Enterprise data systems now sit beside ranking, inference and decision pipelines that influence what users see, interact with ...

In today’s fast-changing data landscape, having a strong data system and advanced analytical tools is key to getting valuable insights and staying ahead of the competition. The data lakehouse ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...

Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

Data pipelines are essential for connecting data across systems and platforms. Here's a deep dive into how data pipelines are implemented, what they're used for, and how they're evolving with genAI. A ...

Many enterprise AI initiatives continue to struggle — with 95% failing to deliver ROI due to inadequate data infrastructure ...

In the ever-evolving fields of artificial intelligence (AI) and machine learning, where technological progress hinges on innovation, Rishabh Shanbhag has emerged as a transformative force. His ...