Denormalization of a data table occurs when a designer specifically chooses not to adhere to the rules of the normalization process. This can be done for performance or historical reasons.
- [Instructor] We've just gone through…and normalized our database design by running through…the requirements of the normal forms.…Here and there though, there might be a reason…to undo some of those changes.…Or keep our database design in a format…that doesn't strictly adhere to the requirements…of a particular normal form.…This is a process called denormalization.…Denormalization should be approached with caution…and you need to be very specific as to your reasoning…for not having your tables meet the third normal form.…The normalization process is all about…removing redundant information from your database…and helping to prevent data anomalies…that can creep in when repeated information…isn't updated simultaneously.…
So why would you want to denormalize a table?…Two reasons: performance and to track historical data.…First, let's take a look at performance.…You might have noticed that the common solution…for all of our normalization procedures…was to create an additional related table…and move the offending columns into them.…
Adam Wilbert covers the basics of relational database design, regardless of whether you use Access, FileMaker, Open Office, or SQL Server. Learn how to prevent data anomalies, gather requirements to plan your design, and develop a conceptual data model—translating your ideas into components like tables, relationships, queries, and views. Plus, learn about logical design considerations that can help you construct a database that is easy to maintain.
- What is a database management system (DBMS)?
- Moving through the database development cycle
- Preventing duplicate, inconsistent, and conflicting data entries
- Gathering requirements
- Developing relationships
- Identifying key fields
- Following a naming convention
- Developing the actual database
Skill Level Beginner
1. Relational Database Basics
Relational structures3m 46s
2. Preventing Data Anomalies
3. Gathering Requirements
4. Developing the Conceptual Data Model
5. Normalizing Your Data
6. Logical Design Considerations
7. Developing the Physical Database
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