Data Profiling Services provide a foundational analysis of datasets to understand their structure, relationships, and content, enabling organizations to evaluate data quality and fitness for use. Data profiling is a form of data analysis used to inspect data and assess quality that utilizes statistical techniques to discover the true structure, content, and quality of a collection of data. These services identify patterns, anomalies, and key metrics that drive quality assessments and remediation efforts. Key Features: * Data Structure Analysis: Examine data attributes, formats, distributions, and relationships to uncover inconsistencies and deviations from expected patterns. * Key Metrics Identification: Measure dimensions such as uniqueness, completeness, and validity, providing a quantitative assessment of data quality. * Anomaly Detection: Highlight outliers, duplicates, and other irregularities that may indicate data quality issues. * Dependency Analysis: Identify relationships between data elements to ensure referential integrity and structural soundness. * Profiling Across Sources: Conduct profiling across databases, files, or data lakes to ensure consistency and uniformity in data representation. * Workflow Integration: Facilitate data quality improvement by generating metadata and recommendations for cleansing, enrichment, and validation workflows.