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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: 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…
Reading Time: 3 minutes While cleaning up our archive recently, I found an old article published in 1976 about data dictionary/directory systems (DD/DS). It was written by L. Delport. Nowadays, we no longer use the term DD/DS, but “data catalog” or simply “metadata system”….
Reading Time: 6 minutes Data Governance as a concept and practice has been around for as long as data management has been around. It, however is gaining prominence and interest in recent years due to the increasing volume of data that needs to be…
Reading Time: 5 minutes Consider a business scenario in which a user wants to determine the sales per month at a product level, and the filter conditions vary for different cases and across different users (So it would require multiple ad hoc queries). If…
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: 3 minutes Including external data in many forms of analytics and reporting can provide significant enrichment. New business insights can be discovered that would be impossible to unearth by working exclusively with internal data. The good news is that external data is…
Reading Time: 3 minutes The business value of applying data science in organizations is incontestable. Prescriptive and descriptive models can help improve business and decision making processes. Data science work can be divided into analytical and data preparation work. Examples of data preparation activities…
Reading Time: 4 minutes Over the years I have seen how data virtualisation can simplify data access and significantly improve agility. Given all the benefits this brings, I would most certainly recommend any organisation to add data virtualisation software to their toolbox – particularly…
