1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
-
Updated
Dec 21, 2024 - Python
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Always know what to expect from your data.
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team collaboration.
Visualize and compare datasets, target values and associations, with one line of code.
⚡ Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
🚚 Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
First open-source data discovery and observability platform. We make a life for data practitioners easy so you can focus on your business.
Automatically find issues in image datasets and practice data-centric computer vision.
Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
Monitor the stability of a Pandas or Spark dataframe ⚙︎
Code review for data in dbt
Lineage metadata API, artifacts streams, sandbox, API, and spaces for Polyaxon
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
🚕 A spreadsheet-like data preparation web app that works over Optimus (Pandas, Dask, cuDF, Dask-cuDF, Spark and Vaex)
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.
Installer for DataKitchen's Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.
Swiple enables you to easily observe, understand, validate and improve the quality of your data
Metadata and data identification tool and Python library. Identifies PII, common identifiers, language specific identifiers. Fully customizable and flexible rules
Add a description, image, and links to the data-profiling topic page so that developers can more easily learn about it.
To associate your repository with the data-profiling topic, visit your repo's landing page and select "manage topics."