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Reading Time: 5 minutes Generative AI has opened up new possibilities for organizations that want to be creative and fearless with their data. In my first post in this series, I introduced ways that data fabric and retrieval augmented generation (RAG) can support large…
Reading Time: 3 minutes Leveraging enterprise data for generative AI and large language models presents significant challenges related to data silos, quality inconsistencies, privacy and security concerns, compliance with data regulations, capturing domain-specific knowledge, and mitigating inherent biases. Organizations must navigate the complexities of…
Reading Time: 4 minutes Providing timely, intuitive access to information has been top-of-mind for many companies, and their data professionals in particular. Over the past few decades, we have been storing up data and generating even more of it than we have known what…
Reading Time: 3 minutes Last year, I was involved in a proof-of-concept (POC) in a major financial institution. It was mid-2023, and Generative artificial intelligence (Gen AI) was already reaching what’s known as Gartner’s ‘peak of inflated expectations.’ The POC was for a data…
Reading Time: 3 minutes As we move deeper into 2024, it is imperative for data management leaders to look in their rear-view mirrors to assess and, if needed, refine their data management strategies. One thing is clear; if data-centric organizations want to succeed in…
Reading Time: 6 minutes The emergence of Large Language Models (LLMs) and Generative AI marks a significant leap in technology, promising to deliver transformational automation and innovation across diverse industries and use cases. Having said that, as everyone races to develop next generation AI…
