BCA Data Analysis and Visualization

bcasemester 8Elective

This course introduces 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.

semester photo

Chapter Wise Notes Question Banks Syllabus Chapter Wise Questions Viva Practical

Unit 1:Introduction to visualization

Introduction of visual perception, Visual representation of data, Data Abstraction, Visual Encodings, Use of Color, Perceptual Issues, Information overloads

Unit 2:Creating visual representations

Visualization reference model, Visual mapping, Visual analytics, Design of Visualization applications

Unit 3:Non spatial data visualization

Visualization of one, two and multi-dimensional data, Tabular data, quantitative values (scatter plot), 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, Time series data, characteristics of time data, visualization time series data, mapping of time

Unit 4:Spatial Data Visualization

Scalar fields, Isocontours (Topographic Terrain Maps), scalar volumes, Direct Volume Rendering(Multidimensional Transfer Functions), Maps (dot, pixel ), vector fields, Defining Marks and Channels

Unit 5:Software tools and data for visualization

The iris data set, The Detroit Data Set, The Breakfast Cereal Data Set, The Dow Jones Industrial Average Data Set (time series), MS spread sheet, Python, Matlab, Java, Tableau