Browse free open source Data Quality tools and projects for Linux below. Use the toggles on the left to filter open source Data Quality tools by OS, license, language, programming language, and project status.

  • Auth0 for AI Agents now in GA Icon
    Auth0 for AI Agents now in GA

    Ready to implement AI with confidence (without sacrificing security)?

    Connect your AI agents to apps and data more securely, give users control over the actions AI agents can perform and the data they can access, and enable human confirmation for critical agent actions.
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  • Cloud tools for web scraping and data extraction Icon
    Cloud tools for web scraping and data extraction

    Deploy pre-built tools that crawl websites, extract structured data, and feed your applications. Reliable web data without maintaining scrapers.

    Automate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
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  • 1
    Dagster

    Dagster

    An orchestration platform for the development, production

    Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust multi-tenant, multi-tool engine that scales technically and organizationally. Dagster as a unified control plane: The ‘single plane of glass’ data teams love to use. Rein in the chaos and maintain control over your data as the complexity scales. Centralize your metadata in one tool with built-in observability, diagnostics, cataloging, and lineage. Spot any issues and identify performance improvement opportunities.
    Downloads: 1 This Week
    Last Update:
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  • 2
    Gretel Synthetics

    Gretel Synthetics

    Synthetic data generators for structured and unstructured text

    Unlock unlimited possibilities with synthetic data. Share, create, and augment data with cutting-edge generative AI. Generate unlimited data in minutes with synthetic data delivered as-a-service. Synthesize data that are as good or better than your original dataset, and maintain relationships and statistical insights. Customize privacy settings so that data is always safe while remaining useful for downstream workflows. Ensure data accuracy and privacy confidently with expert-grade reports. Need to synthesize one or multiple data types? We have you covered. Even take advantage or multimodal data generation. Synthesize and transform multiple tables or entire relational databases. Mitigate GDPR and CCPA risks, and promote safe data access. Accelerate CI/CD workflows, performance testing, and staging. Augment AI training data, including minority classes and unique edge cases. Amaze prospects with personalized product experiences.
    Downloads: 0 This Week
    Last Update:
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  • 3
    A simple little engine to do fuzzy name & address searching. Helps improve data quality and avoids duplicate data entry.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Restful APIs for Data Cleansing

    Restful APIs for Data Cleansing

    This is sister project for osDQ which provide Restful APIs

    (Beta Version) This is sister project for https://sourceforge.net/projects/dataquality/ . It provides Restful APIs for features for data quality and data preparation features. This project will help projects which want embed data quality and data preparation features in their project or UI using restful calls. Data Cleansing APIs Dockerfile: # Pull base image FROM frnde/jetty-9.4.2-jre8-alpine-cet ADD osdq-v0.0.1.war /var/lib/jetty/webapps/osdq.war EXPOSE 8080 Docker Image https://hub.docker.com/r/vreddym/osdq-web/tags
    Downloads: 0 This Week
    Last Update:
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  • Run applications fast and securely in a fully managed environment Icon
    Run applications fast and securely in a fully managed environment

    Cloud Run is a fully-managed compute platform that lets you run your code in a container directly on top of scalable infrastructure.

    Run frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
    Try for free
  • 5
    SDGym

    SDGym

    Benchmarking synthetic data generation methods

    The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device.
    Downloads: 0 This Week
    Last Update:
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  • 6
    Toolsverse ETL Framework

    Toolsverse ETL Framework

    Open source Extract Transform Load engine written in Java

    ETL Framework is a standalone Extract Transform Load engine written in Java. It includes executables for all major platforms and can be easily integrated into other applications. Key Features: * embeddable, open source and free * fast and scalable * uses target database features to do transformations and loads * manual and automatic data mapping * data streaming * bulk data loads * data quality features using SQL, JavaScript? and regex * data transformations Requirements * Java 1.6 and up * At least 4 MB of RAM New in 3.2 (01/18/2013) * Improved auto-update functionality * Bug fixes
    Downloads: 0 This Week
    Last Update:
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