Data Visualization

This course will introduce the students to broad classes of techniques and tools for analyzing and visualizing data at scale. Students will learn basic visualization design and evaluation principles, and learn how to acquire, parse, and analyze large datasets. The course starts with statistical computing, and you will gain experience with SAS Visual Analytics. You will learn the practice of data cleansing, data aggregation, and basic tabulations in producing high quality visualizations.  

  • Learning Goals

The learning goals here are to understand how data visualization techniques can help bring complex data to life, how to design effective visualizations, and how to create intuitive, meaningful, visualizations using enterprise standard applications. Course discussion will explore techniques for visualizing multivariate, temporal, text-based, geospatial, hierarchical, and network data. Using case studies drawn from variety of industries and to explore the logic importance of visualizations in modern data analysis and presentation.

  • Learning Outcomes

On successful completion of the course, the students shall be able to :

  • Understand how data visualization can enhance management through telling stories with data
  • Understand and apply principles of data visualization
  • Critically evaluate visualizations and suggest improvements
  • Design and implement standard visualization techniques
  • Use principles of human cognition in visualization design
  • Rapidly prototype visualizations for business storytelling
  • Concepts and theories to which students are exposed during the course
  • Data cleansing
  • Human cognition
  • Data sets and types
  • Design dimensionality
  • Digital storytelling
  • Graphical integrity
  • Information design
  • Positional, temporal, and retinal catégories
  • Principles of perception
  • Simple and compound marks