Goal

In the dynamic world of data management, effective data modeling is essential for organizations to gain meaningful insights and make informed decisions. This workshop session aims to provide participants with a comprehensive understanding of the fundamentals of data modeling and equip them with the know-how to build robust and scalable data models.

Details

This workshop session has three main parts:

1) Data Modeling Basics: Participants will learn the fundamental concepts of data modeling, including dimensions & facts, keys and normalization techniques as well as the essentials of conceptual, logical, and physical models.

2) Dimensional Modeling: Building upon the basics, participants will delve into dimensional modeling, a widely adopted technique for designing data warehouses and business intelligence solutions. They will learn the fundamentals of star schemas, define dimensions and facts, and learn as well as about historization (slowly changing dimensions) and normalization (snowflaking) techniques.

3) Data Vault Modeling: The workshop will culminate in an introduction to the Data Vault methodology, a highly scalable and adaptable approach for modeling enterprise data warehouses. Participants will learn the core principles, components, and benefits of Data Vault modeling, enabling them to design data vault structures and support data integration, traceability, historical analysis, scalability and flexibility.

Target Audience

This workshop is designed for data professionals, data architects, database administrators, business intelligence developers, and anyone involved in data management and analytics. Participants should have a basic understanding of SQL, databases and data concepts. The workshop will consist of a combination of theoretical explanations, practical examples, and hands-on exercises to ensure a comprehensive and engaging learning experience.