Data Modeling

#### Who is the course for - **Business and IT analysts** who need to precisely define data structures and relationships so that there are no blind spots in the assignment. - **Solution architects**, looking for ways to effectively connect business needs with technological solution design. - **Experienced developers** who are moving towards analysis and need to adopt a methodological approach to modeling independent of specific code. #### What we will teach you - Be able to distinguish between a platform-independent (CO) and a platform-dependent (HOW/WHAT) data model. - Masterfully model domain, conceptual and logical models (including relational tables). - Learn to work correctly with cardinality, data integrity and (de)normalization. - Be able to create and deliver data dictionaries in a way that all recipients (from business to IT) can truly understand. - Effectively use the Sparx Enterprise Architect tool for creating and managing these models. #### Required entry knowledge - Analytical thinking. - Basic orientation in terms such as *table* or *relation* (an advantage, not a requirement). #### Teaching methods * Teaching takes place in the form of professional explanations, which are immediately supplemented with practical examples. * The key part is individual and group exercises on computers, where participants, under the supervision of a lecturer, design specific models in a real modeling tool. #### Study materials - Presentation of the material discussed in printed or online form. #### Course outline - **Introduction to data modeling** - Basic concepts and the principle of abstraction (model, modeling, information, data). - Differences in data modeling approaches (PIM and PSM). - Using the Sparx Enterprise Architect modeling tool for data modeling. - Procedures, tips, tutorials. - **Conceptual modeling (CO level)** - Important concepts: entity, relationship. - Modeling using UML (basics of class diagram) and E-R diagrams. - Multiplicities of relationships, constraint options and other rules for data integrity. - Working with database models in Sparx EA. - **Technological models and architecture (HOW level)** - Determining technologies for different layers. - Front-ends, back-ends, middle layers. - The importance of platforms. - Technological models. - **Modeling for relational databases (WHAT level)** - Relational databases. - Database concepts: table, relationship, primary and foreign keys. - Modeling: cardinality, relationships. - Ensuring data integrity. - Model normalization and denormalization. - Transferring generalization to a relational environment. - Working with database models in Sparx EA. - Indexes.