What you'll learn

Data projects fail. not because of bad code or the wrong tools, but because teams skip the essential step of understanding how their data should be structured. Without a solid data model, organizations face inconsistent data, integration failures, and systems that can't scale--problems that become exponentially more expensive to fix after implementation.

In this course, Data Modeling Core Concepts, you'll gain the ability to understand data models and participate effectively in data-driven projects that shape how organizations manage and use their information.

First, you'll explore the fundamentals of data modeling, learning what data models are, how they bridge business requirements and technical implementation, and why well-designed models improve data quality and system performance while poor models create costly technical debt.

Next, you'll discover the building blocks of data models, understanding entities, attributes, and relationships, differentiating between relationship types, examining keys and cardinality, and learning to read entity-relationship diagrams that communicate data structures to both business and technical stakeholders.

Finally, you'll learn how data modeling fits within the broader data lifecycle, tracing how models evolve from conceptual to physical forms, identifying collaboration points between analysts, architects, and engineers, and understanding how modeling decisions influence database design, ETL workflows, analytics, and long-term system maintainability.

When you're finished with this course, you'll have the skills and knowledge of data modeling concepts needed to read and interpret data models, contribute meaningfully to design discussions, and understand how modeling decisions impact the data systems you work with every day.