Delivery will be by lecture, case study and assignments.
- Introduction to Big Data Analytics
- The importance of analytics and visualization in today's data-prevalent markets
- Introduction to Data Visualization using tools such as Tableau
- Effective ways of visualizing data using other data visualization tools such as free and/or Open Source tools – Ex: D3.JS, DC.JS, Google Charts, etc.
- Diverse types of Visual analysis – Time-Series, Deviation, Distribution and Correlation Analysis
- Interface components of a visualization tool such as Tableau
- The right visualization tool for different data sets – making the right choice
Students who complete this course will be able to:
- Explain foundations of Big Data Analytics & Data Mining Process
- Explain core skills for Information Visualization and available visualization tools available in market
- Demonstrate the use of data visualization tools such as Tableau
- Explore other data visualization tools such as D3.JS or Google Charts, etc.
- Examine effective ways of visual analysis
- Create compelling and effective interactive dashboards.
- Incorporate geospatial visualization in Dashboards
- Publish Dashboards
- Choose the right visualization tool for different data sets
Assignments (min 3) 15% - 20%
Term Project – 1 05% - 10%
Participation 0% - 05%
Quizzes (min 2) 10% - 15%
Midterm Examination 25% - 30%
Final Examination 25% - 30%
Textbooks and Materials to be Purchased by Students:
- Learning Tableau by Joshua Milligan
- Tableau Desktop Manual/Documentation/Help http://www.tableausoftware.com/support/help
- Now You See It: Simple Visualization Techniques for Quantitative Analysis By Stephen Few ISBN-10: 0970601980 and ISBN-13: 978-0970601988
Principles of Math 12 with a C or Pre-Calculus 12 with a C or equivalent
OR currently active in:
PDD Data Analytics
PBD Computer and Information Systems