Processing turns raw inputs into analytics-ready deliverables: cleaning, normalization, deduplication, validation and documented QA.
Inputs we need
- Raw or semi-structured datasets
- Target schema and dictionaries
- Dedup keys and merge rules
- Validation rules and thresholds
- Acceptance criteria
Deliverables
- Clean normalized dataset
- Dedup / merge log
- QA report (error rates, samples)
- Transformation notes for reproducibility
Typical timeline
Small datasets: 2–5 business days. Large or multi-format pipelines: agreed as milestones in the SOW.
How pricing is calculated
Drivers:
- Volume and format diversity
- Rule complexity
- Manual review share
- Iteration rounds included
Example
Normalization of multi-country product feeds into one catalog schema — units, currency, category taxonomy and duplicate collapse.