Module 5 • 22 min
Data Platform and Architecture Requirements
Assess whether the data environment can support the proposed platform.Core Concept
Data readiness includes structure, quality, access, permissions, volume, latency, and context. A platform cannot compensate for data that is unavailable when a decision is required or is not authorized for the intended use.
This decision affects the value, delivery effort, operating ownership, and risk profile of the initiative long after the first release.
How to Apply This in Your Organization
Trace the data needed at each workflow step and identify which source, permission, or timing constraint changes the design.
Use one real workflow, its current systems and data, and the people accountable for the outcome. The purpose is a decision-ready recommendation, not a theoretical evaluation.
Decision Checklist
- Confirm data structure and quality.
- Verify authorized access.
- Test latency and volume needs.
Worked Decision Scenario
A team is evaluating data platform and architecture requirements for a current automation initiative. It uses the framework to identify the narrowest viable next step, the dependency that could change the decision, and the owner responsible for resolving it.
A proposed agent is narrowed to a single approved data source because the broader dataset lacks the permissions and freshness needed for production use.
Apply it
Working Exercise
Identify the key data constraints for a platform decision.
Saved locally for this review prototype. Your response will become private account data when the approved course backend is connected.