Great Expectations
Great Expectations is an open-source Python library for data validation, documentation, and profiling, primarily used in data engineering and data science workflows. It helps ensure data quality by defining expectations (rules) about data and automatically testing them against datasets, generating reports on data health and anomalies. The tool integrates with data pipelines to catch issues early, supporting various data sources like Pandas DataFrames, SQL databases, and Spark DataFrames.
Developers should learn Great Expectations when building or maintaining data pipelines to enforce data quality standards, reduce errors, and improve reliability in data-driven applications. It is particularly useful in scenarios like ETL processes, data migrations, and machine learning pipelines where consistent, clean data is critical, as it automates validation and provides actionable insights through detailed documentation and alerts.