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Visual Analytics for Business Intelligence

SCIS Sch of Computing & Info Sys

Course (UG/PG)

Undergraduate

Offering Unit/Department

SCIS

Course Description

Data analysis and communications can be fun! With visual analytics techniques and tools, everyday data analysts from various disciplines such business, economic, sociology, political science and public policy can now synthesize information and derive insight from massive, dynamic, ambiguous, and often conflicting data without having to deal with complex statistical formulas and programming. Many companies and organization took notice when Gartner cited visual analytics as one of the top five trends transforming business intelligence. In this course, students learn how to use data visualization and interactive analytic tools and techniques to interact with data of different formats from various sources, explore the expected relationships and discover unexpected correlations and patterns.

Course Learning Outcomes

1. Explaining the concepts and principles of Visual Analytics.

2. Describing the differences between Visual Analytics, Data Visualisation, Statistical Graphs

3. Explaining the basic concept of visual variables and applying these concepts and best practice static

4. Explaining interactive techniques and best practice, and applying these techniques in designing interactive data visualisation.

5. Understanding the data characteristics of numerical data and building data visualisation by using appropriate univariate graphical methods.

6. Understanding the characteristics of multivariate data and building data visualisation by using appropriate multivariate visualisation methods.

7. Understanding the characteristics of time-series data and building data visualisation by using appropriate time-series visualisation methods.

8. Understanding the characteristics of geographical data and building data visualisation by using appropriate geo-visualisation methods.

9. Understanding the characteristics of network data and building data visualisation by using appropriate network graph visualisation methods.

10. Explain the concepts and principles of Information Dashboard.

11. Building business dashboard by using Commercial off-the-shelf (COTS) software.

12. Designing visual analytics application programmatically by using free and open source software and packages.

Discipline-Specific Competencies

Data Analytics, Systems Design, User Experience Design, User Interface Design, Data Visualisation

SMU Graduate Learning Outcomes

Disciplinary Knowledge, Multidisciplinary Knowledge, Interdisciplinary Knowledge, Critical thinking & problem solving, Communication, Self-directed learning

Grading Basis

GRD - Graded

Course Units

1