monitoring by interfacing with other
systems. For example, detecting whether server behaviour changed after someone
entered a secure server hall, which could indicate that a server has been
tampered with.
The year ahead in DevOps and agile: bring on the automation, bring on the business involvement
The slower-than-desired pace of automaton stems from "organizations
prohibiting developers from accessing production environments, probably
because developers made changes in production previously that caused
production problems," says Newcomer. "It's hard to change that kind of policy,
especially when incidents have occurred. Another reason is simple
institutional inertia - processes and procedures are difficult to change once
fully baked into daily practice, especially when it's someone's specific job
to perform these manual deployment steps." DevOps and agile progress needs to
be well-measured and documented. "People have different definitions of DevOps
and agile," says Lei Zhang, head of Bloomberg's Developer Experience group.
Zhang's team turned to the measurements established within Google's DevOps
Research and Assessment guidelines -- lead time, deploy frequency, time to
restore, and change fail percentage, and focus on the combination. "We think
the effort is cohesive, while the results have huge varieties. Common
contributors to such varieties include complex dependencies due to the nature
of the business, legacy but crucial software artifacts, compliance
requirements, and low-level infrastructure limitations."
Performance Tuning Techniques of Hive Big Data Table
Developers working on big data applications have a prevalent problem when
reading Hadoop file systems data or Hive table data. The data is written in
Hadoop clusters using spark streaming, Nifi streaming jobs, or any streaming
or ingestion application. A large number of small data files are written in
the Hadoop Cluster by the ingestion job. These files are also called part
files. These part files are written across different data nodes, and when the
number of files increases in the directory, it becomes tedious and a
performance bottleneck if some other app or user tries to read this data. One
of the reasons is that the data is distributed across nodes. Think about your
data residing in multiple distributed nodes. The more scattered it is, the job
takes around “N * (Number of files)” time to read the data, where N is the
number of nodes across each Name Nodes. For example, if there are 1 million
files, when we run the MapReduce job, the mapper has to run for 1 million
files across data nodes and this will lead to full cluster utilization leading
to performance issues. For beginners, the Hadoop cluster comes with several
Name Nodes, and each Name Node will have multiple Data Nodes.
Ingestion/Streaming jobs write data across multiple data nodes, and it has
performance challenges while reading those data.
AI Support Bots Still Need That Human Touch
At the core of providing effective support for critical issues is
personalized, expedited service. In contrast to the wholesale outsourcing of
frontline support to bots with little documentation, by combining best
practices, best-of-breed technology and a trained staff of experts, this
hybrid approach offers the best option for delivering and maintaining
mission-critical networks. When a network administrator has an issue that is
beyond the automated self-healing functions, the first call should be readily
available and start with a dedicated support expert, who will know exactly how
the network is configured, its history, and they should have all of the
pertinent incident data at the proverbial fingertips. Issues can then be
quickly resolved and in the event that something unexpected pops up, it can be
handled without having to start all over again. Today, networks are being
stressed like never before with remote work, IoT, cloud migration, and so
forth, spawning novel, unforeseen issues that cannot be handled by limited
AI-based tools. During these periods, accessing an engineer with intimate
knowledge of the system and configuration on-site will be the lifeline network
teams need to help diagnose and resolve these types of challenges. Is this
simply a luddite view of Artificial Intelligence?
Hidden Dangers of Microsoft 365's Power Automate and eDiscovery Tools
Power Automate and eDiscovery Compliance Search, application tools embedded in
Microsoft 365, have emerged as valuable targets for attackers. The Vectra
study revealed that 71% of the accounts monitored had noticed suspicious
activity using Power Automate, and 56% of accounts revealed similarly
suspicious behavior using the eDiscovery tool. A follow-up study revealed that
suspicious Azure Active Directory (AD) Operation and Power Automate Flow
Creation occurred in 73% and 69%, respectively, of monitored environments. ...
Microsoft Power Automate is the new PowerShell, designed to automate mundane,
day-to-day user tasks in both Microsoft 365 and Azure, and it is enabled by
default in all Microsoft 365 applications. This tool can reduce the time and
effort it takes to accomplish certain tasks — which is beneficial for users
and potential attackers. With more than 350 connectors to third-party
applications and services available, there are vast attack options for
cybercriminals who use Power Automate. The malicious use of Power Automate
recently came to the forefront when Microsoft announced it found advanced
threat actors in a large multinational organization that were using the tool
to automate the exfiltration of data. This incident went undetected for over
200 days.
The ‘It’ Factors in IT Transformation
Shadow IT has been the bane of many-a-CIO for as far as I can remember. But
how many organizations focus on complete business IT alignment where the
operating model supports proactively eliminating business operation
disruptions as opposed to meeting internal IT SLAs? The best way to generate
this elusive value from an IT revamp is to use existing concepts and add vital
new ones to get transformational results. And the outcome? A business that can
comfortably jump barriers and leapfrog competitors for whom IT is an
afterthought. So, let’s break this down a bit. What are the “it” factors that
separate a successful IT transformation from the ones with relegated outcomes?
For starters, in the former, IT leaders address every critical part of the
whole and the framework encourages C-level executives to take the plunge.
Enterprise executives sometimes get cornered by organizational dynamics into
playing it safe, into taking baby steps. Unfortunately, though, as former
British Prime Minister David Lloyd George so appropriately puts it, “You can’t
cross a chasm in two small jumps.” Committing to a well-planned yet courageous
leap is critical for success from the very onset.
Organizations can no longer afford a reactive approach to risk management
“Business leaders must be vigilant in scanning for emerging issues and make
actionable plans to adjust their strategies and business models while being
authentic in fostering a trust-based, innovative culture and the
organizational resilience necessary to successfully navigate disruptive
change. Digitally mature companies with an agile workforce were ready when
COVID-19 hit and are the ones best positioned to continue to ride the wave of
rapid acceleration of digitally driven change through the pandemic and
beyond.” Consistent with the survey’s findings in previous years, data
security and cyber threats again rank in the top 10 risks for both 2021 and
2030. The continuously evolving nature of cyber and privacy risks underscores
the need for a secure operating environment in which nimble workforces can
regularly refresh the technology and skills in their arsenal to remain
competitive. “If there’s any risk that all organizations across industries and
geographies must maintain focus on, it’s cybersecurity and privacy,” said
Patrick Scott, executive VP, Industry Programs, Protiviti. “While the areas
that businesses will need to address may change as they transform their
business models and increase their resiliency to face the future confidently,
cybersecurity and privacy threats will remain a constant and should be at or
near the top of the list.”
Digital Transformation Demands a Culture of Innovation
Research done over the past five years by the Digital Banking Report finds
that corporate culture is much more important than the size of the company,
level of investment, geographic location or even regulatory environment. The
question becomes: How can leaders build and reinforce an innovation culture
within their organization? According to research by Jay Rao and Joseph
Weintraub, professors at Babson College and published in the MIT Sloan
Management Review, an innovative culture rests on a foundation of six building
blocks. These include resources, processes, values, behavior, climate and
success. Each of these building blocks are dynamically linked. The research by
the professors is aligned with insights found recently by the Digital Banking
Report which shows that increasing investment, changing processes and
measuring success is imperative … but not enough. Organizations must also
focus on the overarching company values, the actions of people within the
organization (behaviors), and the internal environment (climate). These are
much less tangible and harder to measure and manage, but just as important to
the success of innovation and the ability to create a sustained competitive
advantage.
How Enterprise AI Use Will Grow in 2021: Predictions from Our AI Experts
Hillary Ashton, the chief product officer at data analytics vendor Teradata,
said that AI will be helpful in 2021 for many companies as businesses look
toward reopening and recouping sufficient revenue streams as the COVID-19
pandemic slowly releases its grip on the world. “They’ll need to leverage
smart technologies to gather key insights in real-time that allow them to do
so,” said Ashton. “Adopting AI technologies can help guide companies to
understand if their strategies to keep customers and employees safe are
working, while continuing to foster growth. As companies recognize the unique
abilities of AI to help ease corporate policy management and compliance,
ensure safety and evolve customer experience, we'll see boosted rates of AI
adoption across industries." That will also involve using AI to boost safety
and compliance measures inside offices, she said. “As companies look to
eventually return in some form to the office, we'll see investments in AI rise
across the board. AI-driven algorithms can scour meeting invites, email
traffic, business travel and GPS data from employer-issued computers and cell
phones to give businesses advance warnings of certain danger zones or to
quickly halt a potential outbreak at a location. ..."
Quote for the day:
"A casual stroll through the lunatic
asylum shows that faith does not prove anything." --
Friedrich Nietzsche
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