Munich Datageeks July Edition

We are thrilled to announce our next Meetup on July 31st at Celonis.
Format:

• 2 talks (each ca. 40 min incl. discussion)
• Time for networking + food + drinks before, in between and after the presentations
• Talks are held in English
• We will be taking photos and/or film footage at the event. These will be used to share news about our meetups and to publicize upcoming events.

The lineup:

First talk:
Dr. Pol Schumacher - How to mine better models, fast!

Abstract:
Join us at Celonis for a talk on Process Mining, beginning with a concise overview of the discipline. We will then focus on process discovery, the core challenge of automatically mining process models from event data. Current discovery methods often face trade-offs between model quality and scalability. This presentation will showcase our research on an improved discovery algorithm; our approach delivers higher quality process models while maintaining excellent scalability, making it ideal for real-world enterprise applications.

Bio:
Pol holds a Diploma in Computer Science from the University of Trier and a PhD in Computer Science from Goethe University. Since 2015, he has been with Celonis, where he has worked in a variety of roles including Data Scientist, Product Manager (focused on system migration and finance products), and Software Engineer.

Second Talk:
Ismail Simsek - Unifying Operational and Analytical Data with Debezium Iceberg Consumer

Abstract:
Apache Iceberg and Debezium have emerged as industry standards in data lake table formats and change data capture (CDC), respectively. Both projects boast active development and robust community support, making them trusted foundations for modern data architectures. This talk will introduce the Debezium Iceberg Consumer, a solution that combines these two technologies. We'll explore how it simplifies the replication of operational data to data lakes and analytical systems in a cost-effective, near real-time manner, while enabling a rich set of features. A brief demonstration will showcase the seamless transfer of data from an operational source to an analytical data layer.

Bio:
Ismail Simsek is a Data and Analytics Engineer specializing in data analytic architectures, data warehousing, analytic use cases, and solutions. He focuses on helping businesses unlock the value of their data efficiently and seamlessly. Ismail also contributes to the open-source community by developing data analytics solutions under the memiiso GitHub organization.