HoloClean: Holistic Data Repairs with Probabilistic Inference

Understand

We introduce HoloClean, a framework for holistic data repairing driven by probabilistic inference.

• HoloClean unifies existing qualitative data repairing approaches, which rely on integrity constraints or external data sources, with quantitative data repairing methods, which leverage statistical properties of the input data.
• Given an inconsistent dataset as input, HoloClean automatically generates a probabilistic program that performs data repairing.
• Inspired by recent theoretical advances in probabilistic inference, we introduce a series of optimizations which ensure that inference over HoloClean's probabilistic model scales to instances with millions of tuples.