📚 User Journeys

[DavidBurela]

List of journeys to be completed

• [ ] Provision - Deploy sample to an Azure subscription
• [ ] ETL - Trigger pipeline to see the data flow to PBI.
• [ ] ETL dev - Modify a pipeline or notebook and commit it
• [ ] ETL dev - Modify Python code, trigger a push package
• [ ] ETL dev - Promote through Staging & Prod
• [ ] ETL dev - View integration tests to ensure everything is good
• [ ] Observability - Looking at logs to see how long execution took
• [ ] Data exploration - How can a Data Scientist use serverless to explore

Provision - Deploy sample to an Azure subscription

Expected flow:

• Get the sample
• Trigger an automation to deploy sample to Azure subscription
• Any manual completion steps
• Recommended next journeys to execute

ETL - Trigger pipeline to see the data flow

Which environment? Sandbox? Expected flow:

• Open Synapse workspace
• Navigate to the pipeline and trigger it? Does this need debugging environment?
• Where to look to see the data has transformed and landed in gold

ETL dev - Modify a pipeline or notebook and commit it

• Fork it in git
• Modify
• Publish
• PR

ETL dev - Modify Python code, trigger a push package

• Use a local dev container
• Modify python
• Try it out in the workbook
• Commit and push

Common questions:

• What happens if pipeline is executing and a new package is deployed
• Why does it take so long

ETL dev - Promote through Staging & Prod

• Run X to promote to Stating
• Run X to promote to Prod, and pause at the approval gate

ETL dev - View integration tests to ensure everything is good

• Integration tests live at X
• What triggers them
• How to view results

Observability - Looking at logs to see how long execution took

• What is recorded
• Where to look at them
• Example of an insight that can be viewed

Data exploration - How can a Data Scientist use serverless to explore

• Open synapse studio
• Open sample exploration notebook
• Do X to have it executed on serverless pool