Data management using dynamic data flow and pattern matching
AssigneeDell Products L.P.
InventorsDhilip S. Kumar, Ajay Maikhuri
Life of this patent
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Abstract
Techniques are disclosed for data management in an information processing system. For example, a method comprises analyzing one or more data sources, wherein each of the one or more data sources comprise a set of metadata and usage information associated with the set of metadata. The method then determines at least one of data definitions and data classifications for the one or more sets of metadata across the one or more data sources, and stores the at least one of data definitions and data classifications for the one or more sets of metadata in a repository.
Claims20
An apparatus comprising:
- at least one processor coupled to at least one memory, the at least one processor, when executing program code, is configured to:
- analyze one or more data sources, wherein each of the one or more data sources comprise a set of metadata and usage information associated with the set of metadata;
- determine at least one of data definitions and data classifications for the one or more sets of metadata across the one or more data sources;
- and
- store the at least one of data definitions and data classifications for the one or more sets of metadata in a repository;
- wherein determining the data definitions for the one or more sets of metadata across the one or more data sources is based in part on a number of matching characters in a first string associated with at least a portion of the set of metadata and a second string associated with a standardized set of metadata;
- wherein determining the data classifications for the one or more sets of metadata across the one or more data sources is based in part on the use of one or more machine learning algorithms;
- and
- wherein the one or more machine learning algorithms comprise one or more decision tree-based algorithms.
A method comprising:
- analyzing one or more data sources, wherein each of the one or more data sources comprise a set of metadata and usage information associated with the set of metadata;
- determining at least one of data definitions and data classifications for the one or more sets of metadata across the one or more data sources;
- and
- storing the at least one of data definitions and data classifications for the one or more sets of metadata in a repository;
- wherein the determining of the data definitions for the one or more sets of metadata across the one or more data sources is based in part on a number of matching characters in a first string associated with at least a portion of the set of metadata and a second string associated with a standardized set of metadata;
- wherein determining the data classifications for the one or more sets of metadata across the one or more data sources is based in part on the use of one or more machine learning algorithms;
- wherein the one or more machine learning algorithms comprise one or more decision tree-based algorithms;
- and
- wherein the analyzing, determining and storing steps are executed by at least one processor coupled to at least one memory comprising executable program code.
A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code, when executed by at least one processor, cause the at least one processor to:
- analyze one or more data sources, wherein each of the one or more data sources comprise a set of metadata and usage information associated with the set of metadata;
- determine at least one of data definitions and data classifications for the one or more sets of metadata across the one or more data sources;
- and
- store the at least one of data definitions and data classifications for the one or more sets of metadata in a repository;
- wherein the determining of the data definitions for the one or more sets of metadata across the one or more data sources is based in part on a number of matching characters in a first string associated with at least a portion of the set of metadata and a second string associated with a standardized set of metadata;
- wherein determining the data classifications for the one or more sets of metadata across the one or more data sources is based in part on the use of one or more machine learning algorithms;
- and
- wherein the one or more machine learning algorithms comprise one or more decision tree-based algorithms.
Dependencies are inferred from the claim text.