Which statement best describes the data products approach in TELUS AI strategy?

• A. Data sources integrated and governed.
• B. Owners defined but no lineage.
• C. As data products with owners, schemas, lineage, access controls, and event-driven updates.
• D. One-off ETL jobs.

Answer: (C)

Data products approach treats data as a consumer-ready asset rather than a one-off data pipeline. The best description centers on having owners, well-defined schemas, complete data lineage, robust access controls, and event-driven updates because these elements together ensure data is discoverable, trusted, secure, and current for analytics and AI workloads. Assigning owners creates accountability and stewardship; clear schemas keep data consistent across use cases; data lineage provides visibility into sources and transformations, supporting debugging, governance, and model explainability; access controls enforce security and compliance; and event-driven updates keep data fresh, enabling near-real-time insights. Without these aspects, you’re left with a collection of sources or ad-hoc processes that aren’t readily reusable or trustworthy as products. One-off ETL jobs, in particular, miss the scalable, continuous, governed nature that AI initiatives rely on.