Alternatives to Quest Trusted Data Management Platform

The Alation Agentic Data Intelligence Platform is designed to transform how enterprises manage, govern, and use data for AI and analytics. It combines search, cataloging, governance, lineage, and analytics into one unified solution, turning metadata into actionable insights. AI-powered agents automate critical tasks like documentation, data quality monitoring, and product creation, freeing teams from repetitive manual work. Its Active Metadata Graph and workflow automation capabilities ensure that data remains accurate, consistent, and trustworthy across systems. With 120+ pre-built connectors, including integrations with AWS, Snowflake, Salesforce, and Databricks, Alation integrates seamlessly into enterprise ecosystems. The platform enables organizations to govern AI responsibly, ensuring compliance, transparency, and ethical use of data. Enterprises benefit from improved self-service analytics, faster data-driven decisions, and a stronger data culture. With industry leaders like Salesforce and 40% of the Fortune 100 relying on it, Alation is proven to help businesses unlock the value of their data.

dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use. With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.

The Actian Data Intelligence Platform is a cloud-native, AI-ready solution aimed at revolutionizing the way organizations discover, comprehend, manage, and trust their data in intricate environments. By consolidating features such as data cataloging, metadata oversight, governance, lineage tracking, observability, and semantic context into a cohesive platform, it establishes a centralized and reliable layer for enterprise data management. Leveraging a federated knowledge graph, the platform fosters intelligent connections between data assets, which allows it to inherently grasp context, yield pertinent search outcomes, and suggest optimal data utilization. This innovative strategy empowers both technical and business users to efficiently locate and utilize trustworthy data, thereby enhancing decision-making processes and boosting operational efficiency. Additionally, the platform performs continuous monitoring of data integrity, enforces governance protocols, and produces automated trust indicators, ensuring that data remains accurate, compliant, and primed for analytics along with AI applications. As a result, organizations can confidently navigate their data landscapes and harness the full potential of their information assets.

The Unity Catalog from Databricks stands out as the sole comprehensive and open governance framework tailored for data and artificial intelligence, integrated within the Databricks Data Intelligence Platform. This innovative solution enables organizations to effortlessly manage structured and unstructured data in various formats, in addition to machine learning models, notebooks, dashboards, and files on any cloud or platform. Data scientists, analysts, and engineers can securely navigate, access, and collaborate on reliable data and AI resources across diverse environments, harnessing AI capabilities to enhance efficiency and realize the full potential of the lakehouse architecture. By adopting this cohesive and open governance strategy, organizations can foster interoperability and expedite their data and AI projects, all while making regulatory compliance easier to achieve. Furthermore, users can quickly identify and categorize both structured and unstructured data, including machine learning models, notebooks, dashboards, and files, across all cloud platforms, ensuring a streamlined governance experience. This comprehensive approach not only simplifies data management but also encourages a collaborative culture among teams.

As a leader in the business arena, it's crucial to have unwavering confidence in your data, ensuring it is thoroughly governed, compliant, and precise. This entails incorporating all data from every source and location without any restrictions. It's important to have a comprehensive grasp of your data resources. Conduct audits to assess risks, compliance, and quality to support your initiatives. Create a detailed inventory of data across all sources and types, fostering a collective understanding of your data resources. Execute a swift, cost-effective, and precise one-time audit of your data assets. Audits for PCI, PII, and PHI are designed to be both fast and thorough. This service approach eliminates the need for any software purchases. Evaluate and audit the quality and duplication of data within all your enterprise data assets, whether they are cloud-native or on-premises. Ensure compliance with global data privacy regulations on a large scale. Actively discover, classify, track, trace, and audit compliance with privacy standards. Additionally, oversee the propagation of PII, PCI, and PHI data while automating the processes for complying with Data Subject Access Requests (DSAR). This comprehensive strategy will effectively safeguard your data integrity and enhance overall business operations.

The erwin Data Marketplace, a component of erwin Data Intelligence by Quest, offers a user-friendly hub for all data consumers, irrespective of their technical background, to explore, choose, and access curated, high-quality data products, datasets, and AI solutions. This self-service model not only streamlines the process of data discovery but also improves data literacy, guarantees governance, and amplifies the overall business value derived from data. Notable functionalities include dynamic filtering options, automated assessments of data value, social feedback through ratings and reviews, and connections to supplementary data insights like mind maps and lineage tracking. Users are able to make side-by-side comparisons of different assets to find the most suitable option for their specific requirements. Data stewards and owners gain advantages through enhanced curation and governance features, which allow them to define data products, manage relationships, classify information, assign searchable tags, and supervise governance responsibilities. Furthermore, integrated workflows simplify the processes of data access requests, approvals, and documentation, all of which are essential for maintaining compliance. As a result, this platform not only fosters a collaborative environment for data sharing but also empowers organizations to fully leverage their data assets for informed decision-making.

Oracle Cloud Infrastructure (OCI) Data Catalog serves as a comprehensive metadata management service tailored for data professionals to facilitate data discovery and governance efforts. It is specifically designed to integrate seamlessly with the Oracle ecosystem, offering features such as an asset inventory, a business glossary, and a unified metastore for data lakes. Fully managed by Oracle, OCI Data Catalog harnesses the extensive capabilities and scalability of Oracle Cloud Infrastructure. Users can take advantage of the robust security, reliability, and performance that Oracle Cloud offers while utilizing the features of OCI Data Catalog. Developers have the option to leverage REST APIs and SDKs to incorporate OCI Data Catalog functionalities into their bespoke applications. Administrators benefit from a reliable system for overseeing user identities and access rights, enabling them to regulate access to catalog objects in accordance with security policies. By exploring data assets available in both Oracle's on-premises and cloud environments, organizations can begin to unlock significant value from their data resources. This comprehensive approach ensures that data governance and management align with organizational goals and compliance requirements.

Aiimi’s Workplace AI platform serves as a comprehensive AI and data management solution designed for enterprises, seamlessly integrating all types of structured and unstructured data within an organization through a unified Virtual Data Layer. This integration facilitates secure and scalable AI-driven functionalities, including search, analysis, automation, and the derivation of actionable insights. By employing advanced technologies such as AI, machine learning, and Retrieval Augmented Generation (RAG), the platform effectively discovers, classifies, enriches, and governs data on a large scale, transforming disjointed information into reliable, “AI-ready” datasets. These datasets empower users with natural language search capabilities, contextual chat and assistant features, sophisticated Q&A functionalities, and visual representations such as knowledge graphs and timelines. Moreover, the platform automates intricate tasks related to data governance, compliance monitoring, enhancement of data quality, handling of DSAR/disclosures, and migration between cloud and legacy systems, all while ensuring the maintenance of access controls, permissions, and detailed audit trails. This comprehensive approach not only streamlines operations but also enhances data accessibility and usability across the enterprise.

Your organization recognizes the significance of data and the importance of making it accessible to business users for optimal effectiveness; however, without proper enterprise data governance, locating, comprehending, and trusting that data may pose challenges. Data360 Govern serves as a comprehensive solution for enterprise data governance, cataloging, and metadata management, enabling you to have confidence in your data's quality, value, and reliability. By automating governance and stewardship responsibilities, it equips you to address vital questions regarding your data's origin, usage, significance, ownership, and overall quality. Utilizing Data360 Govern allows for quicker decision-making regarding data management and usage, fosters collaboration throughout the organization, and ensures users can access the necessary answers promptly. Furthermore, gaining transparency into your organization's data ecosystem empowers you to monitor critical data that aligns with your key business objectives, ultimately enhancing strategic initiatives and fostering growth.

Utilize a unified and governed source of high-quality data for your business intelligence, data warehouse, or other applications to enhance and expedite decision-making processes. With Magnitude Kalido MDM as your comprehensive master data management tool, you can establish and structure essential business information across various domains—such as customers, products, finances, vendors, suppliers, and locations—ensuring the creation and maintenance of precise, integrated, and reliable data that business users can depend on. You can model countless domains within this single solution, which offers domain-agnostic capabilities for modeling, matching, and harmonizing data, ultimately minimizing the need for manual oversight and speeding up data integration from diverse sources. This streamlining facilitates improved business decisions and outcomes, bridging the gap between IT and business functions for enhanced collaboration and communication. By efficiently managing your data, you empower your organization to adapt swiftly to market changes and make informed strategic choices.

Erwin Data Intelligence (erwin DI) integrates data cataloging and data literacy functions to enhance awareness and accessibility of data assets while providing guidance for their usage and establishing safeguards to uphold data policies and best practices. It automatically gathers, transforms, and compiles metadata from a diverse range of data sources, business applications, operational processes, and data models into a centralized catalog. This catalog is then rendered accessible and comprehensible through role-specific, contextual views, empowering stakeholders to make informed strategic decisions based on reliable insights. Furthermore, erwin DI promotes enterprise data governance and supports digital transformation initiatives, alongside any endeavors that depend on data for successful results. It allows for the scheduling of regular metadata scans from a wide variety of data sources, simplifying the mapping of data elements from their origin to their destination, including data in transit, while facilitating seamless data integration across different platforms. In addition, it enables data consumers to identify and explore data that is pertinent to their specific roles, thereby enhancing overall data engagement within the organization. Ultimately, erwin DI serves as a powerful tool for maximizing the value derived from data assets.

Blindata encompasses all the essential components of a comprehensive Data Governance program. Its features, including the Business Glossary, Data Catalog, and Data Lineage, work together to provide a cohesive and thorough perspective on your data. The Data Classification module assigns semantic significance to the data, while the Data Quality, Issue Management, and Data Stewardship modules enhance data reliability and foster trust. Additionally, specific functionalities for privacy compliance are available, such as a registry for processing activities, centralized management of privacy notes, and a consent registry that incorporates Blockchain for notarization. The Blindata Agent facilitates connections to various data sources, enabling the collection of metadata, including data structures like Tables, Views, and Fields, as well as data quality metrics and reverse lineage. With a modular design and fully API-driven architecture, Blindata supports seamless integration with vital business systems, including DBMS, Active Directory, e-commerce platforms, and various Data Platforms. This versatile solution can be deployed as a Software as a Service (SaaS), installed on-premises, or acquired through the AWS Marketplace, making it accessible for a wide range of organizational needs. Its flexibility ensures that businesses can tailor their Data Governance approach to meet specific requirements effectively.

ER/Studio is an enterprise data modeling and architecture solution that helps organizations structure, align, and govern data across complex, distributed environments, including data warehouses, lakehouses, data mesh frameworks, and data vault architectures. It bridges business intent and technical execution through integrated conceptual, logical, and physical modeling, enabling teams to move from strategy to implementation with clarity and control. The result is a consistent architectural foundation that supports analytics, AI initiatives, modernization, regulatory requirements, and operational systems. Collaboration is built into the platform through a centralized, multi-user repository and the web-based Team Server portal. The repository manages version control, role-based permissions, and parallel development so teams can work concurrently while preserving model integrity and full audit history. Team Server extends visibility beyond architects, allowing business and technical stakeholders to review models, explore definitions, and contribute feedback through a browser interface. ER/Studio reinforces governance by embedding standardized definitions, business glossaries, and data dictionaries directly within technical models. Impact analysis provides insight into downstream dependencies before changes are implemented, helping reduce risk and improve coordination. Integrations with Microsoft Purview and Collibra extend metadata into broader governance ecosystems, strengthening lineage tracking, documentation accuracy, and compliance oversight. Available in Standard, Professional, and Enterprise editions, ER/Studio scales from focused modeling teams to enterprise-wide data architecture programs with advanced collaboration and governance requirements.

Dawiso is a comprehensive platform designed to simplify data management by integrating governance with usability for the entire organization. Central to Dawiso is its AI-powered data catalog, which empowers teams to quickly discover and understand trusted data across various systems, reports, and business applications. The platform’s flexible governance capabilities, alongside intuitive documentation apps, make it easy for both technical and non-technical users to collaborate effectively. Dawiso increases confidence in data through visual data lineage that clearly maps connections and dependencies across sources and systems. It supports regulatory compliance with customizable workflows, role-based access controls, and detailed metadata capture. By providing business-friendly tools and structured governance, Dawiso bridges communication gaps and streamlines data-driven decision-making. The platform promotes transparency, security, and usability in data management. Overall, Dawiso is built to enhance collaboration and trust in organizational data assets.

Solid is a data intelligence platform enhanced by AI, aimed at ensuring enterprise data is both dependable and accessible for applications in AI, analytics, and interactive data queries. It automatically identifies, documents, and constructs business-relevant semantic models utilizing a company's existing data, queries, and tools, thereby establishing a reliable foundation that AI systems can depend upon. By assessing the actual usage of data within the organization, it produces validated tables, metrics, relationships, and SQL logic that correspond with genuine business definitions. With offerings like Solid Build and Solid Analyze, teams can streamline semantic modeling, convert natural language inquiries into production-ready SQL, and ensure models are continually refreshed in response to data changes. The platform prioritizes transparency and human involvement, permitting data teams to review, adjust, and confirm AI-generated models instead of merely depending on unclear automation. This approach fosters a collaborative environment where data professionals can enhance the quality and accuracy of the models they work with.

Amplication serves as an open-source platform for backend development, simplifying the processes of creating, managing, and scaling backend services while incorporating industry best practices and standards. By allowing developers to quickly produce production-ready Node.js applications through the definition of data models, roles, and permissions, it automatically generates REST and GraphQL APIs, along with features for authentication, role-based authorization, logging, and an administrative user interface. Additionally, Amplication is designed to be customizable through private plugins, which support the integration of internal tools, workflows, and coding standards. The platform also provides a service catalog, ensuring enhanced visibility and governance, which aids in proactive maintenance and uniformity among development teams. Furthermore, its user-friendly interface encourages collaboration and efficiency, making it a valuable resource for modern backend development.

Quest's erwin Data Catalog is a powerful tool for metadata management that assists organizations in understanding their data assets and their locations, encompassing both static and dynamic data. It provides insights into the available data and metadata related to specific topics, enabling users to swiftly locate relevant sources and resources for analysis and informed decision-making. By automating the tasks associated with harvesting, integrating, activating, and governing enterprise data in line with business needs, erwin Data Catalog enhances accuracy and accelerates the value derived from data governance initiatives and digital transformation projects, such as those involving data warehouses, data lakes, data vaults, and cloud migrations. Effective management of metadata is crucial for sustainable data governance and is essential for any organizational endeavor reliant on data for successful outcomes. The erwin Data Catalog streamlines various functions including enterprise metadata management, data mapping, cataloging, code generation, data profiling, and tracking data lineage, ultimately improving overall data management efficiency. As a result, organizations can better harness their data for strategic advantage and operational excellence.

Amazon DataZone serves as a comprehensive data management solution that empowers users to catalog, explore, share, and regulate data from various sources, including AWS, on-premises systems, and third-party platforms. It provides administrators and data stewards with the ability to manage and oversee data access with precision, guaranteeing that users possess the correct level of permissions and contextual understanding. This service streamlines data access for a diverse range of professionals, such as engineers, data scientists, product managers, analysts, and business users, thereby promoting insights driven by data through enhanced collaboration. Among its notable features are a business data catalog that enables searching and requesting access to published datasets, tools for project collaboration to oversee and manage data assets, a user-friendly web portal offering tailored views for data analysis, and regulated data sharing workflows that ensure proper access. Furthermore, Amazon DataZone leverages machine learning to automate the processes of data discovery and cataloging, making it an invaluable resource for organizations striving to maximize their data utility. As a result, it significantly enhances the efficiency of data governance and utilization across various business functions.

Knowledge Catalog is a modern, AI-powered data catalog developed by Google Cloud to provide comprehensive governance and context for enterprise data. It works by automatically extracting meaning from structured and unstructured data, building a dynamic context graph that connects data assets. This allows organizations to discover, understand, and manage their data more effectively. The platform plays a critical role in improving AI accuracy by grounding models in reliable enterprise data, reducing hallucinations. It offers features such as data lineage tracking, data profiling, and quality measurement to ensure data reliability. Users can also create business glossaries and capture metadata to enhance data organization and accessibility. Knowledge Catalog supports integration with custom data sources and Google Cloud services, making it highly flexible. It enables both traditional analytics and advanced AI applications, including agent-based workflows. The platform also provides powerful search capabilities for locating data resources quickly. By centralizing data context and governance, it reduces operational complexity for data teams. Overall, Knowledge Catalog empowers organizations to build trusted, well-governed data environments.

Informatica's CLAIRE AI represents a sophisticated, enterprise-level artificial intelligence engine that is integrated into the Intelligent Data Management Cloud, designed to automate and expedite various data management activities, ultimately ensuring the delivery of reliable, accurate, and AI-prepared data on a large scale. By leveraging profound metadata insights, CLAIRE minimizes the need for manual intervention, broadens data accessibility, and enhances workflows across several domains including integration, data quality, governance, master data management, and observability, thus enabling autonomous operations through AI agents, natural language processing, and forward-thinking recommendations. This innovative system facilitates features such as CLAIRE Agents, which are capable of independently planning, reasoning, and addressing intricate data issues such as discovery, pipeline creation, quality improvement, and lineage tracking; CLAIRE GPT, a conversational tool that empowers users to engage in natural language inquiries for data exploration, analysis, and task execution; and CLAIRE Copilot, an AI-based assistant that offers contextual advice and actionable suggestions to users. Additionally, the seamless integration of these functionalities transforms the data management landscape, making it more efficient and user-friendly, thereby allowing organizations to harness the full potential of their data resources.

Prospecta Master Data Online, or MDO, is an enterprise master data management platform built to improve data quality, governance, enrichment, and operational trust. The platform helps organizations unify scattered master data across systems, teams, and business domains. MDO is AI-driven and designed to keep enterprise data clean, compliant, complete, actionable, and ready for AI use cases. Its next-generation AI steward, KAI, uses specialized AI agents to guide users through data tasks and scale execution across complex data operations. KAI can structure business requests, enrich information, enforce governance, surface actionable insights, and keep control processes running in the background. MDO supports continuous exploration, improvement, and governance of master data rather than treating trusted data as a one-time cleanup project. The platform is system-agnostic, helping organizations improve confidence in data wherever it lives. Prospecta serves industries such as asset-intensive operations, process industries, product and supply businesses, and retail. By combining master data management, AI stewardship, data governance, data quality, enrichment, and enterprise-wide control, MDO helps organizations make smarter decisions with trusted data.

Entropy Data serves as a marketplace for data products, instilling trust through data contracts and facilitating the discovery of essential data for business needs via an intuitive user interface, semantic search, and advanced filtering options tailored for data products. It efficiently supports the entire data access lifecycle in a self-service manner, allowing consumers to request access, enabling owners to approve or deny these requests, and providing integration options to automate permissions within the data platform. The platform is structured into three main components: Marketplace, Studio, and Governance, which collectively offer data consumers a centralized location for discovering and requesting data products, while granting product owners and developers the tools to create, modify, and oversee their offerings. Additionally, it provides stewards, managers, and platform teams with the means to establish overarching policies and derive valuable insights from the platform. Entropy Data encompasses a wide range of functionalities, managing everything from data products and contracts to access requests, business definitions, assets, domains, teams, source systems, example data, events, certifications, and change management, along with notifications to keep stakeholders informed. This comprehensive approach ensures that all aspects of data product management are effectively addressed, fostering a collaborative environment among all users involved.

Everpure is a modern enterprise data platform built to help organizations manage data as a unified, governed, and AI-ready resource. The platform addresses the challenges of traditional application-centric architectures, where data becomes trapped in silos, governance gaps grow, and AI systems struggle to understand whether information is accurate, connected, or trustworthy. Everpure brings storage, control, automation, intelligence, and service delivery into one enterprise data cloud. Its unified data plane helps virtualize and connect storage across environments, while its intelligent control plane enforces policies and automates operations at scale. The platform also includes data intelligence capabilities that help teams discover, classify, map, and act on enterprise data. Evergreen architecture keeps systems modern through non-disruptive hardware and software updates, reducing the burden of disruptive refresh cycles. Everpure supports a wide range of workloads, including AI, databases, virtualization, cyber resilience, data protection, high-performance computing, cloud storage, and enterprise file services. It is designed to improve reliability, reduce deployment and operating costs, increase utilization, lower energy consumption, and protect against data loss. For enterprises pursuing AI and agentic systems, Everpure provides a trusted data foundation that makes information easier to govern, secure, understand, and use.

Enable data for AI and analytics in a business-friendly manner through smart cataloging, supported by proactive metadata and policy governance. The IBM Watson® Knowledge Catalog serves as a powerful tool for discovering data, models, and more, enhancing the self-service exploration experience. Acting as a cloud-based repository for enterprise metadata, it facilitates the activation of information for AI, machine learning (ML), and deep learning applications. Users can access, curate, categorize, and share data and knowledge assets along with their interconnections, regardless of their location. By organizing, defining, and managing enterprise data effectively, organizations can ensure they have the appropriate context to generate value for various needs, including regulatory compliance and data monetization efforts. Furthermore, it safeguards data integrity, oversees compliance and audit readiness, and fosters client trust through active policy management and the dynamic masking of sensitive information. With user-friendly dashboards and workflows that can be easily shared with colleagues or integrated with analytical tools, businesses can consume and transform data efficiently to keep pace with their operational demands. By leveraging these capabilities, organizations can enhance their decision-making processes and drive innovation across their operations.

DataOS, the flagship product of The Modern Data Company, transforms the way organizations manage, unify, and activate their data at scale by converting raw information into governed, reusable, and AI-compatible data products that enhance insights and decision-making without hindering team productivity. This innovative system provides a flexible, open framework that integrates seamlessly with existing data infrastructures, enabling businesses to find and utilize reliable data products equipped with comprehensive policies, clear ownership, traceability, and a universal semantic layer that standardizes metrics and definitions across various domains. By minimizing complexity and hidden expenses, DataOS accelerates the journey to realizing value from data. Additionally, it offers powerful discovery and search functions, allowing users to navigate through a collection of curated, business-ready data products organized by domain or use case, while also incorporating global metrics and lifecycle management to track the usage, performance, adoption, and return on investment of data products throughout their entire lifecycle. As a result, organizations can make more informed decisions faster, ultimately leading to improved business outcomes.

Auraa is Covasant's innovative, agent-driven data platform designed specifically for Databricks, offering the quickest route to transforming data into AI-ready formats. By utilizing conversational AI features that operate in natural language, businesses can leverage agents to autonomously identify various data sources, construct pipelines, maintain data quality, and register all components in Unity Catalog right from the start. This approach completely removes the need for traditional pipeline code, significantly reduces engineering backlogs, and eliminates months of manual setup efforts. Typically, establishing a data lake on Databricks can take upwards of 18 to 24 months, but with Auraa, the onboarding of the initial data source can be accomplished in less than 15 minutes, the first use case can be launched within hours, and the entire deployment period can be condensed to approximately 8 to 10 weeks, resulting in a cost reduction of up to 70%. Auraa redefines data engineering decisions by managing them as structured, versioned, and governed metadata instead of relying on fragile, hand-coded pipelines. The platform guarantees that the Databricks lakehouse is not only reproducible and auditable but also consistently enhances its capabilities through the use of agents, paving the way for continuous improvement and efficiency in data management.

DataWise is a specialized solution designed specifically for the modernization of SAP data. It effectively connects SAP systems, whether ECC or S/4HANA, with the Databricks Lakehouse, facilitating the conversion of isolated operational data into a reliable and analytics-ready platform that supports real-time decision-making and fosters AI advancements. By utilizing SAP-native connectors and offering prebuilt models for various modules such as SD, MM, PM, Finance, Ariba, and SuccessFactors, DataWise significantly enhances value. It employs automated ELT pipelines to transfer data into Delta Lake, while its MatchX AI-driven data quality engine ensures data cleansing, standardization, deduplication, and entity matching, thereby improving data accuracy and completeness on a large scale. Comprehensive governance is maintained throughout the process via Unity Catalog, which implements fine-grained access controls and tracks data lineage. After the data has been standardized and governed, DataWise enables seamless activation of your SAP data across business intelligence dashboards, machine learning functionalities, and event-driven workflows, all without interfering with your core ERP operations. This innovative approach not only streamlines data accessibility but also empowers organizations to leverage their SAP data for enhanced insights and decision-making.

OvalEdge, a cost-effective data catalogue, is designed to provide end-to-end data governance and privacy compliance. It also provides fast, reliable analytics. OvalEdge crawls the databases, BI platforms and data lakes of your organization to create an easy-to use, smart inventory. Analysts can quickly discover data and provide powerful insights using OvalEdge. OvalEdge's extensive functionality allows users to improve data access, data literacy and data quality.

DvSum, an AI-powered Data Intelligence platform, makes it remarkably easy for data and analytics teams discover, monitor, and govern data. DvSum uses powerful AI-enabled algorithms to automatically catalog, classify, and curate your data and make it available as a Data Catalog. DvSum Data Intelligence will help you propel your enterprise towards its digital- and analytics-enabled transformation goals.

OneTrust Data Use Governance is an AI-ready data governance platform that enables organizations to manage, control, and govern how data is accessed and used across enterprise systems. The solution shifts organizations from manual, data-centric governance processes to policy-centric governance by connecting business policies directly with native controls in data and AI platforms. Instead of relying on lengthy approval workflows, OneTrust automates policy enforcement in real time to support faster, more consistent data access decisions. The platform uses AI-powered classification to analyze both structured and unstructured data while capturing business, regulatory, consent, and data context for machine-readable governance. Organizations can create purpose-based governance policies that are applied consistently from the beginning of data projects through ongoing operations. Machine-readable labels, centralized policy management, and automated enforcement help reduce governance bottlenecks while improving compliance across large-scale environments. The platform also supports auditing of data controls to demonstrate accountability and strengthen governance programs. Integrations with leading technology platforms and service partners allow organizations to extend governance across existing data ecosystems. By automating policy enforcement and enabling responsible data usage, OneTrust Data Use Governance helps enterprises prepare data for AI, analytics, and regulatory compliance.

Effortlessly search, discover, catalog, and access your data with Knoema’s DataHub, which addresses enterprise workflow issues across all business domains by serving as a comprehensive view of any organization's data resources. This platform significantly decreases the time to realize value by eight times when compared to developing solutions internally. It provides smooth connections to both internal databases and third-party data. Users can quickly search to uncover new datasets, ensuring data accessibility during cloud transitions and digital transformation initiatives. The catalog expands daily with new datasets, making it simple to find first-party, public, or third-party information. You can easily add new data subscriptions without added complexity. Filter through your own data, along with licensed third-party information and newly integrated data within Knoema, to obtain the precise data you require. The platform enhances insights and actions tailored to individual user workflows, promoting organizational data literacy. Furthermore, it allows for the integration and embedding of insights into other applications while offering data governance tools to monitor actions and usage effectively. In this way, organizations can not only streamline their data processes but also empower employees to make data-driven decisions.

Graphwise is an advanced AI platform designed to assist businesses in automating their knowledge processes while ensuring confidence in their AI systems by converting disparate data into a reliable semantic foundation. This comprehensive suite enhances the reliability and scalability of generative AI by transforming raw data into contextually rich, AI-compatible assets, implementing intelligent agent-based frameworks, and offering robust AI applications within a cohesive platform. By utilizing Precise GraphRAG, Graphwise transcends mere data fragments, leveraging a governed knowledge graph to anchor every response in established facts, thereby removing inaccuracies and delivering precise, actionable insights. The platform integrates automated modeling, cutting-edge graph technology, semantic search, recommendation systems, taxonomy and ontology management, data automation, graph-centric text mining, and enterprise-ready GraphRAG workflows. Suitable for a variety of applications, it addresses challenges in technical knowledge management, semantic digital twins, compliance intelligence, and scientific knowledge management, showcasing its versatility across numerous business needs. Additionally, Graphwise's innovative approach ensures that organizations can achieve a deeper understanding of their data, ultimately leading to informed decision-making and enhanced operational efficiency.

Octopos serves as a comprehensive platform for data governance and data mesh, empowering large organizations to locate, catalog, and oversee their data assets across various distributed settings while maintaining adherence to compliance, security, and business context. The platform excels in automated metadata harvesting and smart classification, allowing businesses to create a cohesive enterprise data catalog that encompasses business terminology, policies, and data lineage, thus providing teams with a clear and reliable perspective on data origins, usage, and ownership. In addition, it features tools for automated monitoring of data quality, impact analysis, and collaborative workflows that enable data stewards and engineers to swiftly address issues and preserve the integrity of datasets. Moreover, Octopos enhances policy enforcement by integrating technical, business, and compliance criteria into rule sets that can be uniformly applied across cloud, on-premises, and hybrid infrastructures, ultimately minimizing risk and expediting analytics initiatives. By streamlining these processes, Octopos not only improves data management but also fosters a culture of accountability and transparency within organizations.

Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.

Efficiently scan and catalog metadata, uncover and characterize data, while offering comprehensive lineage tracking over millions of datasets. Organize and classify data assets across diverse environments to enhance their value and facilitate reuse. Perform automated scanning across multi-cloud environments, business intelligence tools, ETL processes, and external metadata catalogs, along with various data types. Utilize AI-driven capabilities for domain discovery, data similarity assessment, business term linkages, and tailored recommendations. Monitor data movement with precision, ranging from overarching system perspectives to detailed column-level lineage, accompanied by thorough impact assessments. Access the Data Asset Analytics dashboard to gain insights into asset utilization, enrichment processes, and collaborative efforts. Examine data quality protocols, scorecards, metric clusters, and profiling statistics within their relevant contexts. Engage with shared data intelligence through certifications, ratings and feedback, a Q&A feature, and timely change alerts. What truly distinguishes Informatica is its extensive and robust suite of enterprise-grade data management solutions, ensuring comprehensive support for diverse data needs. With such capabilities, organizations can navigate their data landscapes more effectively and make informed decisions.

Facilitate rapid and secure data sharing by creating an engaging marketplace that allows users to access data with assurance. Promote the responsible distribution of verified data products that drive analytical and AI efforts. Empower teams to independently discover, request, and assess pertinent data through self-service capabilities. Ensure that trusted data sharing is automated in compliance with governance standards. Distribute and highlight curated datasets, AI/ML models, and pipelines from a diverse array of sources. Enhance efficiency by streamlining processes from ordering to delivery while providing easy tracking of operational metrics. Foster improved data literacy through actionable insights and reviews, guiding users on optimal data-driven decisions. Use communication tools like chat, reviews, alerts, and user ratings to share insights and foster collaboration among teams across the organization. A data-sharing marketplace serves as a crucial link between data providers and consumers, allowing for seamless access to valuable information. Such a marketplace empowers organizations to swiftly locate, comprehend, trust, and utilize relevant data through automated processes, ultimately enhancing decision-making capabilities. By bridging the gap between data supply and demand, it cultivates a culture of data-driven innovation and collaboration.

Transform your big data processes and create intelligent knowledge repositories with the Data Lake Governance Center (DGC), a comprehensive platform for managing all facets of data lake operations, including design, development, integration, quality, and asset management. With its intuitive visual interface, you can establish a robust data lake governance framework that enhances the efficiency of your data lifecycle management. Leverage analytics and metrics to uphold strong governance throughout your organization, while also defining and tracking data standards with the ability to receive real-time alerts. Accelerate the development of data lakes by easily configuring data integrations, models, and cleansing protocols to facilitate the identification of trustworthy data sources. Enhance the overall business value derived from your data assets. DGC enables the creation of tailored solutions for various applications, such as smart government, smart taxation, and smart campuses, while providing valuable insights into sensitive information across your organization. Additionally, DGC empowers businesses to establish comprehensive catalogs, classifications, and terminologies for their data. This holistic approach ensures that data governance is not just a task, but a core aspect of your enterprise's strategy.

The Mozilla Data Collective serves as a platform aimed at transforming the AI-data landscape by prioritizing the needs of communities. It empowers data creators and caretakers to share their datasets according to their preferences while maintaining ownership and control over access and conditions. Users are able to upload datasets, select licenses—whether Creative Commons or custom options—define access guidelines, and stipulate requirements for compensation or acknowledgment, all while managing datasets as individuals, cooperatives, or trusts. This platform places a strong emphasis on ethical management, transparency, and community empowerment, standing in opposition to exploitative data extraction practices and fostering fairer participation. With a collection of over 300 high-quality datasets that are both created by and for communities, the platform spans a variety of applications, including multilingual speech-data collections. Additionally, it provides user-friendly tools, such as a public API, to facilitate the integration of these datasets into various applications, thereby enhancing accessibility and usability for developers. Ultimately, Mozilla Data Collective aims to create a more just and inclusive environment for data sharing and usage.

Uncover, record, and oversee your metadata effectively. Dataedo features a range of automated metadata scanners designed to interface with different database technologies, where they extract data structures and metadata to populate your metadata repository. With just a few clicks, you can create a comprehensive catalog of your data while detailing each component. Clarify table and column names with user-friendly aliases, and enrich your understanding of data assets by adding descriptions and custom fields defined by users. Leverage sample data to gain insights into the contents of your data assets, allowing you to grasp the information better prior to utilization and ensuring its quality. Maintain high data standards through data profiling techniques. Facilitate widespread access to data knowledge across your organization. Enhance data literacy, democratize data access, and empower all members of your organization to leverage data more effectively with a simple on-premises data catalog solution. Strengthening data literacy through a well-structured data catalog will ultimately lead to improved decision-making processes.

The Collibra Data Intelligence Cloud serves as your comprehensive platform for engaging with data, featuring an exceptional catalog, adaptable governance, ongoing quality assurance, and integrated privacy measures. Empower your teams with a premier data catalog that seamlessly merges governance, privacy, and quality controls. Elevate efficiency by enabling teams to swiftly discover, comprehend, and access data from various sources, business applications, BI, and data science tools all within a unified hub. Protect your data's privacy by centralizing, automating, and streamlining workflows that foster collaboration, implement privacy measures, and comply with international regulations. Explore the complete narrative of your data with Collibra Data Lineage, which automatically delineates the connections between systems, applications, and reports, providing a contextually rich perspective throughout the organization. Focus on the most critical data while maintaining confidence in its relevance, completeness, and reliability, ensuring that your organization thrives in a data-driven world. By leveraging these capabilities, you can transform your data management practices and drive better decision-making across the board.

Business architecture requires the creation of business process and conceptual models. To align with business goals, create business process and conceptual models. Model the relationships between people, processes, data. Export conceptual models to ER/Studio Data Architect for creating logical models. Quickly verify that business process models comply with BPMN 2.0 specifications. Recognize sensitive data elements to ensure compliance with regulatory requirements.

In today’s data-driven landscape, the quest for data often consumes more time than the actual analysis itself. Azure Data Catalog serves as a comprehensive metadata repository designed to simplify the process of discovering data assets across the enterprise. This fully-managed service empowers users—from analysts to data scientists and developers—to register, enhance, locate, comprehend, and utilize various data sources effectively. You can engage with data using your preferred tools, as Data Catalog enables you to access the information you require and integrate it seamlessly into your workflows. Your data remains where you prefer, while Data Catalog facilitates the exploration and utilization of that data in a user-friendly manner. By promoting widespread adoption and fostering ongoing value creation within your data ecosystem, Data Catalog provides useful insights, practical tips, and unwritten guidelines within a shared platform that benefits all users. With this tool, contributions from everyone are encouraged, leading to a democratization of data asset discovery that enhances collaborative efforts. This collective engagement ultimately transforms how organizations leverage data, paving the way for innovation and efficiency.

Cube serves as a comprehensive platform that establishes a universal semantic layer aimed at streamlining and consolidating the management and analysis of enterprise data. By revolutionizing data management practices, Cube removes the challenges associated with inconsistent models and metrics, thereby providing users with reliable data that is also primed for AI applications. This innovative platform is instrumental for organizations seeking to expand their data infrastructure by harmonizing various data sources and generating uniform metrics applicable across different teams. Tailored for enterprises, Cube enhances analytical capabilities, ensures data accessibility, and facilitates effortless access to AI-driven insights. With Cube, companies can navigate the complexities of data management more effectively than ever before.

Prefect Horizon serves as a managed AI infrastructure platform within the extensive Prefect product ecosystem, enabling teams to deploy, govern, and manage Model Context Protocol (MCP) servers and AI agents on an enterprise level with essential production-ready capabilities like managed hosting, authentication, access control, observability, and governance of tools. By leveraging the FastMCP framework, it transforms MCP from merely a protocol into a comprehensive platform featuring four integrated core components: Deploy, which facilitates the rapid hosting and scaling of MCP servers through CI/CD and monitoring; Registry, which acts as a centralized repository for first-party, third-party, and curated MCP endpoints; Gateway, which provides role-based access control, authentication, and audit logs to ensure secure and governed access to tools; and Agents, which offer user-friendly interfaces that can be deployed in Horizon, Slack, or accessible via MCP, allowing business users to engage with context-aware AI without requiring technical expertise in MCP. This multifaceted approach ensures that organizations can effectively harness AI capabilities while maintaining robust governance and security protocols.

AWS Marketplace serves as a carefully organized digital platform that allows users to explore, buy, implement, and oversee third-party software, data products, AI agents, and services seamlessly within the AWS environment. This marketplace offers a vast array of options spanning various categories, including security, machine learning, business applications, and DevOps tools. By featuring adaptable pricing structures like pay-as-you-go, annual subscriptions, and free trials, AWS Marketplace makes it easier for customers to manage procurement and billing by consolidating expenses into a single AWS invoice. Additionally, it facilitates quick deployment of pre-configured software that can be easily launched on AWS infrastructure. This efficient model not only empowers businesses to spur innovation and reduce time-to-market but also enhances their ability to control software utilization and costs effectively. Ultimately, AWS Marketplace stands as an essential tool for organizations looking to optimize their software management and procurement processes.