Break the data product bottleneck.
To deliver data products at the speed your business demands, you’ll need to overcome the challenges holding most organizations back. The Quest Automated Data Product Factory clears the way.
Building a single data product requires coordination across data architects, engineers, governance teams, and business analysts—each with their own tools, timelines, and priorities. Every handoff introduces delays, translation loss, and compounding risk. The longer the cycle, the greater the exposure to errors, governance gaps, and inconsistencies.
Business users know what data they need but can't build it themselves. They're forced to wait in a queue while data teams manually translate requirements into technical specifications.
Teams build redundant data products because there's no easy way to discover what already exists or trust that it meets their needs. The result: sprawling portfolios of one-time-use data products that drain resources.
Watch how you can experience AI-driven data product creation now
Trusted, reusable data products at speed
faster data product delivery
reduction in TCO vs. assembled alternatives
times return on investment
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Knowledge Center
FAQ
Automated Data Product Factory (ADPF) creates new, governed data products from scratch—it's an architect, not a librarian. While data catalogs help you find and organize existing data assets, ADPF uses AI to generate production-ready data products based on natural language descriptions of what you need. You describe the business outcome, and ADPF builds a fully governed, trust-scored data product complete with lineage, business terms, and quality signals embedded from the start.
No. ADPF's conversational interface lets business users describe data needs in natural language—no SQL or technical specifications required. You simply explain what you're trying to accomplish, and ADPF generates a data product that data teams can validate and deploy. This bridges the gap between business intent and technical execution, dramatically reducing the back-and-forth that typically delays data projects.
ADPF assigns every data product a transparent trust score based on nine measurable components including data quality, governance completeness, timeliness, lineage, and user ratings. Unlike subjective quality labels, these scores are quantifiable and explainable—so when an AI model consumes the data, stakeholders can articulate exactly why they trust it. This is critical because AI outcomes are only as reliable as the data feeding them.
What traditionally takes teams up to six months through manual processes can be reduced to days or weeks with ADPF. The platform automates the labor-intensive work of modeling, governance enrichment, and quality validation that typically requires large teams and multiple handoffs. Organizations using ADPF report delivering data products 54% faster compared to traditional approaches.
ADPD is part of the Quest Trusted Data Management Platform, which unifies data modeling, catalog, governance, quality, and marketplace capabilities in a single SaaS solution. It leverages your existing metadata and governance rules from erwin Data Intelligence, so you're building on your current investments rather than starting over. For organizations already using erwin, ADPF extends your foundation into AI-accelerated delivery.
All product metrics and statistics based on Quest Software’s internal analyses and have not been independently verified by a third party.