Data Profiling

Data profiling is the process of examining a dataset to understand its structure, content, and quality - without necessarily changing anything. It answers: how many records? What is the null rate per field? What are the min, max, and average values? Are there unexpected values or distributions?

Profiling is typically the first step when working with a new data source. Profiling a property listing dataset might reveal that 15% of floor area values are missing, prices cluster in two distinct ranges, and some location fields contain inconsistent country codes - insights that inform your cleaning and validation logic.

Automated profiling tools generate statistical summaries and flag anomalies as data flows through a pipeline. This enables ongoing data observability - detecting when data characteristics shift in a way that might indicate an upstream quality problem before it affects downstream users.