CP7017 DATA VISUALIZATION TECHNIQUES SYLLABUS FOR M.E. COMPUTER SCIENCE AND ENGINEERING REG 2013 - Anna University Internal marks 2018

CP7017 DATA VISUALIZATION TECHNIQUES SYLLABUS FOR M.E. COMPUTER SCIENCE AND ENGINEERING REG 2013

CP7017 DATA VISUALIZATION TECHNIQUES SYLLABUS
M.E. COMPUTER SCIENCE AND ENGINEERING
SEMESTER II

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

TOTAL : 45 PERIODS

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, GraphicsPress, 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. 

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