Operational Dashboard Development as A Data Quality Monitoring Tools Using Data Deduplication Profiling Result

Abstract

Data quality is a crucial thing presently. Poor data quality can lead to business failure and wrong decision making. One problem that arises when merging several databases is the emergence of data duplication. When merging two applications of a government agency first, it causes 39,3% of data duplication. It can cause some business problems such as storage cost, wasted marketing budget, lack of a single customer view, and lost productivity. For this reason, data quality monitoring needed to monitor and control the duplicated data. This study is a follow-up study focusing on developing a data quality monitoring module using data deduplication profiling results. The method used to develop the dashboard in this study is the operational dashboard development methodology that proposed by Suryatiningsih on her research (2011). The methodology consists of six stages, namely requirement identification, plan process, prototype design, review prototype, implementation process, and system testing. By adjusting to the predefined business rule and KPI, the operational dashboard will help the organization to monitor and control their data quality.