Best practices with Power Automate

Some of the best practices to be aware of for data cleaning in Power Automate:

• Workflow planning: Before diving into automation, carefully plan your data cleaning workflow. Identify the key steps that require automation and the triggers that will initiate the processes.
• Error handling: Implement robust error-handling mechanisms within your automated workflows. This includes adding notifications for failed processes, enabling quick identification, and resolving issues. One example would be to check the flow checker from within your flow. To do this, select Flow check in the top right corner of the Power Automate toolbar.
• Flow check will then provide details of any errors or warnings identified within your flow.
• Testing and validation: Thoroughly test your automated data cleaning workflows in different scenarios. Validate the results to ensure that the automated processes align with your data quality standards.
• Security considerations...