How Would You Spend Your Day if Process Mining ETL Took Half the Time?

In the world of process mining, one of the most time-consuming tasks is extracting, transforming, and loading (ETL) data into event logs. As professionals, we’ve come to accept this as part of the job, allocating countless hours to wrangling data before we can even start analyzing processes. But what if ETL for process mining only took you half the time? How would you spend the rest of your day?

Over the past few months, I’ve noticed that my process mining projects are wrapping up much faster. A significant reason behind this shift is our integration of an LLM Copilot within the mindzie Data Designer. This tool has fundamentally changed how we approach the development of process mining event logs, streamlining tasks that used to require extensive effort and collaboration.

The Copilot within the Data Designer offers several benefits that drastically reduce the time spent on ETL:

Explaining the tables and columns in the database: Understanding the structure of a database can be daunting, especially when dealing with unfamiliar databases. The Copilot quickly explains tables and columns, providing insights that save hours of digging through documentation or consulting with subject matter experts.Helping understand data and how tables join: Correctly joining tables is critical in building accurate event logs. The Copilot assists in understanding how tables relate to each other, reducing trial-and-error and ensuring that the data is correctly aligned.Help writing queries: Writing queries can be time-consuming, especially when they require complex logic. The Copilot helps construct these queries and ensures they are optimized, reducing the time spent on debugging and refinement. Copilot supports all the many flavors of SQL supported by the mindzie Data Designer.Automatically documenting the written queries: Documentation is crucial but often neglected due to time constraints. The Copilot automatically generates documentation for the queries it helps create, keeping the project well-organized without additional effort.Checking queries against coding quality standards: Ensuring that queries meet coding standards is vital for maintaining code quality and reducing errors. The Copilot performs these checks, providing another layer of reliability and speeding up the development process.

Beyond the Copilot, the Data Designer has other features that contribute to this newfound efficiency:

Maintaining several small, simple queries to build the event log: Managing smaller, more manageable queries simplifies the ETL process and makes tracking and troubleshooting issues easier.Direct connection to 20 data sources: With direct access to data sources like SQL Server, Oracle, SAP, Data Bricks, and more, data extraction becomes seamless, cutting down on the time spent on integration.Pushing data directly to mindzieStudio: Once the data is prepared, it can be sent directly to mindzieStudio without needing intermediate steps, reducing time and complexity.Easily scheduling regular data transformations: The ability to automate and schedule data transformations ensures that the process runs smoothly and consistently, freeing up more time for analysis.

These features, especially when combined with the LLM Copilot, have allowed me to complete projects in half the time they used to take. The reduced reliance on subject matter experts and the decreased manual effort mean that my workdays look very different now.

With this newfound efficiency, I find myself reflecting on how to best use the extra time. What would you do with your time if ETL for process mining only took half the time?

Maybe you’d dive deeper into analysis, explore new methodologies, or even take a well-deserved break. The possibilities are endless—and that’s the beauty of it.

Please contact me if you would like to try our Data Designer.