Data tables should be allowed to grow taller with user input, but adding columns and growing the table widthwise takes developer intervention. Multi-valued fields are better handled by breaking the data out into multiple tables.
- [Instructor] One of the habits…that sometimes come over from the world of spreadsheets…is the tendency to try and store…multiple pieces of information of the same type…in a single field.…This typically shows up as a comma separated list of values…where one record has several corresponding data items.…Here's an example of what this might look like.…Let's suppose that we wanted to keep track…of the names of our employees' children,…as part of the health benefits that we provide.…An initial thought would be to simply create a new column…in our employees table and place the names there.…When we do that, however, you can quickly see what happens.…
Any employees that have more than one child…will have that information stored…as a list of multiple names.…Once again, we have a structure…that'll work well for us personally,…but doesn't help the database…organize your information in the most efficient manner.…This is why it's called a multivalued field.…And it's inherently difficult to search through.…If we were to ask the database…
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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