- Application
- Data
- ER Diagram
- Relational Schema
- Star Schema
- Application ScreenShot
- Star Schema Query Analysis
The computer retails around the world have the demands to manage their inventory due to the complex nature of their inventory. However, they do not have the necessary skills for building an inventory. Therefore, we applied what we learnt in this class and built an application to help them manage their inventory, and also enable them to do the basic data analysis on their inventory.
We built an inventory management system for the computer retailers. The system not only is able to search the basic information for the inventory such as computer’s brand, type, color, resolution, CPU and et al. In addition, the application is able to do the data warehouse that facilitate the computer retailer to do the data analysis on their complex inventory data.
In our application, in order to mimic the computer retail inventory we need some data that is similar to what the computer retailer store dataset. To achieve our goal, we took advantage of dataset generating agency such as generatedata.com. These websites will auto generate the dataset based on the columns and data samples you provided. It can generate large amount of data in a short time. The generated dataset is stored in the csv file.
However, the auto generated data may have some problems since it’s auto generated, and may not mimic the real dataset. Therefore, after got the auto generated data, we tailored the dataset by modifying the dataset that can mimic the real retail situation. For example, the computer with SSD usually is more expensive with the regular hard disk. But in the auto generated dataset, they are randomly generated and therefore can not depict the real data. So we tailored the dataset ourselves, and tried our best to make the dataset as real as the real dataset. Dillinger uses a number of open source projects to work properly: