Python transformationsTransform with Python, not just SQL
Use fully customizable Python routines to transform, cleanse and enrich data before it reaches the destination, so complex business logic lives in one place.
Delivered, implemented and supported by EVIDENTCORE
- sales_orders12,480 rows · 42 sSynced
- business_partners3,106 rows · 11 sQueued
- opportunities8,912 rows · 27 sQueued
- gl_line_items51,337 rows · 1 m 54 sQueued
delivered and supported by EVIDENTCOREPython transformations in 3 steps
- Step 1
Write
Write a Python function that receives a batch of records.
- Step 2
Attach
Attach it to any pipeline step: after extract, before load.
- Step 3
Run
Datasyncher runs it on every batch and logs output and errors.
What you get with python transformations
Full Python
Use familiar libraries for parsing, validation and enrichment.
Before load
Bad records never reach the warehouse.
Reusable routines
Share one routine across many pipelines.
Versioned
Every change to a routine is versioned and can be rolled back.
Test on samples
Preview the output on sample rows before you deploy.
Logged
Row-level errors are captured without stopping the whole run.
Bring one report you rebuild every month
We'll show the Datasyncher pipeline and the dashboard that replace it.