Autore: martechcubejohn

Data has always been the backbone of business operations, highlighting the significance of data and analytics as essential business functions. However, a lack of strategic decision-making often hampers these functions. This challenge has paved the way for new technologies like data fabric and data mesh, which enhance data reuse, streamline integration services, and optimize data pipelines. These innovations allow businesses to deliver integrated data more efficiently.

Data fabric can further combine with data management, integration, and core services across multiple technologies and deployments.

This article explores the importance of data fabric architecture in today’s business landscape and outlines key principles that data and analytics (D&A) leaders need to consider when building modern data management practices.

The Evolution of Modern Data Fabric Architecture

With increasing complexities in data ecosystems, agile data management has become a top priority for IT organizations. D&A leaders must shift from traditional data management methods toward AI-powered data integration solutions to minimize human errors and reduce costs.

Data fabric is not merely a blend of old and new technologies; it is a forward-thinking design framework aimed at alleviating human workloads. Emerging technologies such as machine learning (ML), semantic knowledge graphs, deep learning, and metadata management empower D&A leaders to automate repetitive tasks and develop optimized data management systems.

Data fabric offers an agile, unified solution with a metadata-driven architecture that enhances access, integration, and transformation across diverse data sources. It empowers D&A leaders to respond rapidly to business demands while fostering collaboration, data governance, and privacy.

By providing a consistent view of data, a well-designed data fabric improves workflows, centralizes data ecosystems, and promotes data-driven decision-making. This streamlined approach ensures that data engineers and IT professionals can work more efficiently, making the organization’s systems more cohesive and effective.

Know More, Read Full Article @ https://ai-techpark.com/data-management-with-data-fabric-architecture/

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The rise of artificial intelligence (AI) has transformed many sectors across the business landscape, reshaping how organizations operate. However, the convenience of AI introduces environmental challenges, such as increased energy consumption and hardware waste. These unintended consequences call for thoughtful strategies from chief information officers (CIOs), who must balance technological advancements with sustainability goals.

According to a Gartner survey, environmental issues are now a top priority for tech companies, and CIOs are facing pressure from executives, stakeholders, and regulators to implement sustainability initiatives. The convergence of AI and environmental responsibility requires proactive measures that can drive sustainable transformation.

This article offers a framework for adopting green algorithms—energy-efficient AI solutions—to help CIOs build sustainable IT organizations.

AI Supporting Environmental Sustainability

To integrate sustainability into IT operations, CIOs must establish clear mandates and requirements to track sustainability metrics, such as energy consumption and carbon footprint. The effectiveness of these efforts depends on embedding sustainability KPIs into the organization's digital infrastructure.

A practical example lies in modern data centers. Advanced optical networks, which use fiber cables, are significantly more energy-efficient than copper-based networks. Fiber cables require fewer raw materials and less manufacturing energy, reducing the environmental impact compared to the extraction and refinement processes for copper. In fact, IT companies implementing modern networking technologies have reported up to fourfold reductions in their environmental footprint.

While AI can introduce environmental challenges, it holds tremendous potential to advance sustainability initiatives when used thoughtfully. CIOs and project managers play a pivotal role in designing and implementing AI-driven solutions that align with sustainable development goals.

By focusing AI efforts on the right use cases, businesses can mitigate environmental impacts, enhance operational efficiency, and reduce unnecessary costs. AI has the potential to become a powerful ally, fostering both innovation and environmental responsibility in the IT industry. With proactive strategies, the convergence of AI and sustainability can transform the future of business.

Know More, Read Full Article @ https://ai-techpark.com/the-convergence-of-ai-and-sustainability-in-the-it-industry/

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Yashin, to kick things off, could you share what inspired you to transition from a career in academia and engineering to founding Pvotal Technologies?

Growing up, I thought a lack of proper education was the root of many societal issues and inefficiencies.

Idealistically, I entered academia thinking I could become a professor who would nurture the issues leading to a wavering generation of talent, innovation, and development. Unfortunately, I quickly realized how some processes were limiting, stifling, and stuck in an antiquated age.

I could not build or address problems I saw in my niche field due to software issues, data breaches, the high cost of licensing fees for some critical tools, and the poor integration of tools. These issues led me to lose thousands of hours in frustration fixing technical problems rather than focusing on my growth, thesis, and research. The tools I used became a greater source of frustration than my research, constantly distracting me from my objectives.

My skills and resolve were too limited to reform academia from within, so I decided to focus on the issues within the software industry to limit the problems that more talented academics faced. I co-founded Pvotal with Ashley to build a new generation of solutions that helped customers focus on the value they bring to customers rather than get stuck in an iterative cycle of integrating code and debugging updates.

Pvotal emphasizes creating “Infinite Enterprises.” Could you explain what this concept entails and how it aligns with your overall mission?

While many industries have adopted different interpretations of the ideal Infinite Enterprise, we believe the “infinite enterprise” is any company that has achieved an infinitely scalable, independent, resilient, and secure infrastructure. Once these criteria are met, we observed that it allows businesses to truly innovate, improve, and elevate their value proposition to customers.

The age-old adage of teens or some fresh graduates going into “founder mode” can build the next generation of software in their proverbial garage, shared workspace, or dorm room is simply no longer possible.

The rise of hyperspecialization, wanton integration of third-party code or vendors, and the unmanaged accumulation of technical debt has led most software companies to become antiquated, vulnerable, and overbloated pieces of code that can no longer efficiently protect their customers’ data, provide a competitive edge to their users, and have a reasonable cost/utilization footprint.

Most modern enterprise software has at least 17 paid or free SaaS, PaaS, and third-party code powering its operation or development. With a tough economy, inflation, and squeezed supply chains, these different services are forced to raise prices continually, thus shifting the burden on the end consumer. In addition to the increasing costs, these software are often abandoned or introduce vulnerabilities to the enterprise supply chains, which is why we have experienced a record-breaking number of successful cyberattacks, ransomware, and fraud every year for the past decade.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-yashin-manraj/

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As the world navigates through 2024, cybersecurity gets more unpredictable and dangerous. With increased sophisticated cyberattacks like ransomware, phishing, and APTs, there has never been a higher demand for cybersecurity professionals. But after the rising tide, the industry stands at a significant skills gap, presenting organizations with vulnerabilities to breaches and data theft.

Following a report by ISC², there is a lack of more than 3.4 million cybersecurity workers across the world. The gap becomes an important threat to diverse organizations, majorly finance, healthcare, and technology-related businesses that are more vulnerable to cyber attacks. As we head to the future, B2B businesses need to invest in the next generation of cybersecurity talent and equip them with crucial knowledge and skills to offer sensitive data and systems protection.

This is your roadmap for the business to educate professionals in cybersecurity across all types of skills with education and strategies to create the best plan of workforce development.

The Growing Need for Cybersecurity Talent in 2024 and Beyond

Current Workforce Shortage

Business operations in almost every corner of the globe are being adversely affected by a severe challenge: an acute shortage of cybersecurity professionals. According to Cybersecurity Ventures, by 2025, cybercrime will reach $10.5 trillion in annual damages worldwide, representing an even greater need for experts in that field. There are not enough trained professionals to fill such a high demand. This presents a challenge to businesses, particularly those sectors dealing with sensitive data, such as healthcare, government, and finance.

Evolving Threats

The 2024 threat landscape is not only about malware and phishing schemes. Organizations are becoming increasingly subjected to more advanced attacks, like ransomware-as-a-service (RaaS), attacks by nation-state entities, and supply chain attacks—all of which make much greater technical capability demands than traditional IT knowledge requires. It is thus crucial to train professionals who can predict the magnitude of new threats.

The Role of New Technologies

Emerging technologies such as artificial intelligence (AI), machine learning (ML), and cloud computing are impacting the cybersecurity sector with new vulnerabilities; therefore, professionals have to become adept at securing these systems; thus, the urgency for cybersecurity knowledge coupled with cutting-edge tech becomes highly integral in the future workforce.

To Know More, Read Full Article @ https://ai-techpark.com/preparing-the-next-generation-of-cybersecurity-professionals/

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Have you encountered a bad situation that was made worse by something that is meant to help? Here’s a recent example of mine – I had to take my son to an emergency room while vacationing in Asia but the most frustrating part was dealing with insurance when we got home. The agent who initially processed my claim put me (and my money) in limbo – no external or internal follow-up communication, inaccessible and invisible in the client portal – because they didn’t follow the process for handling non-English documents. This poor customer service was entirely preventable and, though I’m not an insurance industry expert, I’m going to tell you how.

I started this article with my personal experience because all service providers need to consider customer impact when designing their AI adoption. Unfortunately for me, health insurance is a relatively inelastic service. The insurance company – let’s start to see ourselves in their position now – has many customers locked in for the year irrespective of individual satisfaction. It also means that customer acquisition is relatively fixed. Insurance companies are not alone in having profit margins that are won and lost in processes. They’re also not alone in having a customer base that includes stubborn engineers who will spend above-average time investigating problems to discover a root cause (hi, that’s me). Even though I can’t switch medical insurance, the original agent’s mistakes followed by my persistence led to an undesirably high touch time for the insurance company (getting personal again, I digress…)

Whether your organization manages insurance claims, manufactures automotive components, or facilitates the food and beverage supply chain, profitability is influenced by how well your people, processes and systems are harmonized. Fortunately, some of the up-and-coming solutions embedded with AI have started to measurably improve the balance with people, processes and, ultimately, profit. One of the solutions with a high yield potential from relatively low effort is called Process Mining. Gartner defines it as “a technique designed to discover, monitor and improve real processes (i.e., not assumed processes) by extracting readily available knowledge from the event logs of information systems”. What gives process mining the potential for high yield with low effort is that it leverages information that your business processes already generate but traditionally ignore outside of IT troubleshooting. Process mining users are provided with unprecedented visibility of process flows and deviations. Analysis of those deviations turns into data-driven continuous improvement with the possibility of incorporating process improvements that were already proven through execution even though they weren’t pre-planned.

To Know More, Read Full Article @ https://ai-techpark.com/ais-role-in-process-mining/

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In the digital world, data is the lifeline of any business, be it trade secrets, sales records, customers’ personal data, and other sensitive information. Organizations use this data to create innovations and increase their long-term client base.

However, the current situation is quite different, especially with this surge in cyberattacks, insider threats, and phishing attacks. In a recent report by Forbes, it was witnessed that in 2023, security breaches saw a 72% increase from 2021, which held the previous record. Hence, protecting this data has never been so important.

Organizations can use data loss prevention (DLP), an indispensable tool that monitors, identifies, and protects sensitive data from unauthorized access and leakage, to prevent data loss.

DLP also aids organizations in meeting regulatory mandates such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA). These laws and regulations are stringent obligations in an organization that secures sensitive data and notifies the security teams during data breaches. With the help of DLP solutions, CISOs, CIOs, or IT managers can ensure that the right employees are accessing the right data for the correct reason.

For a better understanding of this subject, today’s AITech Park article will discuss data loss prevention, how it functions, software solutions, and the latest strategies and policies organizations can implement for stronger data security.

Reasons for Data Loss in Organizations

With the growing digital data and increasingly sophisticated cyber threats, data loss has become a primary concern for organizations worldwide, and data breaches, data leakage, or data exfiltration commonly cause this data loss.

Cybercriminals steal and transfer data from a network or device in data exfiltration. This act can be conducted by insiders or outsiders who generally perform cyberattacks such as DDoS attacks or phishing, and such data are exfiltrated through login credentials and intellectual property.

insider threats are extremely dangerous because the hazards come from within the company, leaving sensitive data vulnerable to exploitation. According to the website Check Point, it was observed that 43% of all breaches are insider threats, either intentional or unintentional, through company employees or former employees, contractors, and business associates.

It is witnessed that breaches often occur due to employees’s negligence, and there are numerous reasons such as weak security practices, execution of poor cybersecurity training programs, and not applying the principle of least privilege (POLP). Therefore, organizations need to provide comprehensive cybersecurity training for their employees so they comprehend the significance of keeping company data and personal data safe from antagonists.

CISOs, CIOs, or IT managers should also focus on creating strategies around DLP solutions and train employees to adopt cybersecurity best practices when performing their work.

To Know More, Read Full Article @ https://ai-techpark.com/data-loss-prevention-in-digital-world/

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We live in an age where personalization is key to our experiences, from music and web series to the products and services we use, all tailored to us based on data collected by websites and apps. This capability helps us better understand our needs and improve our overall quality of life.

Similarly, in the healthcare sector, technologies like artificial intelligence (AI), natural language processing (NLP), and machine learning (ML) allow us to monitor our health and receive personalized treatments. Often referred to as AI in healthcare, this technological collaboration is transforming traditional patient care by introducing futuristic clinical and administrative solutions. Doctors, researchers, and healthcare providers are using these advanced tools to enhance healthcare delivery in areas such as preventive care, disease diagnosis and prediction, treatment plans, and administrative tasks.

AI in healthcare is also making strides in recruitment, allowing companies to contribute more effectively to consumer health. The growing use of AI in wearable devices and medical tools is particularly valuable for detecting early-stage heart diseases. These AI-powered sensors and devices enable healthcare professionals to monitor and identify life-threatening conditions at an early stage.

While there are many applications for AI in healthcare, this article will focus on how AI is currently being implemented and what the future holds for healthcare policies in this sector. The concept of patient-centric care is a driving force behind AI-powered prescription medicine, which enhances personal treatment by empowering patients and providing real-time, visual care.

Key Areas of AI in Healthcare

The integration of AI in healthcare is transforming modern healthcare systems, enabling them to diagnose and treat diseases with greater speed and accuracy. These advancements are improving care quality and creating more patient-centered healthcare processes. AI's key focus areas include improving care delivery, strengthening disease surveillance, and accelerating drug discovery.

The future of AI in healthcare holds vast potential to shape public and private health policies. By prioritizing education and training and adopting AI responsibly, leaders in the health tech industry can unlock the full potential of AI, creating innovative, long-lasting solutions to the complex challenges facing healthcare today.To Know More, Read Full Article @ https://ai-techpark.com/ai-in-healthcare/ 

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In today’s tech-driven world, companies that adopt cloud computing can rapidly seize new market opportunities. By leveraging cloud technologies, IT professionals are empowered to innovate new models and software solutions, leading to greater business efficiency and mitigating technological risks.

However, many CIOs continue to rely on traditional models that, while effective in the past, are increasingly obsolete in the digital age. In this era, it’s nearly impossible to thrive without integrating cloud computing. Embracing the cloud enables businesses to foster innovation, improve agility, and enhance customer satisfaction. As a result, migrating to the cloud becomes a transformative journey, allowing companies to implement cutting-edge innovations such as next-generation hosting applications and data platforms, essential for maintaining a competitive edge.

This article explores how CIOs can navigate the cloud migration process and the transformative impact it has on their business.

Cloud Computing’s Transformative Role

For over a decade, cloud computing technologies have been at the forefront of revolutionizing industries. This technology is a catalyst for innovation and breakthrough solutions, as businesses increasingly recognize the significant advantages it offers over traditional computing and data storage methods.

For instance, migrating to the cloud can help businesses eliminate the high costs associated with purchasing on-premises hardware and software. It also provides the flexibility to scale cloud services up or down depending on demand, making it especially beneficial during seasonal fluctuations.

In today’s business landscape, cloud migration and cloud-native solutions are top priorities for CIOs. However, this shift brings with it challenges, such as optimizing cloud costs and determining best practices for hybrid cloud adoption. To maximize the benefits of cloud computing, CIOs must ensure that the migration is executed properly, with the right steps taken at the right time. This is key to unlocking the full potential of cloud technologies for business transformation.

To Know More, Read Full Article @ https://ai-techpark.com/connecting-dots-with-cios-cloud-computing-chronicles/ 

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Can you tell us about your journey as CEO and co-founder of Corti?

Corti was founded in 2016 in Copenhagen by Lars Maaløe and me. Lars, with his PhD in machine learning, and my experience as a multi-entrepreneur in AI from Scandinavia to Silicon Valley, has made for a solid partnership. We’ve always been driven by a belief in AI’s transformative potential for healthcare. We started Corti as a research company, with a bold thesis that Generative AI would become an integral part of every patient interaction in real time. At the time, this was a radical idea, but it has since proven to be viable. Initially, we focused on emergency medicine, assisting in detecting cardiac arrests and managing COVID-19 calls. Today, we are building the most reliable and effective Generative AI platform tailored to healthcare’s unique needs, scaling globally to enhance real-time consultations across healthcare and reducing the margin for error by up to 40%.

What inspired you to focus on healthcare technology, and how does your personal connection influence Corti’s mission and innovation?

From day one, we’ve been driven by the desire to reduce disparities in healthcare. Our vision is that everyone, everywhere, should have access to medical expertise. The uncomfortable truth is that millions of healthcare professionals are missing, and this gap is widening. From a young age, I saw firsthand the impact of overburdened healthcare systems on patients, which inspired me to seek a solution. That’s what drives me every day – to think that, thanks to Corti, a patient somewhere might get more time with their doctor, or avoid a misdiagnosis that could have been life-altering.

Could you provide an overview of Corti’s solutions?

Corti offers an AI-powered platform that enhances decision-making across the entire patient journey. Our AI provides a “second opinion” and integrates seamlessly into nearly any system, enabling healthcare professionals to quality assure, journal, code, nudge, prompt, and document every patient interaction. This drastically improves care, documentation, and revenue through expert guidance and support. We know there is no one-size-fits-all in healthcare, so Corti is fully customizable. It fits effortlessly into any workflow, effectively becoming the easiest employee you’ve never hired – no downtime, no breaks. With Corti, healthcare professionals save an average of two hours of documentation time per day and up to 80% on administrative tasks, freeing them to focus more on what truly matters: patient care.

What are the core values that Corti is built upon, and how do they guide the company’s objectives and mission in revolutionizing healthcare?

At Corti, we believe that everyone is a patient at some point, and we strive to support those who care for us when we need it most. Working at Corti means being committed to making the healthcare system better for all. Our team is driven by this belief – that we can and must do more to support caregivers. This mindset fuels us to go above and beyond, embracing challenges, staying curious, learning from failure, and waking up every day ready to try again.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-andreas-cleve/

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As cyberattacks advance in their sophistication and frequency, traditional cybersecurity defenders-the firewalls, antivirus software, even intrusion detection systems-are no longer sufficient in protecting companies. Organizations are bound to face advanced persistent threats (APTs), ransomware, as well as insider attacks in 2024 that often go undetected by automated detection tools. This makes proactive cybersecurity a dire necessity.

According to new research findings, the average amount of time taken before it is possible to detect a breach stands at more than 200 days, which is a very long window for cyberthieves to siphon sensitive data and cripple business operations.

This mainly occurs in B2B organizations operating within the finance, healthcare, and technology sectors, as these sectors are mainly characterized by sophisticated attackers seeking high-value data. However, the only solution is in cyber threat hunting-a proactive security approach aimed at detecting threats before they trigger damage.

In the guide here, we will cover the most important steps to implement a robust cyber threat hunting strategy tailored for 2024-overview of all the skills, processes, and technologies that will help in keeping your business safe.

What is Cyber Threat Hunting?

Cyber threat hunting is one of the proactive cyber security practice wherein the trained and well-equipped security analysts proactively search for hidden or undetected threats within an organization’s network.  While the traditional monitoring systems passively wait for alerts, the threat hunters search for malicious activity or a weakness that can be exploited.

Why It Matters in 2024

Today, the threat landscape for cyber defence is no longer passive but active detection. Attackers are continually evolving by attempting to evade detection with tactics like lateral movement, credential dumping, and fileless malware. Threat hunting becomes very critical in this approach since it looks beyond waiting for automated tools to flag an anomaly and instead hunts for and discovers sophisticated attacks made to evade traditional defenses.

Common Cyber Threats in 2024

Some of the prominent threats businesses will face in 2024 include the following:

Advanced Persistent Threats (APTs): Organized cyberattacks that siphon off data for long periods of time without being detected.

Ransomware: A ransomware attack encrypts a victim’s data and demands payment in lieu of providing decryption keys.

Insider Threats: It is an employee or contractor who intends to do evil or shows malacious carelessness in doing his duty that might lead to security breaches.

Zero-Day Exploits: In this case, attacks exploit vulnerabilities that have not been patched yet.

To Know More, Read Full Article @ https://ai-techpark.com/implementing-cybersecurity-threat-hunting/

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