Business data visual

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Information about Business data visual

Published on November 8, 2012

Author: jgzheng

Source: slideshare.net

10/25/2012 Data Visualization Basics Jack G. Zheng Fall 2012Credit Card Payments Report 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 2000 OK OK OK OK OK OK OK OK OK OK OK OK 2000 OK OK OK OK OK OK OK OK OK OK OK OK 2001 OK OK OK 10 20 30 30 30 20 10 10 OK 2001 OK OK OK OK OK OK OK OK OK OK OK OK 2002 OK OK OK OK OK OK OK OK OK OK OK OK 2002 OK OK OK OK OK OK OK 10 OK OK OK OK 2003 OK 20 OK 10 OK OK OK OK OK OK OK OK 2003 OK OK OK 10 OK OK OK OK OK OK OK OK 2004 OK OK OK OK OK OK OK OK 30 OK OK OK 2004 OK OK OK OK OK OK OK OK OK 10 OK OK 2005 OK OK OK OK OK OK OK OK OK OK OK OK 2005 OK 10 OK OK OK OK OK OK OK OK OK OK 2006 OK OK OK OK OK 10 OK OK OK OK OK OK 2006 OK OK OK OK OK OK OK OK OK OK OK OK 2007 OK OK OK OK OK OK OK OK OK OK OK OK 2007 OK OK OK OK 10 OK OK OK OK OK OK OK 2008 OK OK OK OK OK OK OK OK OK OK OK OK 2008 OK OK OK OK OK OK OK OK OK OK 10 OK 2009 OK OK OK OK OK OK OK OK OK OK OK OK 2009 OK OK OK OK OK OK OK OK OK OK OK OK 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 2000 OK OK OK OK OK OK OK OK OK OK OK OK 2000 OK OK OK OK OK OK OK OK OK OK OK OK 2001 OK OK OK OK OK OK OK OK OK OK OK OK 2001 OK OK OK OK OK OK OK OK OK OK OK OK 2002 OK OK OK OK OK OK OK OK OK OK OK OK 2002 OK OK OK OK OK OK 20 20 OK OK OK OK 2003 OK OK OK OK OK OK OK OK OK OK OK OK 2003 OK OK OK 10 OK OK 30 20 OK OK OK OK 2004 OK OK OK OK OK OK OK OK OK OK OK OK 2004 OK OK OK OK OK OK 30 30 OK OK OK OK 2005 OK OK OK OK OK OK OK OK OK OK OK OK 2005 OK OK OK OK OK OK 20 30 20 OK OK OK 2006 OK OK OK OK OK OK OK 10 OK OK OK OK 2006 OK OK OK 10 OK OK 30 10 OK OK OK OK 2007 OK OK OK OK OK OK OK OK OK OK OK OK 2007 OK OK OK OK OK 30 20 30 10 OK OK OK 2008 OK OK OK OK OK 10 OK 20 OK 10 20 OK 2008 OK OK OK OK OK OK 30 10 OK OK OK OK 2009 OK 10 OK OK 30 30 OK OK OK 10 OK OK 2009 OK OK OK OK OK OK 10 20 OK OK OK OKLegend:OK – “On Time”; 10 – “0 to 10 days late”; 20 – “10 to 20 days late”; 30 – “20 to 30 days late” 1

10/25/2012Credit Card Payments Report 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 2000 OK OK OK OK OK OK OK OK OK OK OK OK 2000 OK OK OK OK OK OK OK OK OK OK OK OK 2001 OK OK OK 10 20 30 30 30 20 10 10 OK 2001 OK OK OK OK OK OK OK OK OK OK OK OK 2002 OK OK OK OK OK OK OK OK OK OK OK OK 2002 OK OK OK OK OK OK OK 10 OK OK OK OK 2003 OK 20 OK 10 OK OK OK OK OK OK OK OK 2003 OK OK OK 10 OK OK OK OK OK OK OK OK 2004 OK OK OK OK OK OK OK OK 30 OK OK OK 2004 OK OK OK OK OK OK OK OK OK 10 OK OK 2005 OK OK OK OK OK OK OK OK OK OK OK OK 2005 OK 10 OK OK OK OK OK OK OK OK OK OK 2006 OK OK OK OK OK 10 OK OK OK OK OK OK 2006 OK OK OK OK OK OK OK OK OK OK OK OK 2007 OK OK OK OK OK OK OK OK OK OK OK OK 2007 OK OK OK OK 10 OK OK OK OK OK OK OK 2008 OK OK OK OK OK OK OK OK OK OK OK OK 2008 OK OK OK OK OK OK OK OK OK OK 10 OK 2009 OK OK OK OK OK OK OK OK OK OK OK OK 2009 OK OK OK OK OK OK OK OK OK OK OK OK 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 2000 OK OK OK OK OK OK OK OK OK OK OK OK 2000 OK OK OK OK OK OK OK OK OK OK OK OK 2001 OK OK OK OK OK OK OK OK OK OK OK OK 2001 OK OK OK OK OK OK OK OK OK OK OK OK 2002 OK OK OK OK OK OK OK OK OK OK OK OK 2002 OK OK OK OK OK OK 20 20 OK OK OK OK 2003 OK OK OK OK OK OK OK OK OK OK OK OK 2003 OK OK OK 10 OK OK 30 20 OK OK OK OK 2004 OK OK OK OK OK OK OK OK OK OK OK OK 2004 OK OK OK OK OK OK 30 30 OK OK OK OK 2005 OK OK OK OK OK OK OK OK OK OK OK OK 2005 OK OK OK OK OK OK 20 30 20 OK OK OK 2006 OK OK OK OK OK OK OK 10 OK OK OK OK 2006 OK OK OK 10 OK OK 30 10 OK OK OK OK 2007 OK OK OK OK OK OK OK OK OK OK OK OK 2007 OK OK OK OK OK 30 20 30 10 OK OK OK 2008 OK OK OK OK OK 10 OK 20 OK 10 20 OK 2008 OK OK OK OK OK OK 30 10 OK OK OK OK 2009 OK 10 OK OK 30 30 OK OK OK 10 OK OK 2009 OK OK OK OK OK OK 10 20 OK OK OK OKLegend:OK – “On Time”; 10 – “0 to 10 days late”; 20 – “10 to 20 days late”; 30 – “20 to 30 days late”Overview What is business data visualization? Why and when to use visualization? Business data visualization basics  Basic forms of visualization  Visual properties - SSCOPE 2

10/25/2012What is Business Data Visualization? Data/information visualization  For form a mental imagery representation of data/information (meaning) Business data  Abstract  Structured or semi-structured  Multidimensional  Complicate relationship  Directly comprehendible by human Business data visualization  Visualization of business data mainly for communication, analysis, and decision support  Simple, abstract, directWhy use visualization? Visualization and BI  Information visualization is an important part of understanding for information seeking and decision making. Visualization tools have become increasingly important to business intelligence, in which people need technology support to make sense of and analyze complex data sets and all types of information. Visualizations help  Communicate (additional) meaning  Enhance problem solving capabilities  Ease the cognitive load of information processing  Recall or memorize data More specifically …  See following examples 3

10/25/2012Identify relationships Does June report to Joy? Employee Reports to Jane Jack Jessie Jane Jason Jane John Joy Jason Joy Joy Jack June JessieIdentify trends and patterns 4

10/25/2012Identify trends and patternsQuickly focus on area of interest http://www.cnbc.com/id/30231612 http://finviz.com/map.ashx 5

10/25/2012More comprehendible with reality http://www.traffic.com/Atlanta- Traffic/Atlanta-Traffic-Reports.htmlHow to design a visualization? Basic consideration  Choice of visual properties  SSCOPe  Choice of visual form (visual elements)  Embedded visuals  Visual cues, conditional formatting  Sparkline  Standalone visuals  Charts  Illustrational diagrams  Infographics Design principles, best practices, and pitfalls  More to be covered in other classes 6

10/25/2012SSCOPe Visual Properties Shape Golf Scores Size Federal debt Color Gas Heat Map Orientation hospital-dashboard Position Magic Quadrant Texture Source of incomeConditional Formatting Conditional formatting  Direct formatting on text or numbers using visual properties Example   Tag cloud 7

10/25/2012Sparkline A sparkline is a small chart embedded in a context of words, numbers, tables, images, or other type of information.  It presents the general shape of the variation in a simple and highly condensed way. Examples  http://omnipotent.net/jquery.sparkline/Charts Charts  A unique combination of symbols with visual properties which directly represents quantitative values Bar chart  Uses rectangular bars with lengths proportional to the values they represent.  Often used to display and compare discrete data, or categorical data 8

10/25/2012Line Chart Displays continuous (or semi-continuous) data serials Often used to visualize a trend in data over intervals of timePie Chart A circular chart divided into sectors, illustrating proportions. The arc length of each sector (and consequently its angle and area), is proportional to the value it represents To represent the different parts of a whole, or the percentages of a total 9

10/25/2012Other Common Charts General types  Area chart  Radar/Spider chart  Petal chart  Scatter chart, bubble chart  Dial or gauge chart  Tree map - http://finviz.com/map.ashx  Heat map Specialized chart  Stock market: candlestick chart  Project management: Gantt chart  Sale drivers: bridge chart  Marketing: perceptual mapIllustrational Diagrams Illustrational diagrams  Mainly to visualize quantitative as well as qualitative data to illustrate their features, relationships, sequences, etc. Examples  Pivot table  Flow chart  Tree diagram  Structure diagram  Map 10

10/25/2012Infographics Information graphics or infographics are graphic visual representations of information, data or knowledge.  http://en.wikipedia.org/wiki/Information_graphics Usually a mixture of text and multiple visual forms (charts, diagrams, images, tables, maps, lists, etc.) to quickly and clearly communicate complex information (multiple variables or dimensions). Example  http://en.wikipedia.org/wiki/Charles_Joseph_MinardSummary Key concepts  Information/data visualization  Business information/visualization  SSCOPe visual properties Key skills  Know basic types of charts to visualize business data  Understand their features, purposes and uses  Choose appropriate charts and visual properties for any given situation 11

10/25/2012Resources: Visualization Tools User oriented tools  Office: Microsoft Excel  Online: Google Docs Spreadsheet  Google Chart creators  http://dexautomation.com/googlechartgenerator.php  http://stereofrog.com/files/gcui/  Other free online charting tools  http://www.onlinecharttool.com/  http://nces.ed.gov/nceskids/createagraph Developer/system oriented tools  Web API  Google Chart API, Google Visualization API  Programming API  Crystal, dotNetCharting, Telerik, Nevron, amCharts, etc.  Dashboard  QlikView, Dundas, iDahsboard, etc.BI and Visualization:Textbook, Topics and Readings (1) General textbook  “Introduction to Information Visualization”, by Riccardo Mazza, Springer, 2009, ISBN 1848002181  Soukup, T., & Davidson, I. (2002). Visual Data Mining. New York: Jone Wiley & Sons.  “Information Visualization in Data Mining and Knowledge Discovery.” edited by Usama Fayyad, Georges Grinstein, Andreas Wierse, Morgan Kaufmann, 2001, ISBN 1558606890 Information behavior, cognitive styles  Wilson, T. D. (1981). On user studies and information needs. Journal of Librarianship, 37(1), 3-15.  Bowers, et al. (1990) “Intuition in the Context of Discovery,” Cognitive Psychology, 22, 72-110. Types of visualizations  Tegarden, D. P. (1999). Business Information Visualization. Communications of the AIS, 1(4)  “Information Graphics: A Comprehensive Illustrated Reference”, by Robert L. Harris, Oxford University Press, 2000, ISBN 0195135326 Visualization design, system usability  “Information Visualization: Design for Interaction,” by Robert Spence Prentice Hall, 2007, ISBN 0132065509  “Information Visualization”, by Colin Ware, Morgan Kaufmann, 2004, ISBN 1558608192 24 12

10/25/2012BI and Visualization:Textbook, Topics and Readings (2) Dashboard design  “Information Dashboard Design”, by Stephen Few , OReilly, 2006, ISBN 0596100167  “Business Dashboards: A Visual Catalog for Design and Deployment”, by Nils Rasmussen, et al. ,Wiley, 2009, ISBN 0470413476 Visual information exploration and design  Craft, B., Cairns, P., Beyond Guidelines: What Can We Learn from the Visual Information Seeking Mantra? 9th International Conference on Information Visualization, London, 2009 Visual data mining  Keim, D. A. (2002). Information Visualization and Visual Data Mining. IEEE Transactions on Visualization and Computer Graphics, 8(1), 1-8.  Oliveira, M. & Levkowitz, H. (2003). From Visual Data Exploration to Visual Data Mining: A Survey. IEEE Transactions on Visualization and Computer Graphics, 9(3), 378-394. Visualizations in specific application domains  “Visual Explorations in Finance,” edited by G. Deboeck and T. Kohonen, Springer, 1998, ISBN 3540762663  “Performance Dashboards: Measuring, Monitoring, and Managing Your Business”, by Wayne W. Eckerson, Wiley, 2005, ISBN 0471724173 25 13

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