Preserve Raw Evidence and Normalize Records

What you will complete

Raw and normalized fixture layers with traceable run, record, event, entity, and evidence identities.

Make the operating decision

Create a local run manifest before collection with approved scope, input hash, provider or source ID, caps, rubric version, application version, and start time. Give the run a stable internal ID that does not depend on the provider. Save untouched records and error envelopes before normalization.

Assign record, entity, event, and evidence IDs. Retain source URL or identifier, raw index, collection time, original date text, normalized date, date type, public-scope flag, and raw pointer. Evidence objects identify the field path and quote or value that supports a fact.

Keep layers separate: raw source output, normalized records, deterministic analysis, and presentation exports. Missing values become explicit unknown states. No text, blocked page, or absent record is a collection limitation rather than evidence that the organization lacks the researched condition.

Worked fictional example: Harborline Safety Training

Northstar's fictional opening announcement becomes raw record R2, event EVT-NORTHSTAR-OPEN, and evidence E1 for the quoted October opening. Budget, training plan, and decision-maker remain unknown because the source says nothing about them.

Harborline Safety Training, Northstar Distribution, Dockside Logistics, Westbank Storage, all events, excerpts, people, and URLs are fictional fixtures. They do not prove a live source, lead, contact route, or business outcome.

Complete workbook section 4

Use the evidence available for your own bounded job. Write unknown when the evidence is missing, and record the person or action that can resolve it.

1. Create the run manifest before fixture collection.
2. Save untouched success, partial, and error records.
3. Assign stable identities and field-level evidence.
4. Normalize dates while retaining original values and date types.

Open the course workbook PDF or read the workbook details.

Critical gate before continuing

• Raw evidence exists before analysis.
• Every material fact has a source pointer.
• Unknown values remain explicit.
• Errors do not become negative findings.

If a gate fails, repair the current section, narrow the scope, leave the route manual, or record a blocked or stop decision. Continuing is not the only successful learner action.

Common failure modes

• Expanding beyond raw and normalized fixture layers with traceable run, record, event, entity, and evidence identities. before the current artifact can be graded.
• Turning a missing value, unavailable source, or blocked integration into a confident conclusion.
• Treating a prompt instruction as proof that the effective tool or permission boundary works.
• Marking a manual, simulated, or untested route as live.

Check your application