Choosing a data model
Modelers should be familiar with these modeling techniques and apply them when appropriate. In practice, most systems have mixed data models, and finding a pure data model that adheres to all the recommended characteristics explored in this chapter is nearly impossible.
As a general guideline, normalization techniques are suitable for transactional systems focused on capturing events, sometimes involving millions of rows in a short period. The strength of the 3NF is that the updates and inserts of these transactions impact the database in only one place.
The dimensional model or star schema is more suitable for analytical purposes, such as drilling down on data, generating reports, and performing aggregations or calculations. This modeling technique is integrated into some business intelligence tools, making it easier for users to understand and query directly for data extraction and create reports or dashboards.
Highly complex systems with multiple sources...
