Data Profiling Model for Assessing the Quality Traits of Master Data Management

Abstract

Enterprise Resource Planning (ERP) and Business Intelligence (BI) system demand progressive rules for maintaining the valuable information about customers, products, suppliers and vendors as data captured through different sources may not be of high quality due to human errors, in many cases. The problem encounters when this information is accessible across multiple systems, within same organization. Providing adequacy to this scattered data is a top agenda for any organization as maintaining the data is complicated, as having high quality data. Master Data Management (MDM) provides a solution to these problems by maintaining “a single reference of truth” with authoritative source of master data (Customer, products, employees etc). Master Data Management (MDM) is a highlighted concern now a day as valid data is the demand for strategic, tactical and operational steering of every organization. The lane to MDM initiates with the quality of data which demands for discovery of master data, profiling and analysis. As inadequacy of data may leads to adverse effects such as wrong decision, loss of time, bad results and unnecessary risk. Thus there is a need to deal with master data and quality of this specific data in a successful and efficient manner. For ensuring this purpose, an approach is proposed in this paper. The research focuses on development of a Model for Data Profiling to assess the level of Quality Traits for Master Data Management. Results are shown by executing the defined steps on TALEND tool over collected dataset. Thus, level of quality traits processes directly correlates with an organization’s ability to make the proper decisions and better outcomes.