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Informative Article | Data & Knowledge Engineering | India | Volume 10 Issue 5, May 2021 | Popularity: 4.6 / 10
Ensuring the Accuracy and Completeness of Data: Critical Considerations for Data Migration Success
Sneha Dingre
Abstract: There are critical considerations for ensuring the accuracy and completeness of data during the process of data migration. The paper emphasizes the strategic importance of data migration for organizations undergoing system upgrades, platform changes, and compliance requirements. The paper discusses the consequences of inaccurate or incomplete data, highlighting its impact on analytics, decision - making, reputational damage, and compliance risks. The challenges associated with ensuring data accuracy and completeness are discussed, including issues related to data mapping, transformations, and quality assurance. The paper underscores the holistic approach needed for organizations to successfully navigate the complexities of data migration, ensuring the integrity and accuracy of their valuable data assets.
Keywords: data migration, accuracy, completeness, inaccurate data, data challenges
Edition: Volume 10 Issue 5, May 2021
Pages: 1319 - 1321
DOI: https://www.doi.org/10.21275/SR24314004455
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Data & Knowledge Engineering, India, Volume 8 Issue 9, September 2019
Pages: 420 - 423Survey on Market Rate Prediction Based Algorithms
M. Ranjani, Dr. P. R.Tamilselvi
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Data & Knowledge Engineering, India, Volume 7 Issue 10, October 2018
Pages: 505 - 509An Overview of Text Analysis Technologies and Tools
Akshita Lakkad, Sneh Gajiwala, Dr. Mrs. Neepa Shah
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Data & Knowledge Engineering, Sri Lanka, Volume 7 Issue 10, October 2018
Pages: 1146 - 1150Big Data on Cloud Computing, Challenges and Opportunities - A Conceptual Model
A S. T. Nishadi
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Data & Knowledge Engineering, India, Volume 6 Issue 8, August 2017
Pages: 191 - 192Regulatory and Compliance Data Solution for Banking and E-Commerce
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Data & Knowledge Engineering, Bangladesh, Volume 8 Issue 7, July 2019
Pages: 660 - 663A Study to Evaluate Different Classifiers on the Basis of Performance of the Prediction for Major Common Diseases
Mohammad Munem Shahriar, Atiqul Islam Chowdhury