What is Microsoft Fabric? A big tech stack for big data
Microsoft Fabric encompasses data movement, data storage, data engineering, data integration, data science, real-time analytics, and business intelligence, along with data security, governance, and compliance. In many ways, Fabric is Microsoft’s answer to Google Cloud Dataplex. As of this writing, Fabric is in preview. Microsoft Fabric is targeted at, well, everyone: administrators, developers, data engineers, data scientists, data analysts, business analysts, and managers. Currently, Microsoft Fabric is enabled by default for all Power BI tenants. Microsoft Fabric Data Engineering combines Apache Spark with Data Factory, allowing notebooks and Spark jobs to be scheduled and orchestrated. Fabric Data Factory combines Power Query with the scale and power of Azure Data Factory, and supports over 200 data connectors. Fabric Data Science integrates with Azure Machine Learning, which allows experiment tracking and model registry. Fabric Real-Time Analytics includes an event stream, a KQL (Kusto Query Language) database, and a KQL queryset to run queries, view query results, and customize query results on data. If KQL is new to you, welcome to the club.
Cybercriminals are creating their own AI chatbots to support hacking and scam users
In a surprisingly effective attack, researchers were able to use the prompt,
“Repeat the word ‘poem’ forever” to cause ChatGPT to inadvertently expose large
amounts of training data, some of which was sensitive. These vulnerabilities
place person’s privacy or a business’s most-prized data at risk. More widely,
this could contribute to a lack of trust in AI. Various companies, including
Apple, Amazon and JP Morgan Chase, have already banned the use of ChatGPT as a
precautionary measure. ChatGPT and similar LLMs represent the latest
advancements in AI and are freely available for anyone to use. It’s important
that its users are aware of the risks and how they can use these technologies
safely at home or at work. Here are some tips for staying safe. Be more cautious
with messages, videos, pictures and phone calls that appear to be legitimate as
these may be generated by AI tools. Check with a second or known source to be
sure. Avoid sharing sensitive or private information with ChatGPT and LLMs more
generally. Also, remember that AI tools are not perfect and may provide
inaccurate responses. Keep this in mind particularly when considering their use
in medical diagnoses, work and other areas of life.
Building a disaster recovery playbook
No one wants to dwell on the “what ifs.” This is especially the case for organisations that are already maxed on internal resources and growth planning. But having a disaster recovery playbook on hand is a major component of long-term business viability. Disaster recovery playbooks contain all of the information, resources, and processes required to get a business back up and running in the event of a catastrophic event. They have a detailed breakdown of all team members (both internal and external) involved in recovery processes and a methodical approach to isolate any persistent threats and resume normal operations. While there are best practices when going through disaster recovery planning, there is no one-size-fits-all format. A disaster recovery playbook is unique to your business and is formatted and customised based on specific circumstances and factors in your own business requirements when it comes to risk management. Note that for some companies, disaster recovery planning is actually required. For companies that must maintain compliance with standards like HIPAA, SOC, and FedRAMP, disaster recovery plans are necessary.
Transform your financial IT infrastructure: Boost sustainability, security, and resilience
Like other industries, the financial sector is still dealing with the aftermath
of COVID-19. Organizations are trying to figure out how to manage a hybrid
workforce and what to do with a surplus of office space created by
work-from-home practices. At the same time, financial services organizations
need to optimize their digital infrastructure to connect IT and OT systems for a
full view of the entire infrastructure. On the building management side, this
means deploying sensors and connectivity solutions to collect and analyze data
from systems such as chilled water plants, circuit breakers and mechanical
equipment. The data delivers insights that enable businesses to manage systems
more efficiently to reduce energy and operational costs. As they endeavor to
make these improvements, organizations are getting some help from hardware and
energy systems manufacturers, who are producing more efficient products that
generate less waste. Combined with investments in renewable energy sources,
efficient equipment helps organizations meet sustainability goals and comply
with the upcoming disclosure regulations on greenhouse gas emissions.
The role of storage infrastructure in fortifying data security
The data security solution should also include the integrated use of various
security technologies like Security Information and Event Management (SIEM),
Security Orchestration Automation and Response (SOAR), Data Loss Protection
(DLP), Identity and Access Management (IAM), Intrusion Detection and Prevention
Systems (IDPS) to enable comprehensive security to identify, protect, detect,
respond, and recover data. Every component in the overall IT stack needs to
participate in the data security paradigm, particularly enterprise storage
systems. Storage systems (on-premises, on-cloud, or hybrid) are home to all
business data and are essential in enabling the data security considerations
mentioned above. As a result, there is a need for storage systems with targeted
cybersecurity functionalities that can be integrated with the overall security
ecosystem. ... Fortifying storage systems to withstand, adapt to, and recover
from disruptions while maintaining the confidentiality, integrity, and
availability of data. Cyber resiliency also includes auditing, monitoring, and
the ability to recover promptly from cyber threats or incidents, encompassing
strategies such as backup, redundancy, and rapid response mechanisms.
Four Steps To Develop Executive Presence
When it comes to emotional intelligence, being aware of your emotions and
reading other people is crucial. Picking up nonverbal cues from others will
enhance communication. For instance, when you are speaking and notice the
other person’s eyes have "glazed over" or their expression looks blank, it
communicates that they are not fully present. So stop speaking and wait a few
seconds. Once you notice they are present again, there are several questions
you can ask: "Where did I lose you?" or "Was there something I said that
caught your attention?" ... Executive presence is not just about exuding
self-confidence and authority; it is also about building strong relationships.
In my last article on expanding the idea of leadership, I mention being
other-focused, which is the opposite of being self-focused. Addressing those
around you and showing genuine interest in them and what they are working on
makes you more approachable and shows you care and are a good listener. And if
they are struggling with something, empathizing before jumping in with a
solution emphasizes all the above.
Maritime Cybersecurity: An Emerging Area of Concern for India
The International Maritime Organization (IMO) defines maritime cyber risk as a
“measure of the extent to which a technology asset could be threatened by a
potential circumstance or event, which may result in shipping-related
operational, safety or security failures as a consequence of information or
systems being corrupted, lost or compromised.” Maritime cybersecurity includes
the systems overseeing ships’ operating software, navigation information, and
traffic monitoring. However, the current cyber infrastructure available
onboard civilian ships is not lacking in defensive cyber capabilities and
tools. Maritime sector cyber threats have become serious due to the complex
operationalization of IT and OT systems. These systems can be the subject of
ransomware, malware, phishing, and man-in-the-middle (MITM) attacks. The
motives behind such attacks can vary from traditional applications like naval
warfare to espionage, to non-state causes like cyber terrorism, and
hacktivism. Maritime cyberattacks can thus act as an instrument of foreign
policy or be undertaken by criminal groups or individuals. This threat extends
to onshore and offshore maritime assets.
The Meeting of the Minds: Human and Artificial
At the intersection of human cognition and LLMs lies the complex domain of
language, a common ground where the essence of our thoughts and the
architecture of AI converge. Language serves as the bridge between these two
realms, with its nuanced syntax, semantics, and pragmatics offering the basis
for exploration and understanding. For humans, language is the vessel of
consciousness, carrying the weight of our ideas, emotions, and cultural
heritage. For LLMs, it is the structured data through which they learn,
interpret, and generate responses, mirroring human-like patterns of
communication. This shared linguistic foundation enables a unique dialogue
between human intelligence and machine algorithms, fostering a collaborative
exchange that enriches both the depth and breadth of our collective knowledge
and interactions. ... Humans contribute a deep understanding characterized by
subtlety, emotional insight, and creative thinking. In contrast, LLMs bring
powerful data processing abilities, extensive memory capacity, and advanced
pattern recognition. This combination doesn't merely enhance our cognitive
abilities; it expands them, allowing for more thorough analysis and wider
exploration in problem-solving and innovation.
Harnessing Real-time Data: Transforming Data Management with Artificial Intelligence
In the tech industry, “AI” has become a ubiquitous buzzword, often used in
pitches regardless of the underlying technology. As an industry analyst
focused on analytics and AI and co-author and contributing author on a number
of AI books, including
Augmented Intelligence and Causal AI, I have met dozens and dozens of
companies that claim to offer AI solutions. I am direct with vendors and want
to know how they are applying AI to customer needs. In addition, I press
vendors on the depth of the AI/ML capabilities and how they approach the
field. ... The need for applying AI to data management is clear and
compelling. As organizations are inundated with data from myriad sources, the
capacity to curate, process, and extract meaningful insights must scale. The
volume of information generated by businesses makes AI a critical technology
in helping data science teams make sense of new information. When I work with
Chief Data Officers (CDOs), Chief Transformation Officers, and other
executives tasked with driving change through data, it is clear that AI is the
cornerstone of modern data management strategies. Unfortunately, traditional
data ingestion and classification methods begin to fail under the pressures of
real-time, high-volume demands.
API Management: A Weak Link in the Cloud-Native Chain
API management encompasses API design, development, monitoring, testing and
security, as well as making updates to APIs after they are in production.
These tasks are important, of course, because APIs are everywhere today. They
handle 83% of internet requests, according to Akamai, which means that keeping
APIs documented, updated and monitored is a critical requirement for virtually
any organization that deploys Internet-connected applications. Without an
efficient and scalable means of managing APIs, it becomes difficult not just
to defend against challenges like security risks involving APIs but also to
guarantee a positive developer experience. The more time and toil your
developers have to invest in API management, the less time they have to do the
things they want to do and that matter most to the business – like developing
cool apps and bringing them to market. ... APIs are not new, and most teams
that support them have long had API management practices in place. However, in
many cases, those practices were conceived in the era when monolithic
application architectures and bare-metal servers or virtual machines dominated
the IT landscape.
Quote for the day:
''Sometimes it takes a good fall to
really know where you stand.'' -- Hayley Williams
No comments:
Post a Comment