System and method for data quality monitors

#The present disclosure relates to systems and techniques for data quality monitoring. More specifically, identifying and resolving data quality issues and presenting data with potential quality issues for user confirmation and resolution.

#Traditional automated data integration may result in various data quality issues. Automatic scripts to search for and resolve such data quality issues may create further data quality problems.

#There is a need to identify and monitor data quality problems automatically and intelligently. In accordance with one aspect, a computer system is configured to include one or more computer processors and a tangible storage device storing one or more module configured for execution by the one or more computer processors in order to: receive, by the computer system, selection of an object type to monitor for possible data quality problems; receive, by the computer system, selection of one or more data quality criterion; determine potential data quality problems by scanning data associated with a plurality of objects of the selected object type in order to determine if the selected one or more data quality criterion are matched by respective objects; generate a user interface indicating the potential data quality problems of respective objects match the selected one or more data quality criterion, and including one or more properties of the matching objects; receive from a user of the computing environment an indication of how to resolve the potential data quality problems; and implement the indicated resolution.

#FIG. 1 illustrates one embodiment of a database system using an ontology.

#FIG. 2 illustrates one embodiment of a process of generating person objects with properties from multiple data sources.

#FIG. 3 illustrates one embodiment of a system for creating data in a data store using a dynamic ontology.

#In order to facilitate an understanding of the systems and methods discussed herein, a number of terms are defined below. The terms defined below, as well as other terms used herein, should be construed to include the provided definitions, the ordinary and customary meaning of the terms, and/or any other implied meaning for the respective terms. Thus, the definitions below do not limit the meaning of these terms, but only provide exemplary definitions.

#Ontology: Stored information that provides a data model for storage of data in one or more databases. For example, the stored data may comprise definitions for object types and property types for data in a database, and how objects and properties may be related.

#Database: A broad term for any data structure for storing and/or organizing data, including, but not limited to, relational databases (Oracle database, mySQL database, etc.), spreadsheets, XML files, and text file, among others.