Acta Scientific Computer Sciences

Mini Review Volume 3 Issue 12

On the Preeminence of Data Quality

Christian Mancas*

DATASIS ProSoft Srl, Bucharest, Romania

*Corresponding Author: Christian Mancas, DATASIS ProSoft Srl, Bucharest, Romania.

Received: October 18, 2021; Published: November 10, 2021

Abstract

This editorial paper pinpoints the paramount importance of data quality in both computer science and information technology, especially nowadays, when data is the key world asset.

Keywords: Data Quality; Data Plausibility; Correctness Proofs; Object-oriented Programming; Structured Programming; Automated Software Testing; Automatic Code Generation; Databases; Constraints; Coherence and Minimality of Constraint Sets; Social Media Platforms; Fake News; Artificial Intelligence; Machine Learning

Bibliography

  1. Aspnes J. “Correctness Proofs”. Univ. Nacional de Colombia, Bogota, verification.pdf (unal.edu.co) (2003).
  2. Augustin F. “Troll farms peddling misinformation on Facebook reached 140 million Americans monthly ahead of the 2020 presidential election, report says”. Insider (2021).
  3. Blokdyk G. “Automated Software Testing A Complete Guide - 2020 Edition”. 5STARCooks, BookShout, Plano, TX (2021).
  4. Costa-Santos C., et al. “COVID-19 surveillance - a descriptive study on data quality issues”. medRxiv (2020).
  5. Dahl OJ., et al. “Structured Programming”. Academic Press, London and NY (1972).
  6. Europa.EU. “COVID-19 open data quality in research papers”. data.europa.eu (2020).
  7. Dijkstra E W. “Notes on Structured Programming”. Techn. Univ. Eindhoven, Math. Dept., NL (1965).
  8. Dilmegani C. “Data Quality Tools and Criteria for Right Tools”. AI Multiple, Data Quality Tools and Criteria for Right Tools (2021).
  9. Freeman E., et al. “Design Patterns (A Brain Friendly Guide)”. O’Reilly, Sebastopol, CA (2004).
  10. “COVID-19 Data Quality and Considerations for Modeling and Analysis”. GAO-20-63SSP, GAO-20-635SP, Accessible Version (2020).
  11. Ghosh P. “Challenges of Data Quality in the AI Ecosystem”. datadiversity.net, Challenges of Data Quality in the AI Ecosystem - DATAVERSITY (2019).
  12. Hansen H L. “In God we trust. All others must bring data”. IBM, Big Data, "In God we trust. All others must bring data". IBM Nordic Blog (2019).
  13. Larsen T. “Healthcare Data Quality: Five Lessons Learned from COVID-19”. HealthCatalyst, Healthcare Data Quality: 5 Lessons from COVID-19 (healthcatalyst.com) (2021).
  14. “The world’s most valuable resource is no more oil, but data”. The Economist (2017).
  15. Liu L T. “When bias begets bias: A source of negative feedback loops in AI systems”. Microsoft Research Blog (2020).
  16. Mabine V J and Balderstone S J. “The World of the Theory of Constraints”. A Review of the International Literature. CRC Press, Boca Raton, FL (1999).
  17. Mancas C. “Conceptual Data Modeling and Database Design: A Completely Algorithmic Approach”. Volume I: The Shortest Advisable Path. Apple Academic Press/CRC Press (Taylor and Francis Group), Palm Bay, FL (2015).
  18. Mancas C. “On the Paramount Importance of Database Constraints”. Journal of Information Technology and Software Engineering 3 (2015): 1-4.
  19. Mancas C. “MatBase Constraint Sets Coherence and Minimality Enforcement Algorithms”. In: Benczur, A., Thalheim, B., Horvath, T. (eds.), Proc. 22nd ADBIS Conf. on Advances in DB and Inf. Syst., LNCS 11019 (2018): 263-277.
  20. Mancas C. “MatBase - a Tool for Transparent Programming while Modeling Data at Conceptual Levels”. In: Proc. 5th Int. Conf. on Comp. Sci. and Inf. Techn. (CSITEC 2019) (2020): 15-27.
  21. Mancas C. “On Modelware as the 5th Generation of Programming Languages”. Acta Scientific Computer Science9 (2020): 24-26.
  22. Mancas C. “Conceptual Data Modeling and Database Design: A Completely Algorithmic Approach”. Volume II: Refinements for an Expert Path. Apple Academic Press/CRC Press (Taylor and Francis Group), Palm Bay, FL (in press) (2022).
  23. McKeen R. “Data as a key asset - maximizing value and minimizing risk in a changing legal landscape”. Financier Worldwide, Data as a key asset - maximising value and minimising risk in a changing legal landscape — Financier Worldwide (2013).
  24. McLaughlin B., et al. “Object-Oriented Analysis and Design: A Brain Friendly Guide to OOA&D: The Best Introduction to Object Orientated Programming”. O’Reilly, Sebastopol, CA (2006).
  25. Mellin W D. In Work with New Electronic ‘Brains’ Opens Field for Army Math Experts. The Times, Clipping from The Times - Newspapers.com (1957).
  26. Olson P. “For Tesla, Facebook and Others, AI’s Flaws Are Getting Harder to Ignore”. Bloomberg Opinion, Artificial Intelligence Ain't That Smart. Look at Tesla, Facebook, Healthcare - Bloomberg (2021).
  27. Rahanti R. “Data Quality: Dimensions, Measurement, Strategy, Management, and Governance”. Quality Press, Milwaukee, WI (2019).
  28. Redman T C. “Data driven: Profiting from Your Most Important Business Asset”. Harvard Business Press, Boston, MA (2008).
  29. Redman T C. “If Your Data Is Bad, Your Machine Learning Tools Are Useless”. Harvard Business Review, If Your Data Is Bad, Your Machine Learning Tools Are Useless (hbr.org) (2018).
  30. Thalheim B and Jaakkola H. “Models as Programs: The Envisioned and Principal Key to True Fifth Generation Programming”. In: Proc. 29th European-Japanese Conf. (EJC 2019) (2019): 170-189.
  31. Upadrashta P. “AI-Enabled Data Quality: Improve Data Quality Across Your Enterprise”. Mastech InfoTrellis, AI Enabled Data Quality for data quality across enterprise (mastechinfotrellis.com) (2021).
  32. Wells JR and Winkler C A. “Facebook Fake News in the Post-Truth World”. Harvard Business School Case (2017): 717-473.
  33. Zhou X and Zafarani R. “A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities”. Argxiv.org (2020).

Citation

Citation: Christian Mancas. “On the Preeminence of Data Quality". Acta Scientific Computer Sciences 3.12 (2021): 26-29.

Copyright

Copyright: © 2021 Christian Mancas. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




Metrics

Acceptance rate35%
Acceptance to publication20-30 days

Indexed In




News and Events


  • Certification for Review
    Acta Scientific certifies the Editors/reviewers for their review done towards the assigned articles of the respective journals.
  • Submission Timeline for Upcoming Issue
    The last date for submission of articles for regular Issues is May 25, 2022.
  • Publication Certificate
    Authors will be issued a "Publication Certificate" as a mark of appreciation for publishing their work.
  • Best Article of the Issue
    The Editors will elect one Best Article after each issue release. The authors of this article will be provided with a certificate of “Best Article of the Issue”.
  • Welcoming Article Submission
    Acta Scientific delightfully welcomes active researchers for submission of articles towards the upcoming issue of respective journals.
  • Contact US