Current Challenges of Big Data Quality Management in Big Data Governance: A Literature Review
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-59711-4_15
Reference41 articles.
1. Surbakti, F.P.S., Wang, W., Indulska, M., Sadiq, S.: Factors influencing effective use of big data: A research framework. Inf. Manag. 57(1), 103146 (2020). https://doi.org/10.1016/j.im.2019.02.001
2. Byabazaire, J., Hare, G.M.P.O., Delaney, D.T.: End-to-End Data Quality Assessment Using Trust for Data Shared IoT Deployments. IEEE Sens. J. 22(20), 19995–20009 (2022). https://doi.org/10.1109/JSEN.2022.3203853
3. Chirkova, R., Doyle, J., Reutter, J.: Ensuring data readiness for quality requirements with help from procedure reuse. J. Data Inf. Qual. 13(3), 1–15 (2021). https://doi.org/10.1145/3428154
4. Mohammad, B., Alzyadat, W., Al-fayoumi, M.: An approach to improve data quality from big data aspect by sensitive cost and time, pp. 22–26, 2020, https://doi.org/10.1109/ICICS49469.2020.239526
5. Gu, R., et al.: SparkDQ: Efficient generic big data quality management on distributed data-parallel computation. J. Parallel Distrib. Comput. 156, 132–147 (2021). https://doi.org/10.1016/j.jpdc.2021.05.012
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