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

“The end game of analytics in business isn’t to make yourself shine, but to help others transform data into impactful action.”


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

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.


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