CONDOR

Abstract

We present CONDOR, a tool for managing constraints towards improved data quality. As increasing amounts of heterogeneous data are being generated, integrity constraints are the primary tool for enforcing data integrity. It is essential that an accurate and up-to-date set of constraints exist to validate that the correct application semantics are being enforced. We consider the widely used constraint, functional dependencies (FDs). CONDOR is an integrated system that identifies inconsistent data values (along with suggestions for clean values), and generates repairs to both the data and/or FDs to resolve inconsistencies. We extend the set of FD repair operations proposed in past work, by (1) adding a set of attributes to an FD; (2) transforming an FD to a conditional functional dependency (CFD); and (3) identifying redundant attributes in an FD. Our demonstration will showcase the visualization and interactive features of CONDOR to help users determine the best repairs that resolve the underlying inconsistencies to improve data quality.