E-DATA CONSULTING
Data pipelines for analytics
Connect business systems, documents and analytical datasets. Control completeness, freshness and change at each transition.
Discuss the task ↗Start with your situation
A report refreshed on schedule, but some transactions are missing. Design content validation alongside data transfer.
A metric with a traceable path
- Source and transformation lineage
- Exchange contracts and completeness checks
- Late-arriving and duplicate record controls
- Pipeline recovery after failure
Agree scope, data access, cost and acceptance criteria after discovery. Expand after validating the pilot.
Our approach
From the question to a decision.
- 01
Define the decision
Which decision is delayed, and what facts does it require?
Question, scope and owner - 02
Examine the sources
Examine a data sample, its origins and discrepancies.
Quality and rule map - 03
Build and validate
Configure one scenario and test ordinary and difficult cases.
Pilot with acceptance criteria - 04
Make it operational
Hand over operating rules, training and improvement ownership.
Operating routine and next steps