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.

AS-IS WORKFLOW, TO-BE WORKFLOW

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