Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
- analytics
- bigquery
- data-modeling
- data-pipelines
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Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
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Data Quality and Observability platform for the whole data lifecycle, from profiling new data sources to full automation with Data Observability. Configure data quality checks from the UI or in YAML files, let DQOps run the data quality checks daily to detect data quality issues.
A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.
Blazingly fast data comparison tool for Python, powered by Rust. Compare massive CSV/Parquet datasets instantly.
Validates tabular CSV data using predefined validations, inspired from its Python homologue "Great Expectations".