You're tasked with improving data integrity. How do you prioritize tasks as a data quality manager?
Improving data integrity is a critical task that requires a methodical and strategic approach. As a data quality manager, you're responsible for ensuring the accuracy, consistency, and reliability of your organization's data. This involves a series of steps to identify areas of weakness, implement improvements, and monitor outcomes. Prioritizing these tasks effectively is essential to maintain high standards of data quality and to support informed decision-making within your organization. By focusing on key areas such as data assessment, cleansing processes, governance frameworks, and ongoing monitoring, you can create a robust data management strategy that upholds the integrity of your data assets.
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Zachary JakaitisData Governance Lead - RTX
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Mohammed Irfan CDMP, PSMIIData architect with expertise in data management, data modeling, data quality, data governance, integration, ETL and…
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Luiz CruzAnalista de Dados Pleno | Data Specialyst | Business Intelligence Analyst | Power BI | Big Query | Looker Studio | SQL…