Best Data Validation Tools for Databricks Data Intelligence Platform

Compare the Top Data Validation Tools that integrate with Databricks Data Intelligence Platform as of October 2025

This a list of Data Validation tools that integrate with Databricks Data Intelligence Platform. Use the filters on the left to add additional filters for products that have integrations with Databricks Data Intelligence Platform. View the products that work with Databricks Data Intelligence Platform in the table below.

What are Data Validation Tools for Databricks Data Intelligence Platform?

Data validation tools are software tools designed to ensure the accuracy and integrity of data. These tools help identify errors or inconsistencies in data, such as missing values, incorrect formats, or duplicate entries. They work by applying predefined rules and algorithms to check the validity of data against established criteria. Some common types of data validation tools include spell checkers, error flagging systems, and automated testing programs. These tools are essential for maintaining the quality and reliability of data in various industries, including finance, healthcare, and manufacturing. Compare and read user reviews of the best Data Validation tools for Databricks Data Intelligence Platform currently available using the table below. This list is updated regularly.

  • 1
    DataBuck

    DataBuck

    FirstEigen

    DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to: ✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data. ✅ Reduce maintenance costs by minimizing manual intervention. ✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems. By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights. Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world.
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  • 2
    Alteryx

    Alteryx

    Alteryx

    Step into a new era of analytics with the Alteryx AI Platform. Empower your organization with automated data preparation, AI-powered analytics, and approachable machine learning — all with embedded governance and security. Welcome to the future of data-driven decisions for every user, every team, every step of the way. Empower your teams with an easy, intuitive user experience allowing everyone to create analytic solutions that improve productivity, efficiency, and the bottom line. Build an analytics culture with an end-to-end cloud analytics platform and transform data into insights with self-service data prep, machine learning, and AI-generated insights. Reduce risk and ensure your data is fully protected with the latest security standards and certifications. Connect to your data and applications with open API standards.
  • 3
    Ataccama ONE
    Ataccama reinvents the way data is managed to create value on an enterprise scale. Unifying Data Governance, Data Quality, and Master Data Management into a single, AI-powered fabric across hybrid and Cloud environments, Ataccama gives your business and data teams the ability to innovate with unprecedented speed while maintaining trust, security, and governance of your data.
  • 4
    Anomalo

    Anomalo

    Anomalo

    Anomalo helps you get ahead of data issues by automatically detecting them as soon as they appear in your data and before anyone else is impacted. Detect, root-cause, and resolve issues quickly – allowing everyone to feel confident in the data driving your business. Connect Anomalo to your Enterprise Data Warehouse and begin monitoring the tables you care about within minutes. Our advanced machine learning will automatically learn the historical structure and patterns of your data, allowing us to alert you to many issues without the need to create rules or set thresholds.‍ You can also fine-tune and direct our monitoring in a couple of clicks via Anomalo’s No Code UI. Detecting an issue is not enough. Anomalo’s alerts offer rich visualizations and statistical summaries of what’s happening to allow you to quickly understand the magnitude and implications of the problem.‍
  • 5
    Great Expectations

    Great Expectations

    Great Expectations

    Great Expectations is a shared, open standard for data quality. It helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. We recommend deploying within a virtual environment. If you’re not familiar with pip, virtual environments, notebooks, or git, you may want to check out the Supporting. There are many amazing companies using great expectations these days. Check out some of our case studies with companies that we've worked closely with to understand how they are using great expectations in their data stack. Great expectations cloud is a fully managed SaaS offering. We're taking on new private alpha members for great expectations cloud, a fully managed SaaS offering. Alpha members get first access to new features and input to the roadmap.
  • 6
    Talend Data Catalog
    Talend Data Catalog gives your organization a single, secure point of control for your data. With robust tools for search and discovery, and connectors to extract metadata from virtually any data source, Data Catalog makes it easy to protect your data, govern your analytics, manage data pipelines, and accelerate your ETL processes. Data Catalog automatically crawls, profiles, organizes, links, and enriches all your metadata. Up to 80% of the information associated with the data is documented automatically and kept up-to-date through smart relationships and machine learning, continually delivering the most current data to the user. Make data governance a team sport with a secure single point of control where you can collaborate to improve data accessibility, accuracy, and business relevance. Support data privacy and regulatory compliance with intelligent data lineage tracing and compliance tracking.
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