Generative AI and Process Mining - A world of possibilities - Part 2

In my previous article, we explored how a Copilot agent, integrated with Power Automate and Azure OpenAI's large language models, can efficiently process both structured and unstructured event logs from diverse storage systems. This integration enables the generation of tabular data in CSV format, facilitating the creation of Process Mining data models. However, the automation did not extend to generating the process model itself. In this article, we delve into a new yet closely related challenge, as detailed below.

Problem Statement

Now that I have my event logs captured in CSV format, stored in Azure Data Lake Gen2 Container, I am ready to connect it to Microsoft's Power Automate Process Mining to create a process model out of it. (If you have not yet tried your hands creating process models from CSV stored in Azure Data Lake Gen2 accounts, please visit Microsoft documentation here.)

As part 2 of this series of articles, we shall explore ways to automate creation of the process model in a Power Platform environment under Power Automate Studio. 

Solution

Fig. 1: High Level Architecture Diagram

1. The Orchestrator: The Power Automate (which is also named as "The Orchestrator" in my previous article) is just shown in Fig. 1 as a reference to the caller of the Azure Function (see below "Azure Function" step).
2. Azure Function (Role - Data Modeler): In this part of the solution, the Azure Function is supposed to play one more critical role od Data Modeler by executing Power Platform CLI commands and calling Dataverse Web API to create four resources in Microsoft Dataverse, as follows:
1. A Power Platform Solution.
2. A connector that will connect to the Azure Data Lake Gen2 Storage Account.
3. A connection reference for the connector created in step #1.
4. Finally, a PM Inferred Task (or the Process Model).
3. Power Automate Studio Process Mining: Finally the model is ready for: 
1. Creating visuals in Microsoft Power BI dashboards, or 
2. Linking to Microsoft Fabric Lakehouse using DirectLake (see "Useful Resources" section below), or 
3. Power Automate's desktop client for Process Mining (a.k.a. Power Automate Process Mining). See "Useful Resources" section below to know more.

Business Outcomes

This makes the Copilot Agent an apt assistant to a process mining engineer for streamlining an end-end solution or a one-stop-shop for generating process maps, variants, loopholes, root cause analysis and key metrics, etc. from structured and unstructured event logs alike.

Conclusion

This short article is still an as a concept, something yet to be verified. Stay tuned to get more updates once this architecture is tested. The high level architecture will potentially be further broken down into more details in the upcoming articles. Consider following me on LinkedIn so you do not miss on the  latest updates on this blog series.

Useful Resources

How to bring Azure Data Lake Gen2 Storage Container as data source for process mining data model? 

https://learn.microsoft.com/en-us/power-automate/process-mining-byo-azure-data-lake 

Link Process Model to Microsoft Fabric Lakehouse using DirectLake - 

https://learn.microsoft.com/en-us/power-platform/release-plan/2025wave1/power-automate/export-process-intelligence-semantic-model-fabric-workspace

Process Mining Tutorial from Microsoft -

Get started with the process mining capability - Power Automate | Microsoft Learn

Disclaimer: The ideas and concepts presented in this blog post are based on personal opinions and are yet to be proven true. They are intended for informational purposes only and should not be considered as professional advice.