The consequences of poor quality data can be vast and influential to business operations, in many ways. Some of the problems created by poor quality data consist of decreased performance levels, reduced system value and slower decision-making. Moreover, data-dependent plans and strategies may be at constant risk and slowly accumulate into financial losses. This is exactly where master data management steps into the spotlight. The increasing need to tackle master data quality issues at enterprise levels, has led MDM to emerge as the basic necessity for companies looking to enhance sustainability levels and enable bottom-line savings.
Data quality management initiatives work towards enabling several long-term business benefits, such as improved manufacturing processes, smoother business efficiencies and better operational processes. Moreover, MDM also supports the management of data quality, with the help of two key functions, namely Historical Master Data Cleansing and Ongoing Data Quality Maintenance.
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