Delivered by experts from the United Nations International Computing Centre (UNICC).
Data has become one of the most valuable assets for organizations, enabling them to better understand reality, optimize processes, and make more informed decisions. This session will explore the world of data from two complementary perspectives: how to build a solid foundation for efficiently managing and leveraging data, and how to use it to generate a positive impact on development and humanitarian action initiatives. Through practical examples, we will explore opportunities, challenges, and best practices for transforming data into knowledge and value.
UNICC, the United Nations digital services center based in Quart de Poblet, will feature experts who will share their practical experience and best practices applicable to various contexts, ranging from individual settings to complex organizations.
đź“… October 15, 2026
🕙 10:00 a.m. – 12:30 p.m.
đź“ŤLa Harinera, 32 Joan Verdeguer St., 46024 Valencia
Training Session Content:
Tip 1: One UN, Many Data Silos
Objective:
Show why, even in an organization as diverse as the United Nations, the biggest obstacle to leveraging AI is not technology, but data fragmentation.
Key messages:
- Everyone wants AI. Almost no organization is truly ready for it.
- How do radically different data sources coexist within a single organizational family such as the UN?
- Why Data Silos Exist: Different Mandates and Regulations.
- What happens when AI is applied to fragmented data?
- Why working with data in an environment like the United Nations is a unique opportunity to make a global impact.
- Use Cases.
Tip 2: From Data Silos to a Unified Data Layer
Objective:
Explain how architecture, engineering, and data visualization come together to transform fragmented information into reliable decisions, and why they are the true foundation of any AI project.
Key messages:
- What is data architecture, and what specific decisions does it involve?
- The Importance of Creating a Shared, Unified Data Layer.
- What data engineering actually does: ingestion, transformation, validation, and reliable operation.
- Visualization transforms data into clear information that drives decisions and actions.
- AI doesn’t replace data. It builds on it.