Showing 3 open source projects for "data quality cleansing"

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  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

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    Ship Agents Faster

    Transform your applications and workflows into powerful agentic systems at global scale.

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  • 1
    whylogs

    whylogs

    The open standard for data logging

    whylogs is an open-source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to track changes in their dataset Create data constraints to know whether their data looks the way it should. Quickly visualize key summary statistics about their datasets. whylogs profiles are the core of the whylogs library. They capture key statistical properties of data, such as the distribution (far beyond...
    Downloads: 7 This Week
    Last Update:
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  • 2
    Union Pandera

    Union Pandera

    Light-weight, flexible, expressive statistical data testing library

    ...Validate the functions that produce your data by automatically generating test cases for them. Integrate seamlessly with the Python ecosystem. Overcome the initial hurdle of defining a schema by inferring one from clean data, then refine it over time. Identify the critical points in your data pipeline, and validate data going in and out of them. Build confidence in the quality of your data by defining schemas for complex data objects.
    Downloads: 8 This Week
    Last Update:
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  • 3
    Elementary

    Elementary

    Open-source data observability for analytics engineers

    Elementary is an open-source data observability solution for data & analytics engineers. Monitor your dbt project and data in minutes, and be the first to know of data issues. Gain immediate visibility, detect data issues, send actionable alerts, and understand the impact and root cause. Generate a data observability report, host it or share with your team. Monitoring of data quality metrics, freshness, volume and schema changes, including anomaly detection. ...
    Downloads: 0 This Week
    Last Update:
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