How to Create a Data Quality Dashboard to Ensure Data Accuracy

This text discusses the importance of ensuring data quality in organizations and provides guidance on creating a data quality dashboard. It explains that raw data, like oil, is not valuable until it's refined into something useful. Ensuring data quality is crucial because insights derived from poor-quality data are unreliable. The text also highlights the regulatory compliance rules and stakeholder trust that depend on high-quality data. The article outlines several key metrics for tracking data quality, including accuracy, completeness, consistency, timeliness, validity, and integrity. It emphasizes the importance of choosing the right metrics based on context and industry. The text then provides a five-step process for creating a data quality dashboard: data retrieval, data preparation, creating visualizations, interpreting data, and continuous improvement. The article concludes by reiterating that high-quality data is essential for organizations to make strategic decisions based on reliable insights. It suggests using a data observability platform like Acceldata to facilitate the process of building and maintaining a data quality dashboard.