Best Data Quality Software for Databricks Data Intelligence Platform

Compare the Top Data Quality Software that integrates with Databricks Data Intelligence Platform as of July 2025

This a list of Data Quality software that integrates 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 is Data Quality Software for Databricks Data Intelligence Platform?

Data quality software helps organizations ensure that their data is accurate, consistent, complete, and reliable. These tools provide functionalities for data profiling, cleansing, validation, and enrichment, helping businesses identify and correct errors, duplicates, or inconsistencies in their datasets. Data quality software often includes features like automated data correction, real-time monitoring, and data governance to maintain high-quality data standards. It plays a critical role in ensuring that data is suitable for analysis, reporting, decision-making, and compliance purposes, particularly in industries that rely on data-driven insights. Compare and read user reviews of the best Data Quality software 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
    Satori

    Satori

    Satori

    Satori is a Data Security Platform (DSP) that enables self-service data and analytics. Unlike the traditional manual data access process, with Satori, users have a personal data portal where they can see all available datasets and gain immediate access to them. Satori’s DSP dynamically applies the appropriate security and access policies, and the users get secure data access in seconds instead of weeks. Satori’s comprehensive DSP manages access, permissions, security, and compliance policies - all from a single console. Satori continuously discovers sensitive data across data stores and dynamically tracks data usage while applying relevant security policies. Satori enables data teams to scale effective data usage across the organization while meeting all data security and compliance requirements.
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  • 3
    Segment

    Segment

    Twilio

    Twilio Segment’s Customer Data Platform (CDP) provides companies with the data foundation that they need to put their customers at the heart of every decision. Per IDC, it’s the #1 CDP in worldwide market share four years in a row (2019-2022). Using Twilio Segment, companies can collect, unify and route their customer data into any system where it’s needed to better understand their customers and create seamless, compelling experiences in real-time. Over 25,000 companies use Twilio Segment to make real-time decisions, accelerate growth and deliver world-class customer experiences.
    Starting Price: $120 per month
  • 4
    Immuta

    Immuta

    Immuta

    Immuta is the market leader in secure Data Access, providing data teams one universal platform to control access to analytical data sets in the cloud. Only Immuta can automate access to data by discovering, securing, and monitoring data. Data-driven organizations around the world trust Immuta to speed time to data, safely share more data with more users, and mitigate the risk of data leaks and breaches. Founded in 2015, Immuta is headquartered in Boston, MA. Immuta is the fastest way for algorithm-driven enterprises to accelerate the development and control of machine learning and advanced analytics. The company's hyperscale data management platform provides data scientists with rapid, personalized data access to dramatically improve the creation, deployment and auditability of machine learning and AI.
  • 5
    Coginiti

    Coginiti

    Coginiti

    Coginiti, the AI-enabled enterprise data workspace, empowers everyone to get consistent answers fast to any business question. Accelerating the analytic development lifecycle from development to certification, Coginiti makes it easy for you to search and find approved metrics for your use case. Coginiti integrates all the functionality you need to build, approve, version, and curate analytics across all business domains for reuse, all while adhering to your data governance policy and standards. Data and analytic teams in the insurance, financial services, healthcare, and retail/consumer package goods industries trust Coginiti’s collaborative data workspace to deliver value to their customers.
    Starting Price: $189/user/year
  • 6
    Decube

    Decube

    Decube

    Decube is a data management platform that helps organizations manage their data observability, data catalog, and data governance needs. It provides end-to-end visibility into data and ensures its accuracy, consistency, and trustworthiness. Decube's platform includes data observability, a data catalog, and data governance components that work together to provide a comprehensive solution. The data observability tools enable real-time monitoring and detection of data incidents, while the data catalog provides a centralized repository for data assets, making it easier to manage and govern data usage and access. The data governance tools provide robust access controls, audit reports, and data lineage tracking to demonstrate compliance with regulatory requirements. Decube's platform is customizable and scalable, making it easy for organizations to tailor it to meet their specific data management needs and manage data across different systems, data sources, and departments.
  • 7
    Collate

    Collate

    Collate

    Collate is an AI‑driven metadata platform that empowers data teams with automated discovery, observability, quality, and governance through agent‑based workflows. Built on the open source OpenMetadata foundation and a unified metadata graph, it offers 90+ turnkey connectors to ingest metadata from databases, data warehouses, BI tools, and pipelines, delivering in‑depth column‑level lineage, data profiling, and no‑code quality tests. Its AI agents automate data discovery, permission‑aware querying, alerting, and incident‑management workflows at scale, while real‑time dashboards, interactive analyses, and a collaborative business glossary enable both technical and non‑technical users to steward high‑quality data assets. Continuous monitoring and governance automations enforce compliance with standards such as GDPR and CCPA, reducing mean time to resolution for data issues and lowering total cost of ownership.
    Starting Price: Free
  • 8
    BigID

    BigID

    BigID

    BigID is data visibility and control for all types of data, everywhere. Reimagine data management for privacy, security, and governance across your entire data landscape. With BigID, you can automatically discover and manage personal and sensitive data – and take action for privacy, protection, and perspective. BigID uses advanced machine learning and data intelligence to help enterprises better manage and protect their customer & sensitive data, meet data privacy and protection regulations, and leverage unmatched coverage for all data across all data stores. 2
  • 9
    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.
  • 10
    Snowplow Analytics

    Snowplow Analytics

    Snowplow Analytics

    Snowplow is a best-in-class data collection platform built for Data Teams. With Snowplow you can collect rich, high-quality event data from all your platforms and products. Your data is available in real-time and is delivered to your data warehouse of choice where it can easily be joined with other data sets and used to power BI tools, custom reports or machine learning models. The Snowplow pipeline runs in your cloud account (AWS and/or GCP), giving you complete ownership of your data. Snowplow frees you to ask and answer any questions relevant to your business and use case, using your preferred tools and technologies.
  • 11
    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.‍
  • 12
    Wiiisdom Ops
    In today’s world, leading organizations are leveraging data to win over their competitors, ensure customer satisfaction and find new business opportunities. At the same time, industry-specific regulations and data privacy rules are challenging traditional technologies and processes. Data quality is now a must-have for any organization but it often stops at the doors of the BI/analytics software. Wiiisdom Ops helps your organization ensure quality assurance within the analytics component, the last mile of the data journey. Without it, you’re putting your organization at risk, with potentially disastrous decisions and automated disasters. BI Testing at scale is impossible to achieve without automation. Wiiisdom Ops integrates perfectly into your CI/CD pipeline, guaranteeing an end-to-end analytics testing loop, at lower costs. Wiiisdom Ops doesn’t require engineering skills to be used. Centralize and automate your test cases from a simple user interface and share the results.
  • 13
    Lightup

    Lightup

    Lightup

    Empower enterprise data teams to proactively prevent costly outages, before they occur. Quickly scale data quality checks across enterprise data pipelines with efficient time-bound pushdown queries — without compromising performance. Proactively monitor and identify data anomalies, leveraging prebuilt DQ-specific AI models — without manual threshold setting. Lightup’s out-of-the-box solution gives you the highest level of data health so you can make confident business decisions. Arm stakeholders with data quality intelligence for confident decision-making. Powerful, flexible dashboards provide transparency into data quality and trends. Avoid data silos by using Lightup’s built-in connectors to seamlessly connect to any data source in your data stack. Streamline workflows by replacing manual, resource-intensive processes with automated and accurate data quality checks.
  • 14
    Foundational

    Foundational

    Foundational

    Identify code and optimization issues in real-time, prevent data incidents pre-deploy, and govern data-impacting code changes end to end—from the operational database to the user-facing dashboard. Automated, column-level data lineage, from the operational database all the way to the reporting layer, ensures every dependency is analyzed. Foundational automates data contract enforcement by analyzing every repository from upstream to downstream, directly from source code. Use Foundational to proactively identify code and data issues, find and prevent issues, and create controls and guardrails. Foundational can be set up in minutes with no code changes required.
  • 15
    IBM Databand
    Monitor your data health and pipeline performance. Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers. Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up. More pipelines, more complexity. Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs. Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery. Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust. Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems.
  • 16
    Acceldata

    Acceldata

    Acceldata

    Acceldata is an Agentic Data Management company helping enterprises manage complex data systems with AI-powered automation. Its unified platform brings together data quality, governance, lineage, and infrastructure monitoring to deliver trusted, actionable insights across the business. Acceldata’s Agentic Data Management platform uses intelligent AI agents to detect, understand, and resolve data issues in real time. Designed for modern data environments, it replaces fragmented tools with a self-learning system that ensures data is accurate, governed, and ready for AI and analytics.
  • 17
    Secuvy AI
    Secuvy is a next-generation cloud platform to automate data security, privacy compliance and governance via AI-driven workflows. Best in class data intelligence especially for unstructured data. Secuvy is a next-generation cloud platform to automate data security, privacy compliance and governance via ai-driven workflows. Best in class data intelligence especially for unstructured data. Automated data discovery, customizable subject access requests, user validations, data maps & workflows for privacy regulations such as ccpa, gdpr, lgpd, pipeda and other global privacy laws. Data intelligence to find sensitive and privacy information across multiple data stores at rest and in motion. In a world where data is growing exponentially, our mission is to help organizations to protect their brand, automate processes, and improve trust with customers. With ever-expanding data sprawls we wish to reduce human efforts, costs & errors for handling Sensitive Data.
  • 18
    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.
  • 19
    Qualytics

    Qualytics

    Qualytics

    Helping enterprises proactively manage their full data quality lifecycle through contextual data quality checks, anomaly detection and remediation. Expose anomalies and metadata to help teams take corrective actions. Automatically trigger remediation workflows to resolve errors quickly and efficiently. Maintain high data quality and prevent errors from affecting business decisions. The SLA chart provides an overview of SLA, including the total number of SLA monitoring that have been performed and any violations that have occurred. This chart can help you identify areas of your data that may require further investigation or improvement.
  • 20
    APERIO DataWise
    Data is used in every aspect of a processing plant or facility, it is underlying most operational processes, most business decisions, and most environmental events. Failures are often attributed to this same data, in terms of operator error, bad sensors, safety or environmental events, or poor analytics. This is where APERIO can alleviate these problems. Data integrity is a key element of Industry 4.0; the foundation upon which more advanced applications, such as predictive models, process optimization, and custom AI tools are developed. APERIO DataWise is the industry-leading provider of reliable, trusted data. Automate the quality of your PI data or digital twins continuously and at scale. Ensure validated data across the enterprise to improve asset reliability. Empower the operator to make better decisions. Detect threats made to operational data to ensure operational resilience. Accurately monitor & report sustainability metrics.
  • 21
    Validio

    Validio

    Validio

    See how your data assets are used: popularity, utilization, and schema coverage. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Find and filter the data you need based on metadata tags and descriptions. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Drive data governance and ownership across your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Automatically generated field-level lineage map to understand the entire data ecosystem. Anomaly detection learns from your data and seasonality patterns, with automatic backfill from historical data. Machine learning-based thresholds are trained per data segment, trained on actual data instead of metadata only.
  • 22
    Cleanlab

    Cleanlab

    Cleanlab

    Cleanlab Studio handles the entire data quality and data-centric AI pipeline in a single framework for analytics and machine learning tasks. Automated pipeline does all ML for you: data preprocessing, foundation model fine-tuning, hyperparameter tuning, and model selection. ML models are used to diagnose data issues, and then can be re-trained on your corrected dataset with one click. Explore the entire heatmap of suggested corrections for all classes in your dataset. Cleanlab Studio provides all of this information and more for free as soon as you upload your dataset. Cleanlab Studio comes pre-loaded with several demo datasets and projects, so you can check those out in your account after signing in.
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