It is an exciting time for artificial intelligence (AI). As organizations move from exploring generative AI to deploying it at scale, a new phase of innovation is already emerging: the rise of agentic ...

Effective governance has become a key component of modern data and AI strategies. Without clear policies, accountability, and standards, organizations face business, legal, and ethical risks from ...

Yellowbrick has rebuilt the cloud database software stack by leveraging Kubernetes and modern computer architecture to implement a modern, fully elastic SQL data platform with separate storage and ...

Artificial intelligence has moved from experimental technology to strategic imperative, yet most organizations struggle to scale AI beyond pilot programs. The challenge lies not in the technology ...

Retrieval-ugmented generation (RAG) frameworks provide real-time data access for generative AI systems. RAG works by retrieving data from external sources (often vectorized databases) and combining ...

For years, TDWI research has tracked the evolution of data warehouse architectures as well as the emergence of the data lake. The two have recently converged to form a new and richer data architecture ...

Joint controller is not a new concept in the GDPR. In fact, it has been part of the law since its inception in 2018. However, the definition for the term “joint controller” has been updated as part of ...

The availability of big data, lightning-fast development of data analytics software, and increasingly inexpensive computing power have further heightened the importance of data-driven strategies for ...

Predictive analytics can help companies optimize existing processes, better understand customer behavior, identify unexpected opportunities, and anticipate problems before they happen. Almost all of ...

The biggest companies may say they're increasingly using data to drive their decisions and that they're investing heavily in prioritizing data within their organizations, but in fact, two-thirds of ...

Although the enterprise data landscape is littered with new data technology and offerings, the most pressing problem data teams face today isn’t a lack of technology or skills; it’s not knowing how to ...