The first principle is that duplicate information (also called redundant data) is bad,
because it wastes space and increases the likelihood of errors and inconsistencies.
The second principle is that the correctness and completeness of information is important. If your database contains incorrect information, any reports that pull information from the database will also contain incorrect information.
As a result, any decisions you make that are based on those reports will then be misinformed."
"A good database design is, therefore, one that:*
Divides your information into subject-based tables to reduce redundant data.
* Provides the database management system (e.g. ACCESS) with the information it requires to join the information in the tables together as needed.
* Helps support and ensure the accuracy and integrity of your information.
* Accommodates your data processing and reporting needs.
Think of the small database we used in our lab exercise - Products and Suppliers. Briefly describe how this database observes any two of the four design principles outlined above.
Inventory Status is divided by product category.
There are five columns, product name, company name, selling price, quantity on hand and reorder level (subject -based table). Therefore, when people read the information, we can read the column before they go into the detail.
For example: multi-dimensional analysis on an OLAP CUBE
The report includes four measures (Sales amount, revenue goal, revenue status, revenue trend) and one dimension (financial year).
Each table aslo contains a key field to uniquely identify each record for retrieval or manipulation.
Hi Alice ! When you mentioned that "Inventory Status is divided by product category. There are five columns, product name, company name, selling price, quantity on hand and reorder level (subject -based table)...", you are referring to the report that we created using the Report Wizard.
回覆刪除It is the underlying tables (the source of data for the report) which are subject-based. The two tables used are Product and Supplier, where each one focuses on a single subject only.
OLAP cubes are different from relational databases; they are pre-built from data warehouses and organized by multiple dimensions.