A data catalog is a centralized repository that helps users identify, understand, and manage data assets across an organization, making it critical for successful analytics. Traditional data catalogs functioned as data directories, providing metadata such as data type, source, and creation date, but they were often difficult to update manually, making it challenging to track and trust data across multiple systems. Modern data catalogs address these limitations by integrating AI-powered automation, machine learning, and natural language processing (NLP) to streamline metadata management, data discovery, and governance. These next-generation catalogs can automatically tag sensitive data, infer missing metadata, suggest data lineage, and facilitate data cleansing, reducing the burden on data stewards. Additionally, many modern catalogs include collaborative and crowdsourcing features, enabling users to interact with data more intuitively and enhancing trust in analytics-driven decision-making