Working with data profiling

Dataset profiling provides a comprehensive view of your dataset by combining field-level statistics with relationship analysis. It helps you understand the structure, content, and quality of your data, so you can prepare it for analysis or visualization.

Dataset profiling offers two complementary perspectives:

Profiling provides detailed statistics for each dimension or measure in a dataset, such as data type distributions, missing or null values, unique counts, and duplication rates. Column-level charts and summary metrics highlight distributions, patterns, and anomalies.
Correlation shows how strongly different fields are related, making it easier to identify meaningful patterns, key drivers, or unexpected relationships in your data.

By combining these views, dataset profiling helps you quickly evaluate data quality, detect anomalies, and determine whether a dataset is fit for your analytical goals before you start building visualizations or applying transformations.