Course Code: CACS455
Year/Semester: IV/VIII
Class Load: 5 Hrs./ Week (Theory: 3Hrs. Practical: 2Hrs.)
Data Analysis and Visualization intends to extend student’s knowledge and practice in data analysis and visualization, software, and applications. It provides the board overview of techniques of the visualization process, detailed view of visual perception, the visualized data and the actual visualization, interaction and distorting techniques.
Upon completion of this course, students should be able to 1. Explain the concept of visualization in the processing and analysis of data. 2. Develop visualization methods and visualization systems using software applications. 3. Perform creative work in the field of visualization.
- Introduction of Visual Perception
- Visual Representation of Data
- Data Abstraction
- Visual Encodings
- Use of Color,
- Perceptual Issues
- Information overloads.
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Separate, Order, and Align (Bar, staked Bar, dots and line charts), Tree data, Displaying Hierarchical Structures, graph data, rules for graph drawing and labeling, text and document data, levels of text representation, visualizations of a single text document, word cloud, flow data.
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Time series data, characteristics of time data, visualization time series data, mapping of time
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Scalar fields, Isocontours (Topographic Terrain Maps), scalar volumes, Direct Volume Rendering (Multidimensional Transfer Functions) , Maps(dot, pixel), vector fields
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Defining Marks and Channels
- The iris data set, The Detroit Data Set, The Breakfast Cereal Data Set, The Dow Jones Industrial Average Data set (time series), MS Spreadsheet, Python, Matlab, Java, Tableau