CP7017 DATA VISUALIZATION TECHNIQUES Syllabus - ME CSE 2nd Semester Regulation 2013 syllabus - www.annauniv.edu
COURSE OBJECTIVES:
To introduce visual perception and core skills for visual analysis
To understand visualization for time-series analysis
To understand visualization for ranking analysis
To understand visualization for deviation analysis
To understand visualization for distribution analysis
To understand visualization for correlation analysis
To understand visualization for multivariate analysis
To understand issues and best practices in information dashboard design
UNIT I CORE SKILLS FOR VISUAL ANALYSIS
Information visualization – effective data analysis – traits of meaningful data – visual perception – making abstract data visible – building blocks of information visualization – analytical interaction – analytical navigation – optimal quantitative scales – reference lines and regions – trellises and crosstabs – multiple concurrent views – focus and context – details on demand – over-plotting reduction – analytical patterns – pattern examples
UNIT II TIME-SERIES, RANKING, AND DEVIATION ANALYSIS
Time-series analysis – time-series patterns – time-series displays – time-series best practices – part-to-whole and ranking patterns – part-to-whole and ranking displays – best practices – deviation analysis – deviation analysis displays – deviation analysis best practices
UNIT III DISTRIBUTION, CORRELATION, AND MULTIVARIATE ANALYSIS
Distribution analysis – describing distributions – distribution patterns – distribution displays – distribution analysis best practices – correlation analysis – describing correlations – correlation patterns – correlation displays – correlation analysis techniques and best practices – multivariate analysis – multivariate patterns – multivariate displays – multivariate analysis techniques and best practices
UNIT IV INFORMATION DASHBOARD DESIGN I
Information dashboard – categorizing dashboards – typical dashboard data – dashboard design issues and best practices – visual perception – limits of short-term memory – visually encoding data – Gestalt principles – principles of visual perception for dashboard design
UNIT V INFORMATION DASHBOARD DESIGN II
Characteristics of dashboards – key goals in visual design process – dashboard display media – designing dashboards for usability – meaningful organization – maintaining consistency – aesthetics of dashboards – testing for usability – case studies: sales dashboard, CIO dashboard, Telesales dashboard, marketing analysis dashboard
COURSE OUTCOMES:
Upon completion of the course, the students will be able to
Explain principles of visual perception
Apply core skills for visual analysis
Apply visualization techniques for various data analysis tasks
Design information dashboard
REFERENCES:
1. Stephen Few, "Now you see it: Simple Visualization techniques for quantitative analysis", Analytics Press, 2009.
2. Stephen Few, "Information dashboard design: The effective visual communication of data", O'Reilly, 2006.
3. Edward R. Tufte, "The visual display of quantitative information", Second Edition, Graphics Press, 2001.
4. Nathan Yau, "Data Points: Visualization that means something", Wiley, 2013.
5. Ben Fry, "Visualizing data: Exploring and explaining data with the processing environment", O'Reilly, 2008.
6. Gert H. N. Laursen and Jesper Thorlund, "Business Analytics for Managers: Taking business intelligence beyond reporting", Wiley, 2010.
7. Evan Stubbs, "The value of business analytics: Identifying the path to profitability", Wiley, 2011.
COURSE OBJECTIVES:
To introduce visual perception and core skills for visual analysis
To understand visualization for time-series analysis
To understand visualization for ranking analysis
To understand visualization for deviation analysis
To understand visualization for distribution analysis
To understand visualization for correlation analysis
To understand visualization for multivariate analysis
To understand issues and best practices in information dashboard design
UNIT I CORE SKILLS FOR VISUAL ANALYSIS
Information visualization – effective data analysis – traits of meaningful data – visual perception – making abstract data visible – building blocks of information visualization – analytical interaction – analytical navigation – optimal quantitative scales – reference lines and regions – trellises and crosstabs – multiple concurrent views – focus and context – details on demand – over-plotting reduction – analytical patterns – pattern examples
UNIT II TIME-SERIES, RANKING, AND DEVIATION ANALYSIS
Time-series analysis – time-series patterns – time-series displays – time-series best practices – part-to-whole and ranking patterns – part-to-whole and ranking displays – best practices – deviation analysis – deviation analysis displays – deviation analysis best practices
UNIT III DISTRIBUTION, CORRELATION, AND MULTIVARIATE ANALYSIS
Distribution analysis – describing distributions – distribution patterns – distribution displays – distribution analysis best practices – correlation analysis – describing correlations – correlation patterns – correlation displays – correlation analysis techniques and best practices – multivariate analysis – multivariate patterns – multivariate displays – multivariate analysis techniques and best practices
UNIT IV INFORMATION DASHBOARD DESIGN I
Information dashboard – categorizing dashboards – typical dashboard data – dashboard design issues and best practices – visual perception – limits of short-term memory – visually encoding data – Gestalt principles – principles of visual perception for dashboard design
UNIT V INFORMATION DASHBOARD DESIGN II
Characteristics of dashboards – key goals in visual design process – dashboard display media – designing dashboards for usability – meaningful organization – maintaining consistency – aesthetics of dashboards – testing for usability – case studies: sales dashboard, CIO dashboard, Telesales dashboard, marketing analysis dashboard
COURSE OUTCOMES:
Upon completion of the course, the students will be able to
Explain principles of visual perception
Apply core skills for visual analysis
Apply visualization techniques for various data analysis tasks
Design information dashboard
REFERENCES:
1. Stephen Few, "Now you see it: Simple Visualization techniques for quantitative analysis", Analytics Press, 2009.
2. Stephen Few, "Information dashboard design: The effective visual communication of data", O'Reilly, 2006.
3. Edward R. Tufte, "The visual display of quantitative information", Second Edition, Graphics Press, 2001.
4. Nathan Yau, "Data Points: Visualization that means something", Wiley, 2013.
5. Ben Fry, "Visualizing data: Exploring and explaining data with the processing environment", O'Reilly, 2008.
6. Gert H. N. Laursen and Jesper Thorlund, "Business Analytics for Managers: Taking business intelligence beyond reporting", Wiley, 2010.
7. Evan Stubbs, "The value of business analytics: Identifying the path to profitability", Wiley, 2011.