Abstract: Various methods, apparatuses/systems, and media for implementing a data book application module is disclosed. The processor identifies an application that needs to be scanned through a data factory; receives inventories of all servers and databases associated with the data factory; scans the servers and databases for receiving inventories of schema, tables and columns associated with the application; and applies artificial intelligence (AI) and/or machine learning (ML) routines and matching algorithms for matching contents of columns to predefined logical terms. The processor also converts the contents of columns into taxonomies associated with the predefined logical terms; matches the taxonomies with the corresponding predefined logical terms; assigns a probability of accuracy value to the matched terms; and populates a data catalog with the matched terms when the assigned probability of accuracy value satisfies a predetermined threshold value.

Abstract: Various methods, apparatuses/systems, and media for implementing a data book application module is disclosed. The processor identifies an application that needs to be scanned through a data factory; receives inventories of all servers and databases associated with the data factory; scans the servers and databases for receiving inventories of schema, tables and columns associated with the application; and applies artificial intelligence (AI) and/or machine learning (ML) routines and matching algorithms for matching contents of columns to predefined logical terms. The processor also converts the contents of columns into taxonomies associated with the predefined logical terms; matches the taxonomies with the corresponding predefined logical terms; assigns a probability of accuracy value to the matched terms; and populates a data catalog with the matched terms when the assigned probability of accuracy value satisfies a predetermined threshold value.

Abstract: Systems and methods for data management are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for data management may include (1) generating a unified model for a plurality of data sources for an organization, the unified model identifying the data sources and a type of data associated with each data source; (2) harvesting data from the data sources; (3) linking the harvested data to the unified model; and (4) receiving and processing a data lineage query against the linked harvested data.

Abstract: Systems and methods for data management are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for data management may include (1) generating a unified model for a plurality of data sources for an organization, the unified model identifying the data sources and a type of data associated with each data source; (2) harvesting data from the data sources; (3) linking the harvested data to the unified model; and (4) receiving and processing a data lineage query against the linked harvested data.