Track4: Future Organizations

Data Mesh in Action: Harnessing Palantir Foundry for Enhanced Analytical Capabilities

Leverage Palantir Foundry and data mesh to build analytical data pipelines and maintain high data quality (DQ) standards across your organization.

This session will guide you through the creation of structured data pipelines using an analytical data model approach, enabling the extraction of actionable insights from complex datasets. Learn to implement and monitor robust DQ checks within a unified framework, utilizing both built-in and custom solutions in Palantir Foundry. Participants will gain practical experience and insights into integrating effective data models and DQ principles within their projects.

Learning goal

Participants will gain practical experience and insights into integrating effective data models and DQ principles within their projects.

Pre-requisites

Basic knowledge of Python and PySpark.

  • Konstantinos Pittas

    Konstantinos holds an M.Sc. from the National Technical University of Athens in Chemical Engineering and an M.Sc. in Management Science and Technology from Athens University of Economics and Business. Before joining D ONE, he worked as a Senior Quantitative Consultant at Ernst & Young in Athens. Konstantinos has been with the team since 2021.

  • Nikolaos Anagnostopoulos

    Nikolaos received his MSc in Statistics from the Athens University of Economics and Business. He is an enthusiastic data scientist with an advanced theoretical and practical background. Before joining D ONE, he worked as a Data Scientist in the field of Insurance and as a Credit Risk Data Scientist in EY. Nikolaos has been with the team since 2023.