Quest Data Modeler

Quest Data Modeler (QDM) is a cloud-native, AI-first data modeling platform that enables organizations to design, manage, and govern data models in a collaborative environment.

It provides a unified workspace where business and technical teams align on shared data definitions and maintain consistency across the enterprise. The platform integrates with cloud data platforms and analytics tools, helping organizations establish a trusted data foundation for reporting, data pipelines, and AI systems.

Why Quest Data Modeler

Modern data environments often span multiple platforms and tools, leading to inconsistent definitions of key business entities (for example, customer or revenue). QDM provides centralized governance controls that ensure consistent, reusable definitions across all downstream systems.

Data modeling is no longer limited to architects. QDM enables collaboration across architects, data engineers, analysts, stewards, and business stakeholders by providing a shared, browser-based environment where teams can simultaneously define business meaning and technical structure. Real-time editing, threaded discussions, and centralized access control eliminate version conflicts and accelerate consensus.

Cloud data warehouses, pipelines, and transformation tools evolve continuously. QDM treats data models as evolving assets-continuously updated, versioned, and governed alongside the systems they represent, ensuring alignment with rapidly changing data platforms.

Key Capabilities

AI-Assisted Modeling

  • Generate models using natural language prompts

  • Receive suggestions for relationships and joins

  • Refactor models and generate documentation automatically

  • Maintain governance through controlled and reviewable AI usage

Real-Time Collaboration

  • Enable multi-user model editing in a browser-based interface

  • Add comments and discussions at the model or object level

  • Maintain shared semantic definitions across teams

  • Prevent version conflicts through centralized access control

Enterprise Mart Repository

  • Store and manage models in a centralized repository

  • Support check-in and check-out workflows

  • Track version history and changes

  • Compare and merge models with conflict resolution

  • Enforce organizational standards at scale

End-to-End Modeling Support

  • Create conceptual, logical, and physical data models

  • Maintain traceability across modeling layers

  • Perform forward and reverse engineering with industry platforms

Integration with Modern Data Stack

  • Connect with tools such as dbt, Git, and REST APIs

  • Align modeling workflows with existing engineering practices

  • Integrate modeling with data governance and quality processes

QTDMP Integration

  • Integrate with Quest Trusted Data Management Platform (QTDMP) for unified governance, quality, and cataloging workflows

  • Leverage governance, catalog, and data quality capabilities across the data lifecycle

  • Support end-to-end data product development

Key Benefits

  • Accelerated Model Development

    Reduce modeling time by leveraging AI-assisted generation and intelligent suggestions, enabling faster delivery and iteration.

  • Improved Model Quality

    Provide a governed environment where teams can review, validate, and compare models to identify issues early in the design phase.

  • Modernization Without Disruption

    Support existing modeling investments by enabling integration with desktop-based tools and repositories, allowing gradual adoption of cloud capabilities.

  • Enhanced Governance and Control

    Combines AI-driven productivity with enterprise governance practices to ensure all changes are controlled, reviewable, and compliant with standards.

  • Increased Team Productivity

    Enables cross-functional teams to collaborate efficiently within a unified environment, reducing handoffs and duplication of effort.

  • Foundation for Trusted Data

    Transforms data models into governed, reusable assets that improve consistency and reliability across reports, pipelines, and AI-driven applications.

Related topics

The following table provides links to key topics for getting started with QDM. For details about the user interface, refer to the Quest Data Modeler topic.

Subscriptions

Quest Data Modeler is a module in Quest Trusted Data Management Platform. To use it, your organization must have an active subscription. For more information, see the following topics:

Assigning Roles to Users

Users must also have the QDM user role assigned under Settings > Access Control > Roles. For more information, refer to the Assigning a role to a user topic.

System Requirements

QDM supports latest versions of the following web browsers:

  • Microsoft Edge

  • Google Chrome

  • Mozilla Firefox

  • Apple Safari
Quest erwin Mart Portal Permissions

Access to QDM models is managed through roles and permissions in the Quest erwin Mart Portal. For more information, refer to the Manage Profiles and Assign Permissions to Users or Groups topics.

Best Practices

Provides recommended approaches for working with QDM, including modeling strategy, naming conventions, and design guidelines, to help create clear, consistent, and maintainable models. For more information, refer to the Quest Data Modeler Best Practices topic.

Quest Data Modeler AI FAQs

Answers common questions about QDM AI features, including how they work and how to use them effectively. For more information refer to the Quest Data Modeler AI FAQs topic.