Best Data Validation Tools for Amazon Web Services (AWS)

Find and compare the best Data Validation tools for Amazon Web Services (AWS) in 2025

Use the comparison tool below to compare the top Data Validation tools for Amazon Web Services (AWS) on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    DataBuck Reviews
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    Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
  • 2
    Ataccama ONE Reviews
    Ataccama is a revolutionary way to manage data and create enterprise value. Ataccama unifies Data Governance, Data Quality and Master Data Management into one AI-powered fabric that can be used in hybrid and cloud environments. This gives your business and data teams unprecedented speed and security while ensuring trust, security and governance of your data.
  • 3
    Syniti Knowledge Platform Reviews
    For the first time, it is now possible to capture and retain data attributes such as meaning, usage, lineage, alignment with business outcomes, and ownership, which are often lost after each project, transforming them into valuable knowledge. These essential attributes can be reused effectively to enhance strategic business initiatives that rely on reliable data. By reusing data, you can achieve your objectives more swiftly. Take advantage of the hidden potential within your data to drive success. Unlocking data's potential in relation to your business context can be a game changer. Many of your projects demand similar insights and comprehension of your data, leading to the constant re-creation of the same information. Syniti can provide this critical knowledge at a significantly reduced cost and with improved precision. Rather than discarding your insights, consider unlocking and reapplying the knowledge embedded in your data. By preserving this knowledge, you create a valuable resource for future projects and insights. This approach not only saves time but also enhances overall business intelligence.
  • 4
    Informatica PowerCenter Reviews
    Embrace flexibility with a top-tier, scalable enterprise data integration platform that boasts high performance. It supports every phase of the data integration lifecycle, from initiating the initial project to ensuring the success of critical enterprise deployments. PowerCenter, a platform driven by metadata, expedites data integration initiatives, enabling businesses to access data much faster than through traditional manual coding. Developers and analysts can work together to quickly prototype, revise, analyze, validate, and launch projects within days rather than taking months. Serving as the cornerstone for your data integration efforts, PowerCenter allows for the use of machine learning to effectively oversee and manage your deployments across various domains and locations, enhancing operational efficiency and adaptability. This level of integration ensures that organizations can respond swiftly to changing data needs and market demands.
  • 5
    Talend Data Catalog Reviews
    Talend Data Catalog provides your organization with a single point of control for all your data. Data Catalog provides robust tools for search, discovery, and connectors that allow you to extract metadata from almost any data source. It makes it easy to manage your data pipelines, protect your data, and accelerate your ETL process. Data Catalog automatically crawls, profiles and links all your metadata. Data Catalog automatically documents up to 80% of the data associated with it. Smart relationships and machine learning keep the data current and up-to-date, ensuring that the user has the most recent data. Data governance can be made a team sport by providing a single point of control that allows you to collaborate to improve data accessibility and accuracy. With intelligent data lineage tracking and compliance tracking, you can support data privacy and regulatory compliance.
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