Data Cataloging

Data cataloging is the process of creating a comprehensive inventory of the data assets within an organization, including data sources, datasets, databases, tables, columns, and other metadata. The goal of data cataloging is to provide a unified view of all data assets across an organization, making it easier for data analysts, data scientists, and other stakeholders to find and use data.

Data cataloging involves several steps, including data discovery, metadata extraction, data classification, and data mapping. During the discovery phase, GLIDE can scan an organization’s data sources to identify all available data assets. Once the assets have been discovered, metadata is extracted relevant information to each asset, such as its structure, format, and schema. GLIDE can then categorize the data assets based on their content, purpose, and intended use.

Finally, GLIDE can establish relationships between different data assets, helping to identify dependencies and improve data governance. By creating a comprehensive data catalog, organizations can improve their data management practices, promote data discovery and collaboration, and support more informed decision-making.

Customers use GLIDE to establish new or enhance existing Data Catalog solutions, enabling the “Evergreen” state of the data landscape.