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About erwin Data Intelligence

Erwin Data Intelligence is a data management platform from Quest Software that delivers trusted, AI-ready data for modern enterprises. It provides data modeling, data governance, and data lineage capabilities so organizations can achieve successful AI outcomes. The platform supports multiple languages including English, Portuguese, Chinese, French, and German, making it accessible for a global user base. With its comprehensive tools, erwin Data Intelligence helps businesses ensure data quality and compliance while enabling informed decision-making. Key capabilities: data modeling data governance data lineage multi-language support AI readiness Best for: enterprises that need reliable data management to support AI initiatives.

erwin Data Intelligence Details

Vendor
Quest Software
Year Launched
1987
Location
4 Polaris Way, Aliso Viejo, CA 92656, US
Deployment
cloud, on premise, windows
Training Options
documentation, videos, live online, in person
Countries Served
All Countries
Languages
English, Spanish, French, German, Italian, Portuguese
Users
Data Analysts, Data Scientists, Business Analysts, IT Managers
Industries Served
Healthcare, Education, Finance, Retail, Manufacturing, Government, Transportation
Tags
Business Intelligence, Data Management, Data Governance, Data Catalog, Data Lineage, Data Quality, Data Stewardship, Data Modeling, Metadata Management.

erwin Data Intelligence's In-App Market Place

Does erwin Data Intelligence have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

1

Mini Apps

N/A

Pricing Options

Free trial
Free version
Request a quote
Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), JPY (¥), AUD (A$), CAD (C$), CHF (CHF), CNY (¥), SEK (kr), NZD (NZ$), INR (₹), KRW (₩), MXN (Mex$)

Pros & Cons

  • • Comprehensive Data Governance: Provides a centralized platform for managing data governance, including metadata management, data quality, and data lineage.
  • • Enhanced Data Visibility: Improves data visibility and understanding through automated metadata harvesting and data profiling.
  • • Improved Data Quality: Identifies and addresses data quality issues, ensuring data accuracy and consistency.
  • • Self-Service Data Discovery: Empowers users to find and understand data independently, reducing reliance on IT.
  • • Data Lineage and Impact Analysis: Tracks data flow and dependencies, helping to identify potential risks and impacts of data changes.
  • • Data Policy Enforcement: Enforces data policies and standards to maintain data integrity and security.
  • • Integration with Other Tools: Integrates with other data management tools and platforms, providing a unified data management solution.
  • • Complexity: Can be complex to implement and configure, especially for large organizations with diverse data landscapes.
  • • Learning Curve: Requires significant training and learning to fully utilize the tool's capabilities.
  • • Performance Issues: May experience performance issues when dealing with large volumes of data or complex data models.
  • • Vendor Lock-in: Can create vendor lock-in, making it difficult to migrate to other solutions.
  • • Limited Customization: May not be as customizable as some other data management tools.
  • • Dependency on Data Quality: The effectiveness of the tool relies on the quality of the underlying data.

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