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Dear Team, I try to perform a on time delivery machine learning technique with the *cel11920939 217 KB *" but I receive error on my data set. I wanted to ask is there a tutorial on how should we do whole procedure, for example I tried to import tables connected with foreign key, but I do not know is that proper connection, is the data set I am using proper (it has activity name, timestamp, index etc) should I try to execute it in training.celonis.cloud or it does not play any role. Please if you have datasets you could share with me or whole tutorial of on time delivery and not just in .ipynb file, I am getting KeyError: Model Setup 5/5 (see picture) Best regards Milos Markovic WU Vienna

Dear team,is it normal that it takes more than 20 min to open an (empty, newly created) app (smallest memory, storage and CPU limit). If not, what might be the reason? Thank you very much in advance.

Hi team, I am trying to do a usage-statistics datamodel in the front end using the Access_logging with python . I had got a folder of access_logs before i started developement. But now i need the updated versions of access logs for this usage statistics datamodel. Does someone know where this is stored or how we can access for a perticular server? Thanks in advance. image1037258 17.9 KB

Hello all,I was going through various packages in the celonis and i found out that there is a package called "Celonis_ml" with no other documentation. Where can we access the documentation / source files for the Celonis_ml package.Thank you

Dear all, I tried to use the backup_content function for Knowledge Models, so that I can store the YAML Code for worst case szenarios (package gets accidentially deleted). I am able to access the Spaces/Packages/Knowledge Models via .content but for backup_content it says the follwoing:AttributeError: 'KnowledgeModel' object has no attribute 'backup_content' Which components are enabled for backup_content?

Hi team,How to extend the result rows for more than 100 or to export the transformation query result to excel?If not from transformation, is it possible to do it via Machine Learning workspace? Is it allowed?Thank you

Hi team, Our group has been recently migrated to IBC. Now i am trying to access the analysis and datamodels of IBC via python from my local system. But i am unable to login . I was using python in the old environment , and i was using API_ID and API_token, now which API_ID isnt availble for me. Is API_ID required to login? or is just API_token along with the URL is enough? Please suggest Code that i have tried: from pycelonis import get_celonis login = {celonis_url: my_url, api_token: my_api_token} c_source = get_celonis(**login) Thank you.

Hi all, We have 2 (on premise, so not IBC) Celonis environments running: one where we develop our dashboards, and one production environment where finished and tested dashboards run. Transporting dashboards from DEV to PRD is only done by us, on request. However, were looking into automating the manual steps to reduce errors. Creating the transports from one or more dashboards and/or datamodels seems to be feasible through the Python API. However, Im wondering if the overwrite option is available in the Python API when uploading transports. The documentation does not mention this. Does anyone have any insights/ideas/suggestions?

Im following the Machine Learning training and am having problems with permissions. Ive created and entered the API token, but get this error: WARNING : the Application key of this App is missing the necessary Process Analytics permissions to use this App properly. I have added these permissions, but still get the error and when I try to Fetch Data Preview not data is returned. Is this a known problem or am I missing a step to add additional permissions? Dave

Hi everyone, I am not able to deploy the duplicate checker prebuild model. I am currently doing the ML training course and the app does not start. The issue has been discovered last Friday (24.7.20). The screen looks like the picture below. I have provided permission to access the dataset and gave the app further permissions as a Data Engineer, but this did not solve my problem. I am able to deploy a Jupyter Notebook app. This seems to work fine. image1380282 6.1 KB What can I do to solve this issue? Kind Regards Simon

Where should I put the file so that I can using python to read csv file in machine learning?

Hi team, I have been doing the auto-assignment of tables and DBconnection for the datamodel from python. But i am getting a problem in which the store type for a table is appearing as unavialable. This happens only some times when the datamodel is copied from some other server. But this completely removes the object of doing this in the first place. below is the screenshot. Any help would be appriciated. image722226 35.9 KB Edit: It should be as below image701141 39.7 KB

Hello there, Im trying to use the notebooks from the examples_ml-suite folder, specifically the 04_root_cause_analysis.ipynb notebook, but Im facing the following error when running the cell: image1636228 38.8 KB image1359568 104 KB

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? Couldnt find something like data_pool.pull_table(...) Best, Benedikt

In the sandbox, environment following the notebooks, when I run: "from pycelonis import get_celonis celonis = get_celonis()" it tells me i dont have permissions: "WARNING:pycelonis:The IBC did not accept the credentials: " I have given the application key all permissions in the team settings and in the event collection. What am i doing wrong?

Dear Celonis development team, I tried to connect and extract data from IBC to my Colaboratory python environment using Pyceonis. Normally it worked correctly with below scripts. from pycelonis import get_celonis login = {celonis_url: my_url, api_token: my_token} celonis = get_celonis(**login) analysis = celonis.analyses.find('id of my analysis) sheet = analysis.published.sheets.find(id of my sheet) component = sheet.components.find(id of my component) df = component.get_data_frame() But sometimes get_data_frame method returned exception. Exception Traceback (most recent call last) in () ----> 1 df = component.get_data_frame() 2 df 2 frames /usr/local/lib/python3.6/dist-packages/pycelonis/objects_base.py in get_data_file(self, pql_query, file_path, export_type, variables) 647 648 if r[exportStatus] != DONE: > 649 raise Exception(f"Export failed. Status: {r} \\n\\n Query: {pql_query}") 650 else: 651

Hi there, while pushing a dataframe into a datamodel i got the above mentioned error. By checking the parquet_utils.py and a quick research I found out that this (skipna) argument is obsolete and no longer supported. Iam using python 3.7.6, panas 1.0.1 and pycelonis 1.2.8 Is there a workaround for this issue? Best regards, Eike

Dear Celonis Community, We would like to implement Use case: O2C - On Time Delivery Prediction on our on-premise AS which is version 4.5 We checked the sample coding but it seems its prepared for cloud, Unfortunately we couldnt adapt sample use case for our data. Many thanks in advance, Best Regards, Vahide.

Dear Celonis community, I was wondering whether prescriptive analytics / recommendations (which are not out-of-the-box) are possible in Celonis? E.g. is it possible to define a goal (a particular performance indicator) and suggest possible actions to choose from (e.g. option A, B, C) in order to reach that goal? Example: As a production manager I would like to cut throughput times by 15% - What should I do next in order to best achieve my goal? Thanks in advance! Best, Daniel

Hi all, Our use case: We would like to allow our end-users of the Celonis analyses to test hypotheses themselves (does attribute X correlate with KPI y?). Question: As we are currently still on-premise we are investigating connecting Celonis to an R-Server to enable the RCALL function. This would allows us to dynamically build the data set to pass to R and then present the result in a user-friendly way. However, as we might move to the IBC in the (near or far) future, we wondering if such analysis <-> ML interaction is also possible with the ML Workbench. Concretely, can we pass parameters from the analysis to a stored ML function/notebook which then returns the results to be presented in the analysis? An alternative would be to pre-calculate every possible combination of attribute (sets) and KPIs, which I guess is not handy. Looking forward to some inspiration! Cheers, Joos

When using the python API for partial loads the documentation tells you to pass the table ids in the body of the request. Does anybody have the exact syntax? Ive tried: test = requests.post(url, headers={authorization: Bearer {}.format(api_key), table_id:"[{}]".format(tableid) }) test = requests.post(url, headers={authorization: Bearer {}.format(api_key)}, json = {table_id:"[{}]".format(tableid)}) test = requests.post(url, headers={authorization: Bearer {}.format(api_key), body:"[{}]".format(tableid) }) But I always get a 500 error. Regards, Joo

Could you please help with a question about using R in celonis? I only start to use function such as RCALL and RAGG. My analisys requeres work with dates and time, so I have to use datetime types and test this with the following code: *RAGG(v_oa_cases.number AS x, * as.POSIXct(2019-01-01 12:00:00) ) This gives an error: No result value in R script execution. Same as specifying the format in as.POSIXct. What could be the problem? Could somebody help with the suitable options? Thank you

Hello Celonis and others, I am trying out the Machine Learning workbench, and in the examples I see the API secrets out in the open. I would prefer to hide the secrets in a secret management system. Does the Machine Learning workbench support something like that, and how can I setup a secret management system? Inspiration for in my opinion good secret management is in: https://docs.databricks.com/security/secrets/index.html For managing SSH keys inspiration can be found in: https://help.github.com/en/github/authenticating-to-github/adding-a-new-ssh-key-to-your-github-account

Hello, I am investigating the data pool connection via the Python API. I am following the guide in : tenant.realm.celonois.cloud/documentation/data-push-api-python/ If I then try to enter the datapool according to the documentation in: tenant.realm.celonois.cloud/documentation/data-push-api-python/ I get the following error: dataPoolId.Pool does not exist If I try it via the curl command: curl -X GET --header Content-Type: application/jso --header Authorization: Bearer <YOUR_API_KEY> https://<YOUR_DOMAIN>.celonis.cloud/integration/api/v1/data-push/<DATA_POOL_ID>/jobs/ -X POST -d '{targetName:<TABLE_NAME>",type:REPLACE} I get the following error: dataPoolId.Pool id may not be empty For the data pool id I entered the datapool id of my connection. In the picture attached you can see that the 1st mark is the data pool id. I took this as my data pool id. image2019-8-22_17-1-111197512 101 KB

Malloc%20size%20error1358614 68.9 KB Hi All, While trying to get data using Python API, I am getting below error : ArrowIOError: Arrow error: Out of memory: malloc of size 5823262912 failed. I am using Query() method to extract data. Expected data shape is (20000,4) and using Celonis version 4.5 Please help with this error and share any related documentation. Best regards, Pushpendra