Streamlining Data Quality: A Conceptual Model and Excel-based Tool for Email Duplicate Removal

P.G. Naik; R.S. Kamath; S.S. Jamsandekar; G.R. Naik

Abstract

In the realm of data management, ensuring data quality is paramount for meaningful analysis and decision making. This research paper presents a novel conceptual model and practical tool designed to address the challenge of removing duplicate entries from datasets containing email IDs. The proposed mathematical model for duplicate removal is meticulously developed and subsequently implemented in Microsoft Excel, leveraging Visual Basic for Applications. The Excel interface is enhanced with user-friendly macros organized under the newly added 'Manage Emails' tab, which logically groups tasks into three distinct categories: data cleaning, duplicate removal, and report generation. Specifically, the research focuses on the post-acquisition phase, assuming the availability of email datasets, while acknowledging that data acquisition falls beyond the paper's scope and warrants future exploration. The outcome of this study culminates in the creation of a 'Unique Emails' sheet, housing the pre-processed emails after duplicate removal. This research contributes to the domain of data quality enhancement by providing a practical and efficient solution for the removal of duplicate email entries, enabling organizations and analysts to work with cleaner and more reliable data. The proposed model and tool serve as valuable assets for data pre-processing and analysis, ultimately facilitating more accurate and insightful decision-making processes.

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