Chris Joynt, Director Product Marketing at Securiti AI, has spent more than 15 years working in data and AI, wearing many hats from sales to solutions and now product marketing. This broad experience ...

The Telecom Management Forum (TMF) has released the "2025 Modern Data Architecture Empowering Artificial Intelligence (AI) ...

Srinivasa Sridhar Kavikondala is a seasoned technical architect specializing in data warehousing and cloud solutions, based ...

The core of big data models lies in the synergy of algorithm innovation, computational power support, and data governance to ...

What if you could transform the chaos of unstructured data into actionable insights with just a few tools? Imagine an AI-powered system that not only understands your documents, spreadsheets, and PDFs ...

In this podcast, we talk to Boris Bialek, vice-president and field chief technology officer (CTO) at MongoDB, about how artificial intelligence (AI) can help with discovery and management of ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. By 2020, U.S. healthcare data had reached 2,314 exabytes—15 times more than in 2013—thanks ...

Cloud- and AI-based threats now top the list of concerns for IT and cybersecurity professionals, as they struggle to contain the proliferation of unstructured data across modern environments. “We all ...

In this TechRepublic exclusive, a COO states that successful AI initiatives must have the right unstructured data at the right time. Then, she details the proper unstructured data preparation for AI.

It's not just a mess -- it's a security risk, a compliance hazard, and a missed opportunity. That was the message from data evangelist Karen Lopez during the June 27 session of the "How To Take ...

Conquering the complexities of unstructured data to fuel generative AI (GenAI) apps remains a crucial challenge for many organizations. If said unstructured data can be delivered in clean, canonical ...

Data scientists today face a perfect storm: an explosion of inconsistent, unstructured, multimodal data scattered across silos – and mounting pressure to turn it into accessible, AI-ready insights.