Rehearse the cutover until the real one is boring.
Define each extract, mapping and load once. Run them for every rehearsal, compare the results, and run the same definitions again for cutover.
A cutover weekend is the wrong time to find that a customer code has no match or a date column has two formats. Hand-built extracts differ from run to run, so a rehearsal proves little.
Modules. Free for templates, mappings, crosswalks, validation and diff. Transfer, Flow and Database for scheduled loads, pipelines and database reads.
Edition. DataBridge Server for pipelines and batches.
A real DataBridge screen, with sample data from a demo instance.
How DataBridge does it.
Each step names the feature as it appears in the product.
- Step 1
Extract
Pull each entity from the legacy system with a saved query, or take its export file. Both are repeatable.
- Step 2
File templates
Describe each target entity's layout with types, required values and patterns. Validate File lists every problem by row and column.
- Step 3
Field mappings and crosswalks
Translate old codes to new ones (customers, items, vendors, GL accounts). Set a crosswalk to fail the row when a code has no entry, so gaps show up in rehearsal.
- Step 4
Load
Write the files in the new system's import layout, or load a staging table with the Write to database step.
- Step 5
Pipelines and batches
A pipeline chains the loads in order, and a batch operation runs a set of saved queries, sync profiles or jobs with a concurrency limit and an optional stop at the first failure.
- Step 6
Data Diff
Compare the extract with what landed, or one rehearsal with the next, and see rows only in each file and changed cells.
What this does not do.
- DataBridge moves and checks data. It does not know your new ERP's business rules, so load through the ERP's own import route or a staging table it reads.
- Data Diff compares two files. It is not a table-to-table audit.
Related pages.
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