Enhancing Data Management Strategies with a Hybrid Layering Framework in Assessing Data Validation and High Availability Sustainability

Paniti Netinant, Nattapat Saengsuwan, Meennapa Rukhiran () and Sorapak Pukdesree ()
Additional contact information
Paniti Netinant: College of Digital Innovation Technology, Rangsit University, Pathum Thani 12000, Thailand
Nattapat Saengsuwan: College of Digital Innovation Technology, Rangsit University, Pathum Thani 12000, Thailand
Meennapa Rukhiran: Faculty of Social Technology, Rajamangala University of Technology Tawan-ok, Chanthaburi 20110, Thailand
Sorapak Pukdesree: Faculty of Information Technology and Innovation, Bangkok University, Pathum Thani 12120, Thailand

Sustainability, 2023, vol. 15, issue 20, 1-28

Abstract: Individuals and digital organizations deal with a substantial amount of collected data required for performing various data management strategies, such as replacing, upgrading, and migrating existing data from one system to another, while supporting the data’s complexity, authenticity, quality, and precision. Failures in data migration can result in data and service interruptions, financial losses, and reputational harm. This research aims to identify the specific challenges of a data management strategy, develop a comprehensive framework of data migration practices, and assess the efficacy of data validation and high availability for optimizing complex data and reducing the need to minimize errors during data migration. Combining trickle and zero-downtime migration techniques with a layering approach, a hybrid-layering framework was designed to encompass the entire spectrum of data migration techniques, beginning with system requirements and data transformation, rigorous functions, and evaluation metrics for sustainable data validation. The evaluation metric criteria are defined to evaluate data migration based on data consistency, integrity, quality, accuracy, and recall. The experiment demonstrated a real-world scenario involving a logistics company with 222 tables and 4.65 GB of data. The research compared various data migration strategies. The outcomes of the hybrid-layering framework’s examination of the final system’s functionality are satisfactory, emphasizing the critical importance of data migration sustainability to ensure data validity and high availability. This study is useful for individuals and organizations seeking to sustainably improve their data management strategies to minimize disruptions while preserving data integrity.

Keywords: data management; data migration; framework; hybrid layering; evaluation criteria (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/20/15034/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/20/15034/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:20:p:15034-:d:1262584

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().