Erwin Data Intelligence by Quest and Atlan compete in data governance and metadata management. Atlan appears to have the upper hand with more robust features and better engagement.
Features: Erwin Data Intelligence by Quest excels in data cataloging, lineage tracking, and metadata management, providing a comprehensive governance solution. Atlan stands out with its collaborative workspaces, automation capabilities, and integration flexibility, facilitating seamless data operations. Atlan's feature-rich environment positions it as a compelling option for organizations seeking advanced data solutions.
Ease of Deployment and Customer Service: Erwin Data Intelligence by Quest offers a straightforward deployment process with strong customer support to streamline implementation. Atlan provides cloud-based deployment with high scalability and dedicated support for integration, enhancing client satisfaction during onboarding. Atlan’s flexible deployment model provides ease of adaptation for varying business needs.
Pricing and ROI: Erwin Data Intelligence by Quest presents a cost-effective solution with competitive pricing, delivering a solid return on investment through streamlined data management capabilities. Atlan, while commanding a higher setup cost, offers substantial ROI, attributed to its advanced features and superior data handling capabilities. Organizations find Atlan’s price justified by its innovative features and strategic benefits.
Atlan is a comprehensive data management platform designed to enhance data democratization, governance, and collaboration across departments in organizations. It offers a centralized data catalog, intuitive user interface, and robust governance framework to ensure data security and compliance. Users appreciate its efficiency in streamlining processes, promoting better communication, and providing insightful analytics, which drive organizational growth and success.
The erwin Data Intelligence Suite (erwin DI) combines data catalog and data literacy capabilities for greater awareness of and access to available data assets, guidance on their use, and guardrails to ensure data policies and best practices are followed. Automatically harvest, transform and feed metadata from a wide array of data sources, operational processes, business applications and data models into a central data catalog. Then make it accessible and understandable within context via role-based views. This complete metadata-driven approach to data governance facilitates greater IT and business collaboration.
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