Example 2: Natural-language queries for business executives

The same nine ADP governed data products that ground the CVX agent can also power a self-service natural-language query experience for business users who need answers without writing SQL.

Amazon Quick Suite (including Amazon Quick Desktop, the desktop client) connects to Amazon DataZone as a data source, inheriting the subscription and governance model DataZone enforces. A business user who has been granted access to the relevant ADP consumer project through DataZone can ask questions in plain English — the Quick Suite layer translates them to SQL against the underlying Athena tables and returns the answer.

This pattern is a demonstration of the enabling thesis at a non-technical scale: the same foundation deploy that supports ML model training and conversational agents also supports executive-level ad hoc queries, because all three consumption patterns subscribe to the same governed data products through the same DataZone catalog.

Example queries

The operational questions posed in Analytical data platform for automotive OEMs on AWS's "Why ADP" section translate directly to this pattern:

• "Which vehicles have degraded battery SoH after winter?" — vehicle_telemetry_aggregated + vehicle_identity, filtered to a seasonal date range

• "Which customers have open service records and unresolved OTA failures?" — customer_360 + service_records + ota_campaigns, cross-product join on customer_id and vin

• "What is the average energy efficiency delta after the most recent OTA campaign by model year?" — energy_usage + ota_campaigns + vehicle_identity

A business executive using Amazon Quick Desktop can ask these questions through a conversational interface backed by Quick Suite’s natural-language-to-SQL layer. They do not need to know the Athena table names or partition keys; Quick Suite resolves those from the DataZone catalog metadata — the same schemas and documented descriptions that ADP publishes when it registers each data product in the domain.

Scope and framing

This is a demo-scale illustration of the pattern, not a production BI deployment guide. Production deployments of Amazon Quick Suite require IAM Identity Center configuration, DataZone group-to-reader-group mapping, and reader-group provisioning in the Quick namespace — steps that are outside the scope of this chapter and depend on the organization’s existing IAM Identity Center setup.

The value of the pattern is not the deployment complexity; it is the observation that the same adp-{stage}-data-consumers IAM Identity Center group that controls Athena and notebook access to ADP products also controls which users can subscribe to those products in Amazon Quick Suite — one access-control model governs all consumption patterns.