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Files, devices, and where work actually lives
In this lesson
Files, devices, and where work actually lives
Classify local storage, cloud storage, and shared network drives according to access time, availability constraints, and visibility to collaborators, applying the distinctions reco
You'll be able to
- Classify local storage, cloud storage, and shared network drives according to access time, availability constraints, and visibility to collaborators, applying the distinctions recognized in DigComp 2.2 area 1[^3].
- Evaluate which storage location is most appropriate for a given AI workflow scenario (e.g., training data on cloud versus inference artifacts on local devices) by weighing trade-offs such as "data on the cloud is available anytime and from anywhere, but has implications for access time"[^3].
- Explain to a colleague or stakeholder where a specific file resides and who holds access permissions, demonstrating the ability to organize and retrieve digital resources in a structured environment[^3].
- Apply basic data organization tools (folders, headers, metadata tags) to keep track of files across multiple storage locations, ensuring you can retrieve them when needed during job-seeking, project handoffs, or compliance audits[^3].
- Create a simple decision matrix or checklist that maps file types (datasets, model checkpoints, logs, reports) to appropriate storage backends, supporting reproducible and collaborative AI development.