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Welcome to the PyData Berlin July meetup!
We would like to welcome you all starting from 18:30. There will be food and drinks. The talks begin around 19.00 and the doors will close at 19:00. Make sure to arrive on time!
If you cannot attend, please cancel your spot so others are able to join as the space is limited.
Host:
Exasol is excited to welcome you to this month's version of PyData.
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The Lineup for the evening

Talk 1: Empowering Coding Agents: Automated High-Performance Distributed Computing with Exasol Python UDFs
Abstract: As LLM-based coding agents evolve, they often struggle with a critical bottleneck: moving from "code that works" to "code that scales." While agents are proficient at writing Python scripts for local execution, orchestrating high-performance distributed algorithms across massive datasets requires deep domain expertise in database internals and parallel execution models.

In this talk, we introduce a specialized Agent Skill designed to bridge the gap between generative AI and distributed high-performance computing (HPC). We demonstrate how to instruct a coding agent to leverage Exasol’s User-Defined Functions (UDFs) and Script Languages to push complex Python logic directly into the database engine.
Bio: Torsten Kilias is a Senior Staff Engineer at Exasol, where he has been driving technical innovation since 2019. His responsibilities include AI Integration, the Python ecosystem and User Defined Functions. Before joining Exasol, he spent years researching in-database text mining, focusing on how to bring advanced analytics directly to where the data lives.

Talk 2: What Actually Changed? Causal Thinking Across Attribution, Segmentation, and Growth
Abstract: Customer data is often used to explain what happened, attribution assigns credit, segmentation groups users, and dashboards track performance. Yet marketers and business leaders still struggle with a more fundamental question. What actually changed because of our actions?
This talk introduces causal thinking as a practical way to interpret customer data across attribution, segmentation, and growth. It shows why correlation-based metrics can be misleading and how counterfactuals and incrementality help teams ask better questions when they look at results. A concrete email campaign example illustrates how causal uplift modeling separates customers who would have purchased anyway from those whose behavior truly changed.
The goal is to help data scientists, marketers, and decision makers move from reading metrics to reasoning about incremental impact and to make better decisions because of it.
Bio: Dr. Maryam Ramezani-bartsch is a data and analytic leader with over 20 years of global experience building and scaling customer analytics and science teams. She has led the development of customer data, marketing measurement and targeting capabilities at GroupM, adidas, Sky, Delivery Hero, and Zalando, helping embed customer-centric, data-driven decision making across organizations. Her work focuses on building customer data models, causal analytics, experimentation, and developing teams that turn insights into sustainable business impact.

Lightning talks
There will be slots for 2-3 Lightning Talks (3-5 Minutes for each) between the two main talks.
Kindly let us know if you would like to present something :)

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Related topics

Events in Berlin, DE
Deep Learning
Machine Learning
Data Science
Python
Open Source

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