Data Catalog: Approaches, Trends, and Future Directions

Abstract

By offering a consolidated inventory of data assets and simplifying data discovery, interpretation, and governance, data catalogs play a crucial role in contemporary data management. This survey article explores diverse methodologies, present tendencies, and potential future directions in the design and implementation of data catalogs. We learn about the benefits, drawbacks, and considerations of various architectural models by studying them. Additionally, we look at new developments that are influencing the development of data catalog design, such as the incorporation of AI and machine learning, the use of semantic web technologies, and the growing popularity of cloud-based architectures. This survey seeks to further knowledge about efficient data catalog structures and offer direction to businesses looking to improve their data management tactics. Organizations can improve data discovery, foster collaboration, and allow informed decision-making in the constantly changing world of data management by embracing the opportunities offered by new technologies and staying up to date on emerging trends.