Load vendor price files without opening a spreadsheet.
A supplier drops a price file. DataBridge picks it up, checks every row, translates their part numbers to yours and loads the result into a staging table.
Vendor price files arrive in a dozen layouts, often with bad rows. Cleaning them by hand before each load is slow and easy to get wrong, and a bad price that slips through reaches your catalog.
Modules. Everything bundle: Transfer for the source, Flow for the job and the database step, Database for the write-enabled connection.
Edition. DataBridge Server for unattended schedules.
How DataBridge does it.
Each step names the feature as it appears in the product.
- Step 1
Sources
Define where the file arrives: an SFTP or FTP server, a local or network folder, an HTTP address, Azure Blob Storage or Amazon S3. Test and Preview work before you save, and What's there lists waiting files without transferring them.
- Step 2
File template
Describe the vendor's layout with column types, required values, lengths and patterns. Every row is checked against the template before any later step sees it.
- Step 3
Field mapping and crosswalk
Map the vendor's columns to your staging layout. A crosswalk translates their part numbers to yours and can fail the row when a code has no entry.
- Step 4
Write to database
Insert, or update by key columns, into a table that already exists. Choose whether a bad row fails the run or goes to a reject file you can download, and whether the load is all or nothing.
- Step 5
Send notification
Email the right person when a run succeeds or fails, with the job name, status and step counts.
What this does not do.
- A run takes the oldest waiting file only, so schedule the job often enough to drain a backlog.
- The write step never creates or changes a table, and an administrator must switch on writes for the connection.
- Fixed-width files are not supported. The file must be CSV, TSV, Excel or use a custom delimiter.
Related pages.
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