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Quest Data Intelligence 16.0: New AI Capabilities for erwin Customers

Date: June 25th
Time: 11:00am ET
Location: Microsoft Teams Townhall

Quest Data Intelligence 16.0 introduces new AI-native capabilities that help users find trusted data faster, understand context more easily, and simplify governance workflows across the enterprise.

In this live demo, Quest experts involved behind the scenes will walk through two major additions in the 16.0 release: QuestAI Semantic Assistants and AI Native Policy Manager. You’ll see how these capabilities help business and technical users ask questions in plain English, explore catalog assets, understand lineage, compare data products, and create policies with guided AI assistance.

We’ll explore:

  • QuestAI Semantic Assistants that provide trusted, contextual answers from the data catalog
  • Catalog, lineage, glossary, ownership, marketplace, and stewardship assistance to support faster discovery and stronger metadata management
  • AI Native Policy Manager for guided creation of data classification, access masking, and retention policies
  • AI-suggested asset discovery and automated rule generation to reduce manual effort and support policy enforcement in Snowflake and Databricks
  • Plain-English policy explanations that make governance decisions easier to review, validate, and communicate across teams

Join us for a practical, demo-driven look at how Quest Data Intelligence 16.0 helps erwin customers improve data discovery, support data literacy, reduce manual policy work, and make trusted data easier to find, understand, and manage.

Speaker: Kartik Sridhar, Product Management Director and Glenda O’Keefe, Field Chief Technology Officer

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Enterprise Scheduling – Making Your Models Work While You Sleep

Date: September 15th
Time: 11:00am ET
Location: Microsoft Teams Townhall

Manually running reverse engineering and model comparisons doesn’t scale, especially across larger environments.

In this session, we’ll walk through how to use erwin Data Modeler Workgroup Edition to schedule and automate key modeling tasks. You’ll see how to configure recurring jobs for Reverse Engineering and Complete Compare, store parameters securely, and generate difference reports without manual intervention.

We’ll focus on building a repeatable process so model updates, comparisons, and reporting happen consistently, even when you’re not actively running them.

We’ll walk through:

  • Scheduling Reverse Engineering and Complete Compare jobs
  • Generating and interpreting difference reports to track model changes
  • Storing parameters and credentials securely for automated execution
  • Using the Scheduling UI to monitor and manage multiple models

By the end, you’ll have a clear approach to automating routine modeling tasks and maintaining consistency across environments

Speaker: Andy McGovern, Sr. Principal Consultant

ET

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