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Reading Time: 5 minutes For years, organizations have been managing data by consolidating it into a single data repository, such as a cloud data warehouse or data lake, so it can be analyzed and delivered to business users. Unfortunately, organizations struggle to get this…
Reading Time: 3 minutes In this era of data democratization, organizations are aggressively pursuing data self-service initiatives to empower users across departments with seamless access to data. However, many are not factoring in the needs of a new digital stakeholder: generative artificial intelligence (GenAI)…
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: 3 minutes In a previous post, I talked about some key data virtualization concepts and the types of professionals who can benefit the most from it. Data virtualization is not only beneficial in certain specific areas, but it can really make a…
Reading Time: 8 minutes Learn in 12 minutes: What makes a strong use case for data virtualisation How to come up with a solid Proof of Concept How to prepare your organisation for data virtualisation You’ve already read all about data virtualisation and you’ve…
Reading Time: 4 minutes The awareness of what we know is not just a nice-to-have, but the very essence of knowledge itself. Knowledge does not exist by acts of faith; it requires transparency, trust, and communicability. “Knowing something” means knowing the entire path that…
Reading Time: 6 minutes When creating an enterprise data layer using data virtualization some of the questions that usually came up are, what are the options for metadata management and how to provide data governance now that everything is accessed from a new unified…
