Veronica Dumitriu
Product Manager, Oracle Data Access and Database Drivers
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A dynamic technology expert with a robust background in Oracle Analytics, Business Intelligence, Statistics, ML, and AI. Her experience spans product management, solution and data architecture, design, consulting, development, deployment, and user training.
As the product manager for key open-source language drivers, including Python and R, she enables data scientists and developers to build powerful analytics and AI applications on Oracle Database. Veronica is currently focused on empowering business decision-makers and improving business performance management through seamless integration between modern data tools and Oracle technologies.
Supercharge Your Workflow: AI-Powered Oracle Database with n8n
Explore how to integrate 26ai Oracle Database with n8n, a powerful AI workflow automation platform with a drag-and-drop workflow builder. We’ll demonstrate how n8n can be used to build intelligent, data-driven applications, leveraging its wide range of pre-built templates and connectors with minimal coding. You will learn about the Oracle Database node and how it can help build AI workflows, such as Automated Document Ingestion Pipelines, Natural Language Search on documents, and Real-Time Database Health monitoring. This session will also showcase how Oracle can be used as a vector store using n8n’s LangChain integration.
Analyze Spatial Data Using Python, GeoPandas, and Oracle Database
Discover how to leverage the power of Python to get demographic insights from spatial data and drive critical business decisions. In this session, we dive into a hands-on, practical example of using GeoPandas alongside the python-oracledb driver and Oracle Spatial. You'll learn how to extract, manipulate, and visualize geographic and demographic data to uncover actionable insights. Whether you're in urban planning, retail, or logistics, this session will show you how to integrate spatial data analysis into your Python workflow to gain a competitive edge. Ideal for developers looking to elevate their data science skills with spatial analytics.
Influencing the Future: Oracle’s Product Direction, Your Feedback
Bring everything you’ve learned at the conference to this discussion, where Oracle Product Management leaders for data and analytics solutions will share future plans and get your perspective on vision, strategy, and roadmap. This session features presentations, demos, and lots of active discussion! You’ll learn what’s coming and how you can help influence Oracle’s direction through ongoing feedback, early testing, GTM programs, and more. You’ll also have the opportunity for detailed questions and conversations with product teams. We look forward to seeing you there!
Real-World Insights through AI Vector Similarity Search using Python
In this session, we demonstrate an AI-powered e-commerce solution that uses vector similarity search with Python, the python-oracledb driver, and Oracle Database 26ai. The database hosts a catalog of product images represented as vector embeddings. When a user provides a new image, the system queries the database to retrieve the most visually similar items. You’ll learn how to generate image embeddings using AI models, store them as native vectors in Oracle Database, and leverage built-in AI vector search capabilities to power image-based product discovery, recommendations, and personalization.
Unlocking Insights: Exploring Similarity Search with Python in Real-World Scenarios
Delve into the fascinating world of similarity search algorithms and techniques utilized to solve real-world problems efficiently. Exploring their practical applications through a demonstration using Python, the python-oracledb driver, and vector data stored in Oracle Database 26ai, the session will cover different approaches, providing you with a comprehensive understanding of the underlying concepts and their implementation in Python, and empowering you to apply these techniques effectively in your own domains and projects.
Power Analytics in Python with DataFrames and Oracle Database 26ai
Learn how to use DataFrames in Python for Oracle Database queries. New dataframe functionality in Oracle's python-oracledb driver makes it easy to work with libraries such as Apache PyArrow, Pandas, Polars, NumPy, PyTorch, or to write files in Apache Parquet and Delta Lake formats. Support for zero-copy dataframe interchange increases performance. In this session, you’ll see how to efficiently move data between Python and Oracle Database 26ai, enabling fast, scalable analytics and AI-powered workloads directly with your familiar Python tools.
Oracle AI meets Python RAG
What happens when Python, LLM, and Oracle 26ai walk into a database? You get a blazing-fast RAG application live on stage. See how to move from plain prompts to powerful context-aware responses using LLMs, embedding generation and storage, vector search, python-oracledb, and Oracle’s AI SQL. No cloud lock-in. No black boxes. Just Python, SQL, and pure AI speed.
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