ETL Process Monitoring Automation

ETL Process Monitoring Automation

Use Case Description

These are high level steps for this process:

  • Extract data from input files to S3 for initial load.
  • Remove duplicates from the data
  • Update default values for the missing columns
  • Perform data validations to identify inaccurate data
  • Load the processed data to the Snowflake database via snowpipe.
  • Monitor & track these operations using multiple uipath bots
  • submit data to the uipath insights dashboard.

This use case involves integration with snowflake and uipath insights. This is a key focus area for UiPath as well as per their recent agreement with snowflake. Feel free to comment and provide your feedback.


Other information about the use case

Industry categories for this use case: Compliance, Information Technology and Services, Operations

Skill level required: Intermediate

UiPath Products that were used: UiPath Studio, UiPath Insights, UiPath Orchestrator

Other applications that were used: Snowflake, Amazon S3, SNS, Kibana

Other resources: UiPath Announces Partnership with Snowflake | UiPath

What is the top ROI driver for this use case?: Minimize risk and ensure compliance in operations