Data virtualization has a privileged position in modern architectures for data discovery and use cases such as data fabric and logical data warehousing. Data virtualization provides unified data access, data integration, and a delivery layer, bridging the gap between distributed IT data management infrastructure and business users and applications. This enables data virtualization systems like the Denodo Platform to collect active metadata about what is happening across the whole data ecosystem, enabling stakeholders to answer the “five W” questions about data access: who is accessing what data, when, where, why, and how. This offers multiple opportunities for automatically deriving intelligence to optimize every step in the data discovery, integration, and preparation process.

In this post, I will describe one of the latest functionalities introduced by Denodo in this area: using artificial intelligence (AI) to provide automatic recommendations for query acceleration based on past activity.

Read more in Originally published on September 9, 2021



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