Can the data fabric automate the creation of data products?

Enterprises face a challenging tradeoff between centralized data control, which enhances security and data quality but limits agility and scalability, and decentralized data silos, which offer flexibility but often result in outdated or insecure data. Data products, which require data producers to maintain long-term quality and usability, offer a potential solution by balancing these extremes and leveraging a marketplace model similar to traditional products. However, their success depends on the capabilities and efforts of the producers. The data fabric, an enterprise-wide approach using metadata-driven machine learning and automation, can partially automate data product creation, especially for simple, source-aligned products, by integrating and cataloging datasets. Despite this potential, the creative and complex nature of valuable data products often necessitates human involvement, particularly in transforming and integrating data to meet specific consumer needs. Ultimately, the data fabric and data mesh approaches can complement each other by facilitating different stages of data product development, with the data fabric excelling in automation and the data mesh focusing on domain-specific customization.