Pull Data from Data Pool via ML WB

Hi there,

in the ML workbench, there is an API call to push data to a data pool data_pool.push_table(...)
Is there also a way to pull data (eg a specific table) from the data pool? Couldn’t find something like data_pool.pull_table(...)

Best,
Benedikt

Hello Benedikt,

In the machine learning workbench you can use the Celonis API (pycelonis). Please find here how it works:
https://python.celonis.cloud/docs/pycelonis/en/latest/notebooks/01_Pulling_data.html

Hi Benedikt,

At the moment pulling full tables is only possible from an Analysis, as shown in the link that Paul shared. :slight_smile:

There is an experimental function in Transformation to run SQL statements from Python, get_data_frame: https://python.celonis.cloud/docs/pycelonis/en/release-1.2.0/reference/pycelonis.objects_ibc.Transformation.html
It returns up to max. 100 rows of your SQL statement if it is a SELECT statement.

Best,
Simon

Hi Paul, Simon,

thanks for your insights.

What I would like to do is process data in the ML WB from tables that I don’t actually need/want to have in the data model in their raw format. This would help me keep the data model small and prevent analysts from accessing tables in the workspaces they are not supposed to.

Is there another more or less clean solution to tackle this?

My ultimate goal would be to first process data from raw tables in the ML WB and afterwards load this data into a data model for use in the analyses.

Best,
Benedikt

Hi Benedikt,

At the moment the options I mentioned are the only options. Thanks for your input! We will take it into account.

Best regards,
Simon

Hi Simon,

thanks for your answer. Looking forward to seeing such a feature in ML WB.

Best,
Benedikt