Difference between revisions of "Lesson 1"
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| − | + | <font size="5">'''Introduction to Visual Analytics for Business Intelligence'''</font> | |
| − | <font size="5">'''Introduction to Visual Analytics'''</font> | ||
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* Course Overview | * Course Overview | ||
| − | + | * Motivation of Visual Analytics | |
| + | * What Visual Analytics is | ||
| + | * Visual Analytics in History | ||
| + | * Intents of Visual Analytics Applications | ||
| + | * Visual Analytics Techniques: basic graphical methods | ||
| + | * Visual Analytics Tools | ||
=Core Readings= | =Core Readings= | ||
| + | * Thomas, J.J. & Cook, K.A. (2006) "[https://www-computer-org.libproxy.smu.edu.sg/csdl/magazine/cg/2006/01/mcg2006010010/13rRUxBa5ej A Visual Analytics Agenda]", ''IEEE Computer Graphics and Applications'', January 2006, Vol.26(1), pp.10-13 | ||
* [https://www.youtube.com/watch?v=LYKO_6KPZCM/ VIVA – What is Visual Analytics?] | * [https://www.youtube.com/watch?v=LYKO_6KPZCM/ VIVA – What is Visual Analytics?] | ||
* [https://www.youtube.com/watch?v=5uGRGqCFryg/ Why Visual Analytics] | * [https://www.youtube.com/watch?v=5uGRGqCFryg/ Why Visual Analytics] | ||
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* [https://www.tableau.com/sites/default/files/whitepapers/the_5_most_influential_data_visualizations_of_all_time.pdf The 5 Most Influential Data Visualizations of All Time] | * [https://www.tableau.com/sites/default/files/whitepapers/the_5_most_influential_data_visualizations_of_all_time.pdf The 5 Most Influential Data Visualizations of All Time] | ||
* [https://www.tableau.com/sites/default/files/whitepapers/TS_WP_VA_F2_new_temp_0.pdf Whitepaper: Visual Analysis for Everyone] | * [https://www.tableau.com/sites/default/files/whitepapers/TS_WP_VA_F2_new_temp_0.pdf Whitepaper: Visual Analysis for Everyone] | ||
| + | * J.J. Thomas and K.A. Cook, eds. (2005) [https://ils.unc.edu/courses/2017_fall/inls641_001/books/RD_Agenda_VisualAnalytics.pdf Illuminating the Path: The Research and Development Agenda for Visual Analytics], IEEE CS Press. | ||
=All About Tableau= | =All About Tableau= | ||
| − | + | ==Things about Tableau Prof. Kam want you to know!== | |
| − | |||
* [https://graphics.stanford.edu/papers/polaris_extended/polaris.pdf Polaris: A System for Query, Analysis,and Visualization of MultidimensionalRelational Databases] | * [https://graphics.stanford.edu/papers/polaris_extended/polaris.pdf Polaris: A System for Query, Analysis,and Visualization of MultidimensionalRelational Databases] | ||
* [https://www.tableau.com/products/technology Tableau Technology] | * [https://www.tableau.com/products/technology Tableau Technology] | ||
Latest revision as of 11:12, 31 December 2019
IS428 Visual Analytics for Business Intelligence
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Introduction to Visual Analytics for Business Intelligence
Contents
Lesson Outline
- Course Overview
- Motivation of Visual Analytics
- What Visual Analytics is
- Visual Analytics in History
- Intents of Visual Analytics Applications
- Visual Analytics Techniques: basic graphical methods
- Visual Analytics Tools
Core Readings
- Thomas, J.J. & Cook, K.A. (2006) "A Visual Analytics Agenda", IEEE Computer Graphics and Applications, January 2006, Vol.26(1), pp.10-13
- VIVA – What is Visual Analytics?
- Why Visual Analytics
- Visual Analytics - Mastering the Information Age
- Chabot, C (2009) "Demystifying Visual Analytics", IEEE Computer Graphics and Applications, March 2009, Vol.29(2), pp.84-87.
- The 5 Most Influential Data Visualizations of All Time
- Whitepaper: Visual Analysis for Everyone
- J.J. Thomas and K.A. Cook, eds. (2005) Illuminating the Path: The Research and Development Agenda for Visual Analytics, IEEE CS Press.
All About Tableau
Things about Tableau Prof. Kam want you to know!
- Polaris: A System for Query, Analysis,and Visualization of MultidimensionalRelational Databases
- Tableau Technology
- Show Me: Automatic Presentation for Visual Analysis
Tutorial
- Getting Started with Data also self-learn the remaining videos under Connecting to Data
- Getting Started with Tableau Prep Builder. This is a brand-new product from Tableau designed to help everyone quickly and confidently combine, shape, and clean their data for analysis. You can learn more about Tableau Data Prep here. You are encouraged to view all the 12 videos under Tableau Prep.
