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HOW BUSINESSES CAN UNLOCK THE TRUE VALUE OF MODERN LOG MANAGEMENT

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Mala Pillutla, Vice President of Sales for Log Management, Dynatrace

Without logs, it would be almost impossible to keep modern applications, cloud platforms, or customer-facing services running efficiently. Some might argue that logs are one of the most critical but least celebrated sources of truth in the digital era.

At its core, log management is about turning raw system logs — unprocessed, detailed records of a system’s activities, including server actions, user interactions, and error messages — into actionable insights. As digital systems grow in scale and complexity, logs have evolved from a backroom tool into a critical driver of reliability, performance, and security across an entire business.

From a website crashing or pages loading too slowly, to customers encountering errors or even early signs of a cyberattack, logs provide teams with a clear view of what’s happening inside their digital systems. Within an observability platform, they present the detailed “story” behind these events, helping teams move from simply knowing something is wrong to understanding why it’s happening and how to fix it before it impacts users.

Research has found that 87% of organizations claim to use logs as part of their observability solutions. That number shows how universal log usage has become. The question now is whether businesses are unlocking their full value. Collecting logs is one thing but interpreting them is another.

For too long, logs have been treated as clutter, something to store, sift, and forget. The reality is that they’re one of the clearest signals of how a business is running. Modern log management makes those signals impossible to ignore.

The limits of traditional log management

As business digital estates grow more complex, the volume of logs generated across applications, infrastructure and business services has exploded. However, more logs do not automatically mean more insight. In fact, many teams are overwhelmed by sheer volume, struggling to separate meaningful signals from background noise. This overload creates noise that makes it difficult to identify urgent issues, leaving IT and Security teams on the back foot during critical incidents and proactive response.

The problem is as much about cost as complexity. Storing and managing log telemetry without a clear purpose often leads to escalating expenses that outpace the value delivered. Traditional licensing and infrastructure models add to the problem. They often make log management feel like a financial liability than a strategic advantage.

Another common constraint is fragmentation. Logs often live across multiple tools, with different interfaces and storage models, slowing root cause analysis and complicating cross-team collaboration. In a cloud-native world where speed and scale are vital, this siloed approach is out of step with modern business needs.

Together, these shortcomings point to the need for a smarter approach—one that focuses on clarity, efficiency, and value.

Turning logs into actionable intelligence

Taking a smarter approach to log management starts with a shift in perspective. Rather than treating logs as an endless stream of technical data, leading organizations use them as a lens to understand how their digital ecosystems truly perform. The real value lies in not collecting everything but in knowing what matters and identifying which logs drive resilience, security, customer experience, or compliance, and filtering out the rest.

AI is becoming an essential part of this process. Modern techniques can detect anomalies, trace issues back to their root cause, and even trigger automated fixes. This reduces manual investigation and accelerates recovery, allowing teams to move from firefighting to foresight.

Equally important is being selective. Forward-thinking organizations decide which logs to capture, which to discard, and how to route them most effectively. This helps control costs and ensures that attention is focused on the telemetry that delivers the greatest value. When organizations find this balance, log management evolves from a tactical task to a strategic capability that strengthens both performance and resilience.

Observability and the bigger picture

Log intelligence on its own is valuable, but it is only part of the story. The next frontier is AI powered observability, uniting logs with metrics that track performance, traces that map interactions, and events that reveal key system changes. Combined in a single platform, these data types give teams a complete picture – connecting technical performance with genuine business impact and moving from a view of what happened to an understanding of why it happened and how to respond quickly.

Consider a global telecommunications provider that recently re-evaluated its log strategy. Managing more than 15TB of logs every day, stored for long periods and spread across thousands of dashboards, the team was buried in dashboards and redundant data. By consolidating logs within a broader observability framework and replacing static alerts with intelligent detection, they cut through the noise across its systems. Able to focus on the signals that mattered most, the organization improved uptime, speed, and overall resilience.

This example shows that observability delivers its greatest value when it helps teams cut through complexity. With logs feeding into a single platform, data becomes easier to interpret and act on, transforming technical insight into business intelligence.

Unlocking the true value of modern log management

Modern log management gives organizations the context they need to turn massive volumes of data into meaningful insight. Organizations that harness AI, automation, and broader observability, gain a clearer view of how their technology is supporting their goals. Enterprises can analyse faster, automate smarter, and innovate with confidence.

True modernization comes from changing how teams think about data. Now is the time to review current strategies, identify gaps, and adopt modern platforms that integrate AI, context, correlation, and smarter telemetry management practices because organizations can no longer afford to treat log management as a background IT task. The companies that thrive will be those that treat logs not as exhaust from their systems, but as evidence of how their business thinks and performs. By bringing intelligence to the data they already have, they will turn observability into a source of continuous advantage and understand their business like never before.

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Tech Features

HOW WOMEN SCIENTISTS CAN ACCELERATE NATIONAL INNOVATION GOALS

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Dr Heba El-Shimy, Assistant Professor (Data and AI), Mathematical and Computer Sciences, Heriot-Watt University Dubai

Healthy societies, institutions, or teams operate best when comprising a healthy balance between males and females. A landmark study by Boston Consulting Group (BCG) with the Technical University of Munich uncovered that companies with above-average gender diversity generated around 45% of their revenues from innovative products, compared to only 26% as innovative revenues for companies with below-average gender diversity. These findings are echoed in the scientific field. A 2025 study by Nature analyzing 3.7 million US patents revealed that inventing teams with higher participation of women are associated with increased novelty in patents. Research by the Massachusetts Institute of Technology confirms that teams with more women exhibit significantly higher collective intelligence and are more effective at solving difficult problems. These studies tell one clear story: that participation of women in innovative and scientific fields is not only desirable — it is a strategic national asset.

UAE Women In STEM

The UAE holds one of the world’s most striking gender profiles in STEM education. According to UNESCO data, 61% of graduates in STEM fields are Emirati women, surpassing the Arab world average of 57% and nearly doubling the global average of 35%. At government universities, 56% of graduates are women, and they represent over 80% of graduates in natural sciences, mathematics, and statistics.

These numbers have translated into accomplishments that have captured global attention. The Emirates Mars Mission — the Hope Probe — was developed by a team of scientists that was 80% women, selected based on merit. Noora Al Matrooshi became the first Arab woman to complete NASA astronaut training in 2024. The Chair of the UAE Space Agency and the mission’s Deputy Project Manager is a woman: H.E. Sarah Al Amiri. At Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), female enrolment reached 28% within five years and continues to grow. Women’s talents are being recognised — this is not a mere future ambition, but a present reality.

Scientific Research As An Engine For National Strategy

The ‘We the UAE 2031’ vision sets ambitious goals: doubling GDP to AED 3 trillion, generating AED 800 billion in non-oil exports, and positioning the country as a global hub for innovation, artificial intelligence, and entrepreneurship. The UAE’s rise to the 30th place in WIPO Global Innovation Index 2025 signals a steady pace towards achieving the UAE 2031 vision. Sustaining this ascent requires continued investment into human capital to produce research output, intellectual property, and commercial innovation at a pace matching the ambition. This is precisely where women scientists become indispensable.

Women scientists are already major contributors to the seven priority sectors identified in the UAE National Innovation Strategy: renewable energy, transport, education, health, technology, water, and space. UAE women scientists are research-active in climate science, sustainable materials, clean energy systems, AI-driven diagnostics in healthcare, and environmental monitoring — all crucial sciences that the national development commitments depend on.

Knowledge economies are built on the ability to generate, apply, and commercialize research locally — reducing the dependence on imported technologies and creating self-sustaining innovation ecosystems. When a researcher at UAEU develops patented computational methods for drug design, as Dr. Alya Arabi recently did with four patents spanning AI-driven pharmaceutical development and medical devices, that is intellectual property created on UAE soil, addressing healthcare challenges that would otherwise require imported solutions. When women scientists at Masdar City and Khalifa University advance research in solar energy systems, carbon captured materials, or sustainable desalination, they are producing foundational science that the UAE’s Net-Zero 2050 Strategy depends upon.

Masdar’s WiSER (Women in Sustainability, Environment and Renewable Energy) programme has graduated professional young women from over 30 nationalities, closing the gap in the global sustainability workforce. In healthcare, women scientists are active in the areas where AI, genomics, and precision medicine converge. The Emirati Genome Programme, M42’s Omics Center of Excellence, and the Abu Dhabi Stem Cells Center all represent domains where locally produced research can reduce the country’s reliance on imported diagnostics and therapeutics.

From these examples, it is clear that women scientists’ and researchers’ contributions are a central pillar of the national R&D ecosystem.

A Regional And Global Perspective

The UAE’s experience is instructive for the wider region. Across the Arab world, up to 57% of STEM graduates are women, yet the MENA region maintains one of the lowest female workforce participation rates globally at 19%. Saudi Arabia’s Vision 2030 has made notable progress, with women’s workforce participation reaching 36.2% and women now comprising 40.9% of the Kingdom’s researchers. The challenge across the GCC and MENA is consistent: converting educational attainment into sustained professional participation and research output. Globally, only one in three researchers is a woman, and parity in engineering, mathematics, and computer science is not projected until 2052. UNESCO’s 2026 International Day of Women and Girls in Science theme — “From Vision to Impact” — captures this urgency well.

The Way Forward: From Vision To Impact

As an academic working at the intersection of artificial intelligence and healthcare research in Dubai, I witness this potential daily — in students who arrive with rigour and ambition, in researchers producing work that stands alongside the best globally, and in a national ecosystem that increasingly treats women’s scientific participation as a strategic priority rather than a social courtesy. But policies alone do not produce innovation. What produces innovation is funding, access to facilities, clear pathways from research to commercialisation, and the recognition that a woman scientist publishing a patent in the UAE is building national capability in exactly the same way as the infrastructure projects that make headlines.

Sustained commitment is key — from governments, institutions, and the private sector — to ensure that every woman scientist in this region has the funding, the platforms, and the pathways to convert her research into national impact. When women scientists thrive, nations innovate faster. The UAE understands this. Now it must ensure the rest of the ecosystem does too.

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Tech Features

WOMEN IN AI AND DATA SCIENCE: WHO IS BUILDING THE ALGORITHMS THAT SHAPE OUR FUTURE?

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Dr Maheen Hasib, Global Programme Director for BSc Data Sciences, School of Mathematical and Computer Sciences, Heriot-Watt University Dubai

Artificial intelligence (AI) and data science are no longer distant or experimental ideas. They quietly sit behind many of the decisions that shape our everyday lives: how patients are diagnosed, how job applications are filtered, how loans are approved etc. These systems increasingly influence who gets opportunities and who does not. That reality makes one question impossible to ignore: who is building the algorithms that shape our future?

As a Programme Director for the Data Sciences programme at Heriot-Watt University, this question is not just academic for me, it is deeply personal. Every year, I meet capable, curious, and motivated young women who are genuinely interested in data science. Yet many hesitate. Not because they lack ability, but because they are unsure whether they truly belong in the field. Too often, they do not see people (like themselves) reflected in AI research, technical teams, or leadership roles. And that absence matters.

When bias in AI feels uncomfortably familiar

AI systems are often described as objective or neutral, yet they are trained in data shaped by human history, something that is far from neutral. When training data reflects existing gender imbalances, AI systems can replicate and even magnify those patterns. This has led to technologies that perform less accurately for women, fail to capture women’s health needs, or disadvantage women in recruitment and evaluation processes.

For many women, these outcomes feel uncomfortably familiar. They echo everyday experiences of being overlooked, misunderstood, or underrepresented. In most cases, this is not the result of deliberate exclusion. It is the consequence of design choices made without diverse perspectives at the table.

Why representation goes beyond numbers

Representation in AI and data science is often discussed in terms of statistics or diversity targets. But at its core, representation is about perspective. When women are involved in developing AI systems, they help shape how problems are defined, what data are considered relevant, and which risks are taken seriously.

From an academic perspective, diverse teams produce more robust research and better-tested models. From a human perspective, they help ensure that AI systems work for the full range of people they are meant to serve. Inclusion improves both technical quality and social impact, it strengthens the science and the society it serves.

Women and the future of ethical AI

Many women working in AI are already at the forefront of discussions around fairness, transparency, explainability, and responsible data use. These are not peripheral concerns; they are central to building trustworthy AI. Ethical AI requires asking difficult questions: Who might be harmed when a system fails? Whose data is missing? Who is affected by design decisions that seem minor on the surface?

By advocating for human-centered approaches, women in AI are helping shift the field beyond purely performance-driven metrics toward systems that balance innovation with responsibility.

Education, encouragement, and visibility matter

At Heriot-Watt University Dubai, we make a deliberate effort to encourage women to pursue data science, not just as a degree, but as a long-term career. This means creating supportive learning environments, highlighting female role models, and openly discussing the wide range of paths that data science can lead to. Students need to see that success in AI does not follow a single template.

Equally important are spaces where women can connect, share experiences, and feel supported. As an ambassador for Women in Data Science, I have seen how such events play a vital role. They create visibility, build confidence, and remind women that they are not alone. We need more of these initiatives, not as one-off celebrations, but as sustained platforms for mentorship, networking, and growth.

Encouraging women in AI is not about lowering standards or meeting quotas. It is about recognizing that inclusive participation leads to better research, more ethical technologies, and systems that genuinely reflect the societies they shape.

Conclusion

As AI and data science continue to influence our world, we must ask not only what these systems do, but who designs them. Supporting women to study data science, pursue AI careers, and step into leadership roles is essential to building technologies that are fair, responsible, and trustworthy. Through education, visibility, and initiatives, we can help ensure that the future of AI is shaped by many voices.

The future of AI should be one where women do not simply use technology but actively shape it.

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Tech Features

INSIDE THE TECHNOLOGY THAT MAKES HUAWEI FREECLIP THE BEST OPEN-EAR EARBUDS!

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White HUAWEI FreeClip open‑ear earbuds inside an open charging case on a table, with a smartphone, Christmas tree, lights, and wrapped gift boxes in the background.

It has been two years since the debut of the original HUAWEI FreeClip, Huawei’s first-ever open earbuds that took the market by storm. Its massive popularity proved that the world was ready for a new kind of listening experience. The new HUAWEI FreeClip 2 tackles the hard challenges of open-ear acoustics physics head-on, combining a powerful dual-diaphragm driver with computational audio. It delivers depth and clarity, which was once thought impossible with an open-ear design.

Solving the acoustic limitations of open-ear audio alone would have been sufficient to make the HUAWEI FreeClip 2 our pick for best open-ear audio. But it is way more than that.

Comfortable C-Bridge design

The HUAWEI FreeClip 2 earbuds weigh only 5.1 g per bud, a 9% reduction from the previous generation. This lightweight architecture ensures an effortless experience, perfect for long calls, workouts, and commutes, allowing you to wear them all day without fatigue. The comfort bean is 11% smaller than the previous model, yet the design provides a secure fit that prevents the earbuds from falling out, even during intense activity.

Constructed from a new skin-friendly liquid silicone and a shape-memory alloy, the C-bridge is 25% softer and significantly more flexible than its predecessor. Finished with a fine, textured surface, it ensures a comfortable, irritation-free wearing even after extended use.

Adaptive open-ear listening

The acoustic system has been significantly upgraded, featuring a dual-diaphragm driver and a multi-mic call noise cancellation system. This setup not only delivers powerful sound but also maximises space efficiency. That’s why, despite their small size, these earbuds can deliver substantial acoustic performance.

The Open-fit design of the earbuds demands high computing power to maintain sound quality and call clarity. The HUAWEI FreeClip 2 offers ten times the processing power of the previous generation, serving as Huawei’s first earbuds to feature an NPU AI processor for a truly adaptive experience. The new dual-diaphragm driver includes a single dynamic driver with two diaphragms, effectively doubling the sound output within a compact space to provide a significant boost in volume and bass response.

Furthermore, the earbuds dynamically detect surrounding noise and adjust volume and voice levels in real-time. If the environment is too noisy, the system uses adaptive voice enhancement to specifically boost human frequencies, ensuring you never miss a word of a podcast or audiobook. When you return to a quiet environment, the earbuds automatically settle back to a comfortable volume level.

Crystal clear calls

To ensure call quality in chaotic environments, the HUAWEI FreeClip 2 utilises a three-mic system combined with multi-channel DNN (Deep Neural Network) noise cancellation algorithms. This system intelligently identifies and filters out ambient noise. Thanks to the NPU AI processor, the earbuds automatically enhance voice clarity, ensuring your conversations remain crisp regardless of your surroundings.

Battery life and charging

With the charging case, the HUAWEI FreeClip 2 offers a total battery life of 38 hours, allowing users to enjoy music throughout a full week of commuting on a single charge. On their own, the earbuds last for 9 hours—enough for a full workday of uninterrupted calls. For those in a rush, just 10 minutes of fast charging in the case provides up to 3 hours of playback. For added convenience, they support wireless charging and are compatible with watch chargers.

Rated IP57, the earbuds are resistant to sweat and water. They can easily withstand intense workouts or even a downpour.

Connectivity

The earbuds support dual connections and seamless auto-switching across iOS, Android, and Windows. When connected to EMUI devices, you can even switch audio between more than two devices. Additionally, when connected to a PC, the earbuds allow you to answer an incoming call without disconnecting from or interrupting your conference setup.

It is, quite simply, a pair of earphones reliable enough for the gym, the office, and the commute.

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