Data entry tasks can be accomplished by different people with different abbreviation tendencies. Inconsistencies in the way the same value is stored can lead to the database returning incorrect information.
- [Instructor] Typographic errors and spelling mistakes…can completely wreck even the most well planned database.…These types of errors are difficult to predict…and often occur when data entry tasks are being performed…by human beings.…We simply get in a hurry and can get a little sloppy…with our typing skills.…Related to this is the common problem of…having different entry styles…among a variety of individuals.…Different people might be in charge of putting…data into the database.…Some people like one abbreviation over another,…and others will choose to spell out information completely.…
Let's take a look at an example using the products table…that we created in the last movie.…Here we have the various olive oils that are available…for sale and the manufacturers of those products.…In the manufacturer's column,…you can see that they're all produced by…the Two Trees Olive Oil company.…But, one of them was input as a numeral two…instead of the word two written out.…While this gets the information across in a way…
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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