Discovering Conditional Functional Dependencies to Detect Data Inconsistencies

Provided by: VLD Digital
Topic: Big Data
Format: PDF
Poor quality data is a growing and costly problem that affects many enterprises across all aspects of their business ranging from operational efficiency to revenue protection. In this paper, the authors present an approach that efficiently and robustly discovers conditional functional dependencies for detecting inconsistencies in data and hence improves data quality. They evaluate their approach empirically on three real-world data sets, and show that their approach performs well on these sets across several dimensions such as precision, recall, and runtime.

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