Microsoft Access uses query objects to piece together bits of data that are spread across multiple data tables in order to present usable information to the end user.
- [Narrator] I've gone ahead and fill in some data…into the table that we've created in the last movie…and I want to now show you how the database…uses what it knows about our tables…and their relationships to give us some useful information.…Let's first take a look at the line items table…and all the data that I've added.…Here, we have a column for the invoice ID.…This is a numeric value that links back to the invoice.…We can see that we have two invoices,…invoice one and invoice two.…On those invoices we have a number of line items.…On invoice number one we have two lines, one and two,…and on invoice number two we have three lines,…one, two and three.…
We also have a reference to the product ID.…This is a numerical reference to the product ID…that we can find in the products table,…as well as the quantity of the product that was ordered.…Now we have all of this data,…but it doesn't really convey any true information to me.…For instance I really want to know who placed the order.…And I also want to know which products were ordered…
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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