Smart Data Platform — Areas of Concern

Area 1

Data acquisition & ingestion

How does raw data enter the platform?

Area 2

Data refinement

How does raw become AI-ready?

Area 3

Knowledge construction

How does the platform become smart?

Area 4

Model development

How are AI models built and validated?

Area 5

AI request & inference

How is intelligence delivered to consumers?

Area 6

Agentic execution

How does an agent complete a task?

Area 7

Human-in-the-loop

How are high-risk decisions governed?

Area 8

Observability & feedback

How does the platform learn and improve?

Area 9

Governance & compliance

How is trust maintained across all paths?

Purpose

These nine areas of concern form the decision framework for the Smart Data Platform architecture. Each area poses a core governance question that guides technical choices, policy, and operational patterns. Together, they ensure the platform remains compliant, observable, and trustworthy at every stage — from raw data ingestion through agent-driven automation and human review.