Speed is power, and in 2025, edge analytics is redefining how businesses harness that power. As enterprises generate massive data streams from IoT sensors, devices, and applications, relying solely on cloud-based Business Intelligence (BI) systems is no longer enough. Traditional models are increasingly strained by bandwidth limitations, rising costs, and scalability challenges. That’s where edge

Introduction: Every year, companies face significant losses from an often-overlooked issue: data debt. It doesn’t appear in financial statements, but it drives delays, inefficiency, and higher costs across the organization. Recent research highlights the scale of the problem: • $15 million per year: The average cost organizations incur due to poor data quality (Gartner). •

For much of the past decade, data science has been seen as one of the most attractive career paths. Organizations built analytics teams, universities added specialized programs, and countless professionals reskilled to step into this growing field. The phrase “data is the new oil” captured the imagination of businesses everywhere. But with the rise of

Continual Learning in ML Systems: Why It Matters for the Future of AI Machine learning systems are often trained once, deployed, and then left static. While this approach works in controlled environments, real-world data is never static. Customer behavior shifts, fraud tactics evolve, and industries face new regulations. In such cases, a model that isn’t

What is Zero-ETL? ETL stands for Extract, Transform, Load, a process used to pull data from different sources, clean and format it, and then load it into a central system like a data warehouse. Traditional ETL pipelines are often complex, slow to build, and require ongoing maintenance as data systems evolve. Zero-ETL takes a different

As we all know, data is one of the most valuable assets for any organization. However, it is only the technical teams (data scientists, analysts, and engineers) who can harness and apply this data the way it is supposed to. This in turn creates a bottleneck: business users have questions, but they must wait for

There aren’t many things that are as intriguing anymore, due to the nature of the rapid technological innovations. However, the convergence of Artificial Intelligence (AI), sensors, and biotechnology is one of those advancements that truly stands out and truly lives up to its hype. Living Intelligence is the fusion of AI, biotechnology, and advanced sensor

What is Agentic AI? Agentic AI refers to systems composed of multiple intelligent agents that can act independently, respond to real-time context, and solve complex problems in a step-by-step manner. These agents use large language models and reasoning tools to make decisions and interact naturally with users. Unlike traditional or rule-based AI, which can only

With 74% of companies striving to be data-driven but only 29% succeeding, it’s clear that traditional centralized data models are falling short. Over 60% of data professionals report delays due to bottlenecks in centralized systems, which slow decision-making and reduce agility. As organizations scale, relying heavily on a central data team creates inefficiencies, which result