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Dimensional Modeling – Foundation
Develop knowledge and insight into dimensional modeling for BI and data warehousing.
Why do some dashboards work quickly and flexibly, while others are difficult to scale and become increasingly complex? Often, the cause lies in the way data is modeled.

In this foundation training, you will be introduced to the key concepts, techniques, and mindsets within dimensional modeling, data warehousing, and Business Intelligence. You will learn to understand how operational data is transformed into dimensional models suitable for reporting, dashboards, and analysis.

The focus is on knowledge, insight, and application skills. You will learn what types of models exist, when to make certain choices, and how BI users use data for analysis and decision-making.

In addition, the course serves as good preparation for the Dimensional Modeling Foundation assessment.

Why this training?
Many organizations collect large amounts of data but encounter questions such as:

Which data are important for management information?
Which dimensions best support reports?
What is the difference between a star model, snowflake, or Data Vault?
How do you deal with history?
Why do some reports perform poorly?
How does a data model align with the reporting question?
This course helps you gain insight into dimensional modeling and its role within Business Intelligence and data warehousing.

What do you learn?
Afterwards you will have:

insight into the basic principles of dimensional modeling
knowledge of facts, dimensions, and hierarchies
understanding of BI architectures and workloads
insight into star models, snowflake models, and Data Vault
basic skills in interpreting dimensional models
understanding of history and Slowly Changing Dimensions
insight into the relationship between reporting questions and data models
good preparation for certification

Topics
-Foundations of dimensional modeling
-What are dimensions?
-What are facts?
-How do you identify facts in source data?
-What do you measure with a fact?
-Facts without measured values
-Relationships between facts and dimensions
-BI architectures & analysis techniques
-ROLAP, HOLAP and MOLAP
-Hypercube dimensional models
-Drill down, roll up and pivoting
-Workloads and reporting needs
-Modeling dimensions
-Hierarchies
-Shared & conformed dimensions
-Ragged dimensions
-Recursive relationships
-Attribute trees
-Pruning & grafting
-Outriggers
-Many-to-many relationships
-Degenerated & junk dimensions
-Keys & history
-Surrogate keys
-Business keys
-Primary & foreign keys
-Slowly Changing Dimensions (SCD)
-Modeling historical data
-Historical queries
-From ERD to Data Warehouse
-Analyzing relational models
-ERD → star model
-ERD → snowflake model
-Data marts
-Shared dimensions between processes
-Data Vault & modern architectures
-When do you use Data Vault?
-Differences between Data Vault and dimensional modeling
-Flexibility versus performance
-History and auditability

Practical approach
The course combines theory, examples, and short exercises. The goal is not to build extensive data warehouses, but to develop insight into:

how dimensional models are constructed;
why certain design choices are made;
and how BI users perform reports and analyses.
The work uses recognizable practical cases and examples from BI and reporting environments.

For whom?
This course is suitable for anyone who wants to understand more about:

Data warehouses
Data marts
Business Intelligence
Data modeling
BI reports
Analysis environments such as Power BI

For example:

Young professionals in IT
BI specialists
Data analysts
Information analysts
Database professionals
Consultants
Functional designers
Developers who want to delve into BI
Level & prior knowledge
Level: Higher Professional Education (HBO)

Prior knowledge: not required

Execution
3 classroom days
Usually 1 class day per week
Online execution possible
Theory combined with examples and exercises

What's in it for you?
Afterwards, you will understand:

how data warehouses and data marts are structured;
what role dimensions play within BI;
how workloads influence dimensional modeling;
when star, snowflake, or Data Vault models are used;
and how history and Slowly Changing Dimensions work.

Exam (optional)
Dimensional Modeling Foundation assessment
40 multiple-choice questions
Maximum 90 minutes
Open book exam
The Dimensional Modeling Foundation assessment is fully owned and maintained by the Business & IT Exams Association.

Ready to better understand Business Intelligence?
Do you want to gain insight into dimensional modeling, data warehousing, and BI reporting?

Then sign up for:

Dimensional Modeling – Foundation
and develop a solid foundation in Business Intelligence and dimensional modeling.