Published
Jul 29, 2026
10 • Pages
Build a Medallion Architecture Your AI Can Trust
Every dashboard and every AI agent depends on data someone can vouch for, yet most architectures assume trust instead of measuring it. This paper shows how Qlik Talend Cloud, Qlik Open Lakehouse, and Qlik Cloud Analytics work as one platform to turn raw sources into governed, trust-scored Data Products your teams and your AI can build on with confidence.

IPC Global
Technology
AUTHOR
Igor Alcantara
AUTHORED YEAR
2026
AUDIENCE
Data & Analytics Leaders
INDUSTRY
Technology (Data & Analytics)
TOPIC
Medallion Architecture on Qlik Cloud
White Paper Snapshot
Everything you need to know in under 30 seconds
Results & Impact
Up to 5x Faster Queries
The Adaptive Iceberg Optimizer auto-tunes storage, delivering up to five times faster queries with zero manual maintenance.
~50% Lower Storage Cost
Description: Separating storage from elastic spot compute cuts large-workload storage costs by roughly half.
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Highlights
One Platform, Every Layer of the Stack
Ingestion, quality, storage, cataloging, analytics, and AI run from a single platform, with one catalog and one lineage graph end to end.
Qlik Open Lakehouse stores Apache Iceberg tables in your own S3, readable by Snowflake, Databricks, Spark, and more, no lock-in.
The Adaptive Iceberg Optimizer removes manual tuning while cutting query time and storage cost dramatically.
Choosing between QVD and Open Lakehouse becomes a scale decision, not a platform migration.
Key Topics
Data Products: Where Trust Becomes Measurable
A Gold table nobody can find is wasted work, Data Products package it with an owner, quality score, and lifecycle.
Every dataset carries a Qlik Trust Score, a 0–5 measure built from validity, completeness, and up to five other dimensions.
Visible ownership in an internal marketplace changes team behavior faster than any governance policy ever could.
AI agents answer fluently even when the data is stale or wrong, scoring quality before it reaches the model is the only real defense.

