Data Discovery

Data discovery is the process of locating, identifying and selecting relevant data assets from various sources within an organization, in order to facilitate data analysis, reporting and decision-making. It involves understanding the data environment, including data sources, formats, and storage locations, and finding the most appropriate data sets for a specific use case or analytical need.

Data discovery can involve manual methods, such as reviewing data dictionaries, metadata, and data catalogs, or automated methods, such as GLIDE to scan and classify data. The aim is to identify the relevant data sets and attributes that can be used for analysis, ensuring that the data is accurate, reliable and appropriate for the intended purpose.

Using GLIDE for data discovery can improve data management and reduce the time and resources needed for data analysis. It can also help organizations to identify new data sets and sources that may be relevant to their operations or to discover previously unknown relationships between data sets, leading to better insights and decision-making. 

Customers use GLIDE to accelerate and maintain ongoing data discovery, enabling the “Evergreen” state of the data landscape.