BigID and erwin Data Intelligence by Quest are competing in the data management and security platforms category. BigID is favored for its privacy compliance and data discovery capabilities, while erwin is considered superior for its comprehensive governance features.
Features: BigID is valuable for privacy compliance, automated data mapping, and the ability to scan structured and unstructured data. erwin stands out with detailed metadata management, business glossary capabilities, and comprehensive data lineage.
Room for Improvement: BigID could improve by enhancing support for flash drives, reducing false positives, and delivering more accurate data scans. erwin may benefit from simplifying its deployment process, better integrating with existing tools, and enhancing user-friendliness in its catalog and glossary features.
Ease of Deployment and Customer Service: BigID offers an intuitive setup with strong customer support for quick deployment. erwin provides detailed documentation and training but may take longer to deploy due to its extensive capabilities, attracting technically skilled teams.
Pricing and ROI: BigID presents a competitive pricing model, focusing on quick ROI through efficient privacy compliance. erwin, despite its higher initial cost, offers strong ROI through long-term comprehensive governance and data management benefits.
BigID is a leader in data security, privacy, compliance, and governance: enabling organizations to proactively discover, manage, protect, and get more value from their data in a single platform for data visibility and control. Customers use BigID to reduce their data risk, automate security and privacy controls, achieve compliance, and understand their data across their entire data landscape: including multicloud, hybrid cloud, IaaS, PaaS, SaaS, and on-prem data sources.
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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