A reference study that automates multi-source data import and validation into CRM
A data automation study developed for reading Excel files in different formats from various departments, making sense of the data, mapping it to CRM fields, creating records automatically, and validating with a double-check mechanism after transfer.
Non-standard Excel files received from different departments were brought into the automation flow. The process was designed to read different data layouts without depending on a single fixed Excel template.
Columns and records inside the Excel files were analyzed to determine which CRM fields they corresponded to. This automated not only file transfer, but also interpretation across different formats.
Interpreted data was converted into the record format expected by the CRM. Missing, incorrect, or ambiguous fields became separable before transfer.
Valid records were processed into the CRM without requiring officers to enter them manually one by one. The manual data entry operation was moved into an automation flow.
The system did not only send records; after the transfer, the CRM was queried again. Submitted records were compared against the records actually created in the CRM.
Records that could not be transferred due to missing or incorrect information were listed separately. For example, if a small percentage of records failed due to incomplete information, they were reported for correction.
Successfully transferred, failed, and review-required records became reportable. This made the transfer process not only automated, but also auditable.
