Enhance Data Quality with Databricks and AI: A Benchmarking Guide for Optimal Standards
Data quality benchmarking is a crucial process that helps organizations assess and improve the accuracy and integrity of their data. It involves measuring an organization’s data against established standards to identify areas needing enhancement. Key concepts include data profiling, which analyzes data patterns and anomalies, and data cleansing, which removes errors and duplicates. Traditional methods ...