Odoo implementations generate valuable business data that often remains untapped without proper data integration strategies.

In this talk, we will explore how implementing streamlined data extraction and warehouse-based transformations enables faster, more flexible, and more scalable data integration workflows for Odoo environments. By leveraging modern data warehouses and implementing effective extraction techniques, teams can accelerate reporting, analytics, and AI/ML initiatives. We'll break down why this approach matters, how we built our Odoo BI pipelines, and the practical considerations you should know for implementation. This talk offers actionable insights for anyone looking to future-proof their Odoo data strategies.

Key Points:
- Why extracting data from Odoo unlocks business value
- Practical techniques for efficient Odoo data extraction
- Designing transformations at the data warehouse level (SQL, dbt, etc.)
- How to quickly implement these techniques in your environment
- Common implementation challenges and their solutions
- Real-world benefits: faster pipelines, more flexible analytics, easier maintenance

Key Learnings:
- Learn how to design modern data pipelines that load data first and transform it later for agility and performance
- Discover best practices for warehouse-native transformations (e.g., using SQL, dbt)
- Identify best practices for maintaining security and compliance when handling large data sets

Target Audience:
- BI Developers and Data Engineers working with Odoo data
- Odoo Technical Consultants and Solution Architects
- CTOs, CIOs, and Heads of IT planning data modernization initiatives
- DevOps Engineers building data integration pipelines for Odoo