Why do we spend millions of euros and thousands of hours every year developing solutions that don’t work?

The poor understanding and formulation of business requirements lead to enormous waste of resources. Good data models prevent this waste of time and money by capturing business terminology and requirements precisely and at various levels of detail, ensuring smooth communication within the company.

Complete the Data Modeling Master Class to develop competencies in data modeling. The Data Modeling Master Class is the training on data modeling, offered several times a year publicly or, upon request, exclusively for your team.

Content

The Data Modeling Master Class is a complete data modeling course, spread across three modules, that teaches practical techniques for creating conceptual, logical, physical relational, dimensional, and NoSQL data models.

After learning the different types and individual steps of requirement gathering and modeling, you will apply a best-practice approach to creating and validating data models using the Data Model Scorecard®. You will not only learn how to create a data model but also how to optimize it.

This Data Modeling Master Class consists of three modules with over 30 exercises and 20 hours of instruction:

After completing Module 1, you will be able to explain the benefits of data modelling, apply the five guidelines for creating a data model, and correctly use the individual data modelling components (entities, attributes, representatives, relationships, subtyping, keys, hierarchies, and networks).

Schema

At the end of Module 2, you will master the creation of conceptual, logical, and physical relational and dimensional data models. You will also be able to differentiate NoSQL data models in terms of modelling structure and approach compared to traditional models.

Scorecard®

By the end of Module 3, you will be able to apply best practices for data models using the ten categories of the Data Model Scorecard®. The categories are correctness, completeness, schema, structure, abstraction, standards, readability, definitions, consistency, and data.

Upon completion of the Data Modeling Master Class, you will not only know how to create a data model but also how to create an excellent one. After the training, you will be well-prepared to take the Data Modeling Certification (DMC) and demonstrate that data models are in good hands with you.

Top 10 Learning Objectives

• You will be able to validate any data model using important "settings" (scope, abstraction, timeframe, function, and format) as well as the Data Model Scorecard®
• You can read a data model of any size and complexity with the same confidence as reading a book
• Apply techniques for requirement gathering, including interviews, artifact analysis, prototyping, and workplace observation
• Explain the components of data modeling and identify them in your projects through targeted questions
• Practice identifying problems in data model structures, as well as violations of guidelines and conventions
• You will create relational and dimensional conceptual and logical data models and understand trade-offs in the physical implementation for both RDBMS and NoSQL solutions
• Use a set of templates for capturing and validating requirements and creating data profiles
• Understand when abstraction makes sense and how patterns and industry data models can be highly beneficial
• Use Data Vault and an enterprise data model for a successful enterprise architecture
• Evaluate definitions for clarity, completeness, and correctness

Upon completion of the Data Modeling Master Class, you will not only know how to create a data model but also how to create an excellent one. After the training, you will be well-prepared to take the Data Modeling Certification (DMC) and demonstrate that data models are in good hands with you.

This training requires no prior knowledge of data modeling, and as such, there are no specific prerequisites. The training is aimed at anyone with one or more of the following terms in their job title: data, analyst, architect, developer, database, and modeler.