Which steps should a healthcare organization take to ensure data quality and meaningful insights in SAP Analytics Cloud?

Performing data profiling is essential for ensuring data quality and obtaining meaningful insights in SAP Analytics Cloud. This process involves examining the data sets to understand their structure, content, relationships, and quality. By assessing these elements, a healthcare organization can identify any inconsistencies, anomalies, or gaps within the data. This deep understanding allows for better data governance and supports the establishment of more accurate analytics models, ensuring that the insights derived from the data are reliable and actionable.

Additionally, data profiling serves as a foundation for other data quality initiatives. It helps organizations recognize what specific quality issues need to be addressed and guides them in defining appropriate data quality rules. This proactive approach enables better decision-making and enhances the overall value derived from the analytics platform.

While utilizing predictive analytics and implementing anonymization are important in their own contexts, they do not inherently focus on assessing and ensuring the quality of the data being analyzed. Establishing data quality rules is certainly critical, but without the initial clarity gained through data profiling, rules may not be effectively tailored to the specific data challenges encountered. Therefore, data profiling stands out as a foundational step that supports the overall data quality framework.