A SUBJECTIVE DATA QUALITY METRICS TO ASSESS RETAIL INVENTORY DATASET

• Main Author: ZULKIFFLI, PUTERI NOR ILYA NADIA
• Format: Thesis
• Language: English
• Published: 2023
• Subjects: T Technology (General)
• Online Access: http://utpedia.utp.edu.my/id/eprint/24630/1/PuteriNorIlyaNadiaZulkiffli_17007904.pdf; http://utpedia.utp.edu.my/id/eprint/24630/

Data quality management remains a challenge in every organization where high-quality data is needed to help decision-making. Poor data quality management has a negative impact resulting in financial loss, loss of privacy, business process failure, and inefficiencies, creating legal and security risks and loss of reputation. Much research has been conducted on the data quality areas, but not many studies specifically focus on the retailing area with dedicated dimensions, sub-dimensions, and measurement parameters to assess the inventory dataset from a data collector point of view. The problem in retailers’ inventory has led to a loss in profit even though most retailers have implemented a system. However, without a proper assessment that consists of dimensions with their own sub-dimensions at the early stage, the data with quality would not be acquired.