Difference between revisions of "Lesson01"
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<Font size =5>'''Introduction to Visual Analytics'''</font> | <Font size =5>'''Introduction to Visual Analytics'''</font> | ||
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== Content == | == Content == | ||
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|width="30pt"|Time required | |width="30pt"|Time required | ||
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A Tour through the Visualization Zoo [http://queue.acm.org/detail.cfm?id=1805128]'''Must read!''' | A Tour through the Visualization Zoo [http://queue.acm.org/detail.cfm?id=1805128]'''Must read!''' | ||
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Visual Analytics - Mastering the Information Age [http://www.youtube.com/watch?v=5i3xbitEVfs] | Visual Analytics - Mastering the Information Age [http://www.youtube.com/watch?v=5i3xbitEVfs] | ||
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|Day 3||60 mins||Demystifying Visual Analytics, ''IEEE Computer Graphics and Applications, March/April 2009'' e-journal @smu library | |Day 3||60 mins||Demystifying Visual Analytics, ''IEEE Computer Graphics and Applications, March/April 2009'' e-journal @smu library | ||
| − | + | The beauty of data visualization [http://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.html] | |
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| + | Data Visualisation, Australian Bureau of Statistics Research Paper, July 2007 [http://www.abs.gov.au/ausstats/abs@.nsf/mf/1211.0.55.001] | ||
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|Day 4||60 mins|| | |Day 4||60 mins|| | ||
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Robert Kosara (2012) Visualization: It’s More than Pictures! [http://stat-computing.org/newsletter/issues/scgn-22-1.pdf] | Robert Kosara (2012) Visualization: It’s More than Pictures! [http://stat-computing.org/newsletter/issues/scgn-22-1.pdf] | ||
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| − | |Day 5|| | + | |Day 5||3 hours|| |
| − | + | Self-Learning Tableau | |
| + | * Getting Started [http://www.tableau.com/learn/tutorials/on-demand/getting-started] | ||
| + | * Tableau Interface [http://www.tableau.com/learn/tutorials/on-demand/tableau-interface] | ||
| + | * Connecting to Data: From Getting Started with Data to Data Blending [http://www.tableau.com/learn/tutorials/on-demand/getting-started-data] | ||
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== References == | == References == | ||
Latest revision as of 20:16, 13 August 2016
IS428 Visual Analytics for Business Intelligence
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Introduction to Visual Analytics
Content
Introduction to the course
- Why this course?
- What does it cover?
- Who is involved?
- What assignments?
- Rules to be followed
Motivations of Visual Analytics
- Massive data
- Complex problem
- Visual Representation
- New visual paradigm
- Hidden insight
The Visual Analytics Framework
- The Science of Analytical Reasoning
- Sense-Making Methods
- Components of visual analytics
- History of visual analytics
- The visual analytics process
- Application challenges
- Technical challenges
A Gallery of Visual Analytics applications
Hands-on Session
Self-learning Tableau
- Getting Started [1]
- Tableau Interface [2]
- Connecting to Data: From Getting Started with Data to Data Blending
My First Date with Tableau
Daily Readings
| Day | Time required | Readings |
| Day 1 | 60 mins | Why Visual Analytics [3]Must view!
A Tour through the Visualization Zoo [4]Must read! |
| Day 2 | 60 mins |
Visual analysis for everyone [5] Visual Analytics - Mastering the Information Age [6] |
| Day 3 | 60 mins | Demystifying Visual Analytics, IEEE Computer Graphics and Applications, March/April 2009 e-journal @smu library
The beauty of data visualization [7] Data Visualisation, Australian Bureau of Statistics Research Paper, July 2007 [8] |
| Day 4 | 60 mins |
Andrew Gelman and Antony Unwin (2011) Infovis and Statistical Graphics: Different Goals, Different Looks [9] Robert Kosara (2012) Visualization: It’s More than Pictures! [10] |
| Day 5 | 3 hours |
Self-Learning Tableau
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References
James J. Thomas & Kristin A. Cook (ed) (2005) Illuminating the Path: The Research and Development Agenda of Visual Analytics [14]
