NADEEF

Author:

Ebaid Amr1,Elmagarmid Ahmed2,Ilyas Ihab F.2,Ouzzani Mourad2,Quiane-Ruiz Jorge-Arnulfo2,Tang Nan2,Yin Si2

Affiliation:

1. Qatar Computing Research Institute and Purdue University

2. Qatar Computing Research Institute

Abstract

We present NADEEF, an extensible, generic and easy-to-deploy data cleaning system. NADEEF distinguishes between a programming interface and a core to achieve generality and extensibility. The programming interface allows users to specify data quality rules by writing code that implements predefined classes. These classes uniformly define what is wrong with the data and (possibly) how to fix it. We will demonstrate the following features provided by NADEEF. (1) Heterogeneity: The programming interface can be used to express many types of data quality rules beyond the well known CFDs (FDs), MDs and ETL rules. (2) Interdependency: The core algorithms can interleave multiple types of rules to detect and repair data errors. (3) Deployment and extensibility: Users can easily customize NADEEF by defining new types of rules, or by extending the core. (4) Metadata management and data custodians: We show a live data quality dashboard to effectively involve users in the data cleaning process.

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 31 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. RLclean: An unsupervised integrated data cleaning framework based on deep reinforcement learning;Information Sciences;2024-11

2. IterClean: An Iterative Data Cleaning Framework with Large Language Models;ACM Turing Award Celebration Conference 2024;2024-07-05

3. BUNNI: Learning Repair Actions in Rule-driven Data Cleaning;Journal of Data and Information Quality;2024-06-24

4. Rock: Cleaning Data by Embedding ML in Logic Rules;Companion of the 2024 International Conference on Management of Data;2024-06-09

5. Automatic Data Repair: Are We Ready to Deploy?;Proceedings of the VLDB Endowment;2024-06

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