datawebotExtraction guide
Map product observations into a data pipeline
A manual handoff recipe to adapt in your own environment.
01 / INPUTSource product records + authorized internal IDs
02 / YOUR WORKFLOWMap fields → inspect → hand off
03 / OUTPUTA proposed catalog mapping
Keep the right fields.
Manual data handoff| Field / step | Input | Rule |
|---|---|---|
| Source record | Product and variant identifiers | Keep identity as strings. |
| Namespace | Source ID + internal ID | Preserve both and record match evidence. |
| Evidence | source_url + retrieved_at | Keep the original observation attached. |
02 / Inspect the example
| Variant | SKU | Example price | Example availability |
|---|---|---|---|
| Small / Navy | DEMO-TEE-S-NV | USD 32.00 | Example: available |
| Medium / Navy | DEMO-TEE-M-NV | USD 32.00 | Example: available |
| Medium / Sand | DEMO-TEE-M-SD | USD 34.00 | Example: unavailable |
| Large / Navy | DEMO-TEE-L-NV | USD 32.00 | Example: unknown |
All names, identifiers, prices and availability values are fictional. They do not describe a merchant’s catalog or inventory.
Before you use the output
Product extraction is separate from customer identity resolution and event collection.
Check one record first.
Start with the smallest useful scope. Compare the returned record with its source, confirm variant identity and inspect missing fields before applying the mapping to a larger dataset.
Keep extraction warnings and the retrieval timestamp with downstream output. When a required field is missing, leave it unresolved or return to the source; do not fill it from an assumption.