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- IoT Data Analytics
- Implementation and migration
How a IoT Data Analytics rollout works
Pilot a measured source from definition through a reviewed result.
Establish ownership
Name the organization, source owner, analyst, steward, reviewer and follow-up owner for a pilot stream.
Configure the source
Record its source identity, effective definition, field mapping and collection basis.
Rehearse readings
Register a normal observation and a repeated request; inspect the operation key, numbered steps and outcome.
Review an anomaly
Compare a reading with its effective bounds, verify the stream read-back and record a decision for the source revision when required.
Reconcile a metric
Select an approved definition, calculate from eligible readings and inspect the persisted result and run.
Correct and follow up
Write a successor revision for a correction, preserve the earlier result and close an assigned action with a resolution.
What the customer provides
Provide sample source records, observed readings, effective measurement rules, known bounds and the people who own each decision. Bring a normal case, an out-of-bound case and a correction with the expected outcome. Identify the source system for snapshots and any external operation receipts.
Changing it afterwards
Version definitions and mappings when the source changes. Keep prior run results, decisions and source history tied to their original revisions. Review the next observation window before expanding beyond the pilot. See get started for the first operating cycle.
Set up IoT Data Analytics your way.
Start free, then use Proto to change fields, steps and approvals before your team goes live.