research-article

BIGQA: Declarative Big Data Quality Assessment

Authors:

Hadi Fadlallah,

Houssein Dhayne,

Rami El Haddad,

Ali JaberAuthors Info & Claims

ACM Journal of Data and Information Quality, Volume 15, Issue 3

Article No.: 27, Pages 1 - 30

https://doi.org/10.1145/3603706

Published: 22 August 2023 Publication History

Abstract

In the big data domain, data quality assessment operations are often complex and must be implementable in a distributed and timely manner. This article tries to generalize the quality assessment operations by providing a new ISO-based declarative data quality assessment framework (BIGQA). BIGQA is a flexible solution that supports data quality assessment in different domains and contexts. It facilitates the planning and execution of big data quality assessment operations for data domain experts and data management specialists at any phase in the data life cycle. This work implements BIGQA to demonstrate its ability to produce customized data quality reports while running efficiently on parallel or distributed computing frameworks. BIGQA generates data quality assessment plans using straightforward operators designed to handle big data and guarantee a high degree of parallelism when executed. Moreover, it allows incremental data quality assessment to avoid reading the whole dataset each time the quality assessment operation is required. The result was validated using radiation wireless sensor data and Stack Overflow users’ data to show that it can be implemented within different contexts. The experiments show a 71% performance improvement over a 1 GB flat file on a single processing machine compared with a non-parallel application and a 75% performance improvement over a 25 GB flat file within a distributed environment compared to a non-distributed application.

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Cited By

Vazquez HGrosboillot V(2024)cuallee: A Python package for data quality checks across multiple DataFrame APIsJournal of Open Source Software10.21105/joss.066849:98(6684)Online publication date: Jun-2024
https://doi.org/10.21105/joss.06684
Zhang T(2024)Construction and Optimization of University Financial Risk Early Warning Model Based on Big Data AnalysisProceedings of the 2024 International Conference on Machine Intelligence and Digital Applications10.1145/3662739.3672303(182-187)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3662739.3672303
Elouataoui WEl Mendili SGahi Y(2024)Active Metadata and Machine Learning based Framework for Enhancing Big Data QualityProceedings of the 7th International Conference on Networking, Intelligent Systems and Security10.1145/3659677.3659707(1-8)Online publication date: 18-Apr-2024
https://dl.acm.org/doi/10.1145/3659677.3659707
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Index Terms

BIGQA: Declarative Big Data Quality Assessment
1. Information systems
  1. Data management systems

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cover image Journal of Data and Information Quality

Journal of Data and Information Quality Volume 15, Issue 3

September 2023

326 pages

ISSN:1936-1955

EISSN:1936-1963

DOI:10.1145/3611329

Editor:
Tiziana Catarci
Sapienza University of Rome, Rome, Italy

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Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 22 August 2023

Online AM: 13 June 2023

Accepted: 12 May 2023

Revised: 16 April 2023

Received: 16 April 2022

Published in JDIQ Volume 15, Issue 3

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Cited By

Vazquez HGrosboillot V(2024)cuallee: A Python package for data quality checks across multiple DataFrame APIsJournal of Open Source Software10.21105/joss.066849:98(6684)Online publication date: Jun-2024
https://doi.org/10.21105/joss.06684
Zhang T(2024)Construction and Optimization of University Financial Risk Early Warning Model Based on Big Data AnalysisProceedings of the 2024 International Conference on Machine Intelligence and Digital Applications10.1145/3662739.3672303(182-187)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3662739.3672303
Elouataoui WEl Mendili SGahi Y(2024)Active Metadata and Machine Learning based Framework for Enhancing Big Data QualityProceedings of the 7th International Conference on Networking, Intelligent Systems and Security10.1145/3659677.3659707(1-8)Online publication date: 18-Apr-2024
https://dl.acm.org/doi/10.1145/3659677.3659707
Bena YIbrahim RMahmood J(2024)Current Challenges of Big Data Quality Management in Big Data Governance: A Literature ReviewAdvances in Intelligent Computing Techniques and Applications10.1007/978-3-031-59711-4_15(160-172)Online publication date: 30-Jun-2024
https://doi.org/10.1007/978-3-031-59711-4_15
Abughazala MMuccini HQadri K(2023)PyDaQu: Python Data Quality Code Generation Based on Data Architecture2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)10.1109/MODELS-C59198.2023.00020(60-64)Online publication date: 1-Oct-2023
https://doi.org/10.1109/MODELS-C59198.2023.00020
Fadlallah HKilany RHaber MJaber A(2023)Addressing the Velocity Challenge of Big Data in Radiation Pollution Monitoring: Implementation and Demonstration2023 IEEE 4th International Multidisciplinary Conference on Engineering Technology (IMCET)10.1109/IMCET59736.2023.10368261(104-109)Online publication date: 12-Dec-2023
https://doi.org/10.1109/IMCET59736.2023.10368261

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