Data Cleansing Framework for Address and Contact Databases

Abstract

Data cleansing framework for address and contact databases is important because organizations depend on accurate customer, supplier, employee, and partner information for communication, billing, service delivery, reporting, and compliance. Address and contact databases often contain spelling errors, incomplete fields, duplicate records, invalid phone numbers, outdated email addresses, inconsistent formats, and mismatched location details. Existing literature highlights data profiling, format standardization, duplicate detection, address validation, phone and email verification, missing value handling, and rule-based correction as major practices for improving contact data quality. However, many organizations still face challenges such as inconsistent naming patterns, regional address variations, outdated contact details, multiple records for the same person, and weak validation during data entry. This research is important because poor contact data can affect customer communication, delivery accuracy, marketing performance, and operational reliability. This article discusses a data cleansing framework for address and contact databases, focusing on data assessment, standardization rules, validation checks, deduplication, enrichment, error logging, and continuous quality monitoring. The study concludes that an effective cleansing framework improves data accuracy, reduces duplication, strengthens communication reliability, and supports better enterprise information management.