A table is in third normal form if it is in 2NF and no non-key fields are functionally dependent on a field that is not the primary key.
- [Instructor] The Third Normal Form…follows a similar pattern to the Second Normal Form.…But instead of checking against the individual components…of a composite primary key, we'll check each non-key column…against every other non-key column.…Here, we're looking for columns that are functionally…dependent on another piece of information…that isn't the primary key.…This often occurs when two fields are simply stating…the same thing in a different way.…For instance, you might try storing the state,…and the state abbreviation in an address table.…Since state abbreviation is entirely dependent on the state,…or vice-versa, one of those two fields should be…removed from the table.…
Here's another example…using our Explore California tour company.…In the table about the various tour packages, we are…storing a difficulty rating as both a numeric rating,…and a text description of what that number means.…You can see that a difficulty of easy should always…correspond to a rating of one,…and a difficulty of difficult…should always correspond to a rating of five.…
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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