List of the Top 8 Data Quality Software for Cloudera in 2025

Ensuring the integrity of Big Data Quality is crucial for maintaining data that is secure, precise, and comprehensive. As data transitions across various IT infrastructures or is housed within Data Lakes, it faces significant challenges in reliability. The primary Big Data issues include: (i) Unidentified inaccuracies in the incoming data, (ii) the desynchronization of multiple data sources over time, (iii) unanticipated structural changes to data in downstream operations, and (iv) the complications arising from diverse IT platforms like Hadoop, Data Warehouses, and Cloud systems. When data shifts between these systems, such as moving from a Data Warehouse to a Hadoop ecosystem, NoSQL database, or Cloud services, it can encounter unforeseen problems. Additionally, data may fluctuate unexpectedly due to ineffective processes, haphazard data governance, poor storage solutions, and a lack of oversight regarding certain data sources, particularly those from external vendors. To address these challenges, DataBuck serves as an autonomous, self-learning validation and data matching tool specifically designed for Big Data Quality. By utilizing advanced algorithms, DataBuck enhances the verification process, ensuring a higher level of data trustworthiness and reliability throughout its lifecycle.

QuerySurge serves as an intelligent solution for Data Testing that streamlines the automation of data validation and ETL testing across Big Data, Data Warehouses, Business Intelligence Reports, and Enterprise Applications while incorporating comprehensive DevOps capabilities for ongoing testing. Among its various use cases, it excels in Data Warehouse and ETL Testing, Big Data (including Hadoop and NoSQL) Testing, and supports DevOps practices for continuous testing, as well as Data Migration, BI Report, and Enterprise Application/ERP Testing. QuerySurge boasts an impressive array of features, including support for over 200 data stores, multi-project capabilities, an insightful Data Analytics Dashboard, a user-friendly Query Wizard that requires no programming skills, and a Design Library for customized test design. Additionally, it offers automated business report testing through its BI Tester, flexible scheduling options for test execution, a Run Dashboard for real-time analysis of test processes, and access to hundreds of detailed reports, along with a comprehensive RESTful API for integration. Moreover, QuerySurge seamlessly integrates into your CI/CD pipeline, enhancing Test Management Integration and ensuring that your data quality is constantly monitored and improved. With QuerySurge, organizations can proactively uncover data issues within their delivery pipelines, significantly boost validation coverage, harness analytics to refine vital data, and elevate data quality with remarkable efficiency.

OvalEdge serves as an affordable data catalog that facilitates comprehensive data governance and ensures compliance with privacy regulations. Additionally, it offers swift and dependable analytics capabilities. By scanning through your organization's databases, business intelligence platforms, and data lakes, OvalEdge establishes a user-friendly and intelligent inventory system. This enables analysts to efficiently locate data and derive valuable insights with ease. Moreover, the platform’s broad array of features empowers users to enhance data accessibility, promote data literacy, and elevate data quality across the organization. Ultimately, OvalEdge stands out as a vital tool for businesses seeking to optimize their data management practices.

iCEDQ is a comprehensive DataOps platform that specializes in monitoring and testing various data processes. This agile rules engine automates essential tasks such as ETL Testing, Data Migration Testing, and Big Data Testing, which ultimately enhances productivity while significantly shortening project timelines for both data warehouses and ETL initiatives. It enables users to identify data-related issues in their Data Warehouse, Big Data, and Data Migration Projects effectively. By transforming the testing landscape, the iCEDQ platform automates the entire process from beginning to end, allowing users to concentrate on analyzing and resolving issues without distraction. The inaugural version of iCEDQ was crafted to validate and test any data volume utilizing its advanced in-memory engine, which is capable of executing complex validations with SQL and Groovy. It is particularly optimized for Data Warehouse Testing, scaling efficiently based on the server's core count, and boasts a performance that is five times faster than the standard edition. Additionally, the platform's intuitive design empowers teams to quickly adapt and respond to data challenges as they arise.

Immuta's Data Access Platform is designed to provide data teams with both secure and efficient access to their data. Organizations are increasingly facing intricate data policies due to the ever-evolving landscape of regulations surrounding data management. Immuta enhances the capabilities of data teams by automating the identification and categorization of both new and existing datasets, which accelerates the realization of value; it also orchestrates the application of data policies through Policy-as-Code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that both technical and business stakeholders can manage and protect data effectively; additionally, it enables the automated monitoring and auditing of user actions and policy compliance to ensure verifiable adherence to regulations. The platform seamlessly integrates with leading cloud data solutions like Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform ensures that data access is secured transparently without compromising performance levels. With Immuta, data teams can significantly enhance their data access speed by up to 100 times, reduce the number of necessary policies by 75 times, and meet compliance objectives reliably, all while fostering a culture of data stewardship and security within their organizations.

Ataccama offers a transformative approach to data management, significantly enhancing enterprise value. By integrating Data Governance, Data Quality, and Master Data Management into a single AI-driven framework, it operates seamlessly across both hybrid and cloud settings. This innovative solution empowers businesses and their data teams with unmatched speed and security, all while maintaining trust, security, and governance over their data assets. As a result, organizations can make informed decisions with confidence, ultimately driving better outcomes and fostering growth.

Data management solutions are primarily employed by teams within large enterprises, requiring a design that emphasizes ease of use, automation, and intelligent features. It is also critical for such software to adhere to various industry regulations and data protection laws. To empower business teams to make well-informed, data-driven strategic choices, the information handled must meet high standards of adequacy, accuracy, consistency, quality, and secure access. The software advocates for a holistic approach to managing data privacy, assuring data quality, supervising test data management, enabling data analytics, and aiding in data modeling. In addition, it efficiently handles growing data volumes using a service engine-based architecture, while also catering to unique data processing requirements through a customizable function framework and a Python adapter. Furthermore, it creates a coherent governance structure that emphasizes data privacy and quality management, thereby bolstering overall data integrity. This comprehensive approach ensures that organizations can depend on this software to adapt to their ever-changing data needs, ultimately fostering enhanced operational efficiency and data reliability.

Acceldata stands out as the sole Data Observability platform that provides total oversight of enterprise data systems. It delivers extensive, cross-sectional insights into intricate and interrelated data environments, effectively synthesizing signals from various workloads, data quality, security, and infrastructure components. With its capabilities, it enhances data processing and operational efficiency significantly. Additionally, it automates the monitoring of data quality throughout the entire lifecycle, catering to rapidly evolving and dynamic datasets. This platform offers a centralized interface to detect, anticipate, and resolve data issues, allowing for the immediate rectification of complete data problems. Moreover, users can monitor the flow of business data through a single dashboard, enabling the detection of anomalies within interconnected data pipelines, thereby facilitating a more streamlined data management process. Ultimately, this comprehensive approach ensures that organizations maintain high standards of data integrity and reliability.