Visual Analytics with Data Integration Capabilities
| Autor: | Lin, Min-Chen, 林旻蓁 |
|---|---|
| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 The quantity of data grows in the speed of light with the advancing technology. One of the topics that are most talked about today is big data, as it implies much more value than it appears to have. The faster the implications hidden in the data are deciphered as they are produced, the greater opportunity there is to stay ahead of competitors. One of the effective techniques that allow people to interpret what is hidden in data is the shortest possible time is the visualized analysis. The use of visualization tools allows complicated data to be transformed into easy-to-read graphics. This process requires integration of data coming from a wide variety of sources in order to demonstrate the value of these data graphically. Most of the visualization tools are available in the market; however, they provide only the import of single files. The few that allow importing of multiple files are not necessarily capable of data integration. On the other hand, professional statistical analysis programs are complicated to use, which increases the difficulty to use. For this reason, this study intends to integrate data of multiple files and sources. The data integration consists of data merge and addition of new attributes. Data merge allows the merging of different data table, while the addition of new attributes allows the extension of existing data field and create new attribute fields. This helps sort out the data to be visualized before the visualization and maximizes the effects of visualization. Google Visualizations API is introduced as the visualization tool, which contains large quantity of graphics. User’s visualization settings are imported into Google Visualization API to create visual graphics. The framework designed for this study provides portable graphic service. A website creates specifically for the graphics creates is generated and encrypted based on the visualization settings of the graphics. The user only has to share the address and password to allow others to view the graphics through a browser. An integrated visualized analysis system framework in this study is built for data analysts, which allows them to integrate data before the visualization and maximizes the visual effects after the visualization of the data to be visualized. The portable graphic service allows users to share the visualized results with others. The feasibility of this framework can be demonstrated by applications such as cross-referencing of college examination lists and nationwide mortality due to cancers. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|