Business Data Visualization - updated in fall 2014

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Overview of data visualization and its position in business intelligence. …

Overview of data visualization and its position in business intelligence.
- What is (business) data visualization?
- The role and value of data visualization in information seeking and decision making
- Business data visualization design basics
- Basic visual forms
- Visual elements
- Visual properties (SCOPeS)
- Charts
- Data visualization tools and choices

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  • provide a high level overview of complex data sets;identify patterns and trends in data;identify structures and relationships in data;To form strong contrast to it is easy to focus on areas of “interest”; identify anomalies in data;Productivity: time sensitive response; understanding in short timeMemorization
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Transcript

  • 1. Business Data Visualization IT 6713 BI J.G. Zheng Fall 2014 http://jackzheng.net/teaching/it6713/
  • 2. Credit Card Payments Report Legend: OK – “On Time”; 10 – “0 to 10 days late”; 20 – “10 to 20 days late”; 30 – “20 to 30 days late” 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 OK Quickly identify the credit patterns for these 3 customers.
  • 3. Credit 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 OK Legend: OK – “On Time”; 10 – “0 to 10 days late”; 20 – “10 to 20 days late”; 30 – “20 to 30 days late”
  • 4. Overview What is (business) data visualization? The role and value of data visualization in information seeking and decision making Business data visualization design basics Basic visual forms Visual elements and properties (SCOPeS) Charts Data visualization tools and choices
  • 5. What is Business Data Visualization? Data/information visualization To form a mental imagery representation of data/information (meaning) The process of representing data as a visual image 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, direct
  • 6. Why 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 data comprehension and enhance problem solving capabilities Provide a high level overview of complex data sets Exploiting the human visual system to extract additional (implicit) information/meaning Ease the cognitive load of information processing Recall or memorize data More specifically (see examples in the following slides) Identify structures or relationships Identify patterns and trends Quickly focus on area of interest or area of difference (can be an anomaly) More comprehendible with reality
  • 7. Identify Structures/Relationships Does June report to Joy? Employee Reportsto Jane Jack Jessie Jane Jason Jane John Joy Joseph Joy Joy Jack June Jessie Jack Jane Joy Jessie Jason John June Joseph
  • 8. Identify Trends and Patterns What's the difference between these two cities? Which one is Atlanta? In 10 seconds?
  • 9. Identify Trends and Patterns What's the difference between these two cities? Which one is Atlanta? In 10 seconds? Monthly average temperature Monthly average precipitation
  • 10. Quickly Focus on Area of Interests http://finviz.com/map.ashx
  • 11. More Comprehendible with Reality
  • 12. How to design a visualization? Understand human information and analytic behavior http://www.cc.gatech.edu/~stasko/papers/infovis05.pdf Choice of visual forms Visual form is the basic style a visualization is presented. It can be categorized as embedded visual, standalone visual, and combined visual. Choice of visual elements Visual elements are the basic building blocks in a chart or diagram to visualize data items. The most fundamental and abstract elements are: point, line, surface (area), and volume (3D). These basic elements, and the more complex elements built up on them, can represent almost anything in a visualization. Choice of visual properties Visual properties are used to "decorate" visual elements, so that the values or categories of data items can be directly and easily perceived and understood by human. Summarized as "SCOPeS" Design principles, best practices, and pitfalls -More to be covered in other classes
  • 13. Visual Forms/Styles Style Description Types/Examples Embedded visuals Embedded in a pre-define presentation (paragraphs of text,tables, etc.) Conditional formatting (Visual cues) Inline chart: Sparkline Standalone visuals Occupya larger space and coherently displayed as an complete entity Illustrational diagrams Infographics Map Charts Motion charts Table Combined visuals A combination of different types of visuals Dashboard Infographics
  • 14. Conditional Formatting Conditional formatting Direct formatting on text or numbers using visual properties, embedded in a pre-established presentation Example Golf http://www.masters.com/en_US/scores/ Tag cloud
  • 15. Sparkline A sparklineis 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. http://en.wikipedia.org/wiki/Sparkline Examples http://omnipotent.net/jquery.sparkline/ http://www.klipfolio.com/blog/table-component-overview
  • 16. Illustrational Diagrams Illustrational diagrams Mainly to visualize quantitative as well as qualitative data to illustrate their features, relationships, sequences, etc. http://en.wikipedia.org/wiki/Diagram Examples Flow chart: http://en.wikipedia.org/wiki/Flowchart Structure diagram: http://en.wikipedia.org/wiki/Data_structure_diagram Tree diagram: http://en.wikipedia.org/wiki/Tree_structure Spatial map: https://maps.google.com/gallery/
  • 17. Infographics Information graphics or infographicsare 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 vividly communicate complex information (multiple variables or dimensions). Example http://dailyinfographic.com/ http://www.cooldailyinfographics.com/ http://blogs.scientificamerican.com/sa- visual/2014/10/14/sa-recognized-for-great-infographics/
  • 18. Chart Chart is a unique combination of symbols (visual elements) with visual properties which directly represents quantitative values http://en.wikipedia.org/wiki/Chart Chart vs Diagram No explicit defined difference. Diagram is considered to include chart. Chart is more abstract and focus on quantitative values
  • 19. Common Chart TypesBar chart Uses rectangular bars with lengths proportional to the values they represent. Often used to display and compare discrete data, or categorical dataLine 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 (or its angle and area) is proportional to the value it represents To represent the different parts of a whole, or the % of a total
  • 20. Other Common Charts General types Area chart, Radar/Spider chart, Petal chart, Scatter chart, bubble chart, Dial or gauge chart Tree map: http://en.wikipedia.org/wiki/Treemapping Field specialized charts Pareto (combo) chart (line/bar charts with left and right axis): http://en.wikipedia.org/wiki/Pareto_chart Stock market: candlestick chart: http://en.wikipedia.org/wiki/Candlestick_chart Project management: Gantt chart: http://en.wikipedia.org/wiki/Gantt_chart Impacting factors and drivers: waterfall/bridge chart: http://en.wikipedia.org/wiki/Waterfall_chart Marketing: perceptual map: http://en.wikipedia.org/wiki/Perceptual_mapping Performance: bullet graphs: http://en.wikipedia.org/wiki/Bullet_graph Heat map: http://en.wikipedia.org/wiki/Heat_map More chart types http://en.wikipedia.org/wiki/Chart http://www.amazon.com/Information-Graphics-Comprehensive-Illustrated- Reference/dp/0195135326 https://developers.google.com/chart/interactive/docs/gallery http://www.inetsoft.com/business/chart_gallery/ http://www.visualmining.com/resource/chartgallery/
  • 21. Motion charts A motion chart is an animated chart which allows efficient visualization of data changes along a dimension (typically temporal dimension). http://en.wikipedia.org/wiki/Motion_chart https://developers.google.com/chart/interactive/docs/ gallery/motionchart Examples http://www.google.com/publicdata/directory http://www.amcharts.com/inspiration/motion-chart/ http://tableau7.wordpress.com/2014/01/12/motion- map-chart/
  • 22. Choose a Chart Figure from http://www.extremepresentation.com/design/charts/or http://extremepresentation.typepad.com/blog/2008/06/visualization-taxonomies.html Online chooser with templates: http://labs.juiceanalytics.com/chartchooser/
  • 23. Visual Properties: SCOPeS Visual property is a basic feature that can represent different values of a particular dimension of data They can be used together to represent multiple dimensions of data SCOPeS Shape Color Orientation Position Texture Size
  • 24. Visual Property: Shape Shapes are usually used to represent different type of things, or nominal or discrete data (e.g., category) Type of shapes Shapes can be formed using simple shapes: square, triangle, etc. More complex shapes also can be formed by combination of simple shapes: icon, marker, etc. Example http://www.masters.com/en_US/scores/ ERD: http://en.wikipedia.org/ wiki/Entity-relationship_diagram
  • 25. Visual Property: ColorColor is the most common visual property used for both categorical data and continuous data. Color also include properties like hue, brightness, and gray scale. Color can be used to represent both dimensions and measures Example http://www.gasbuddy.com/gb_gastemperaturemap.aspx(color to represent gas price) http://en.wikipedia.org/wiki/Pie_chart(colors in pie chart commonly represent categories)
  • 26. Visual Property: Orientation Orientation can be seen as variations of a particular shape or pattern pointing to different directions. An common example is arrows or hands pointing to different directions. Examples http://voyager8.blogspot.com/2014/01/the-historical-relationship-between.html
  • 27. Visual Property: Position Data values can be visualized as absolute positions in the visualization, or as the relative distance between elements. Position is commonly used to visualize the placement of data items against a pre- established scheme (such as a Cartesian coordinate system), categorization and grouping of date items in terms of similarities and differences, or spatial distances (especially used with maps). Examples http://www.gartner.com/technology/research/methodologies/research_mq.jsp http://en.wikipedia.org/wiki/Cluster_analysis
  • 28. Visual Property: Texture Texture is important when color sensitivity is an issue. Implementations include fill patterns, border patterns, shadow, etc. Examples
  • 29. Visual Property: Size The size of an element is an important property used for continuous data values. It can be implemented as length, width, height, area, angle, etc. For various reasons, it is common that the size property does not directly and truly represent the underlying value. In these cases, it must be very careful to design the size property, because unreasonable distortions will impact human perception. Examples
  • 30. Composition of Multiple Properties More complex visual elements (such as icons and symbols) can be built based on the basic elements and properties discussed above. Combinations of these properties can be used to represent multi-dimensional data in the same visualization. Animations (such as blinking, movement, spinning, etc.) are based on some dynamic changes of these properties, and they can be used for richer meaning and grab greater attention.
  • 31. Visual Properties used for OLAP Measure Dimension Shape ** Color * ** Orientation * * Position ** * Texture ** Size ** * •Use one visual property to represent one dimension attribute. •Use different visual properties, instead of different values of the same visual property, for different dimensions (or dimension attributes). •Use different visual elements for different measures.
  • 32. Data Visualization Tools User oriented tools Office: Microsoft Excel, PowerView, PowerMap, Visio Online: Google Docs Spreadsheet Google Chart creators: http://dexautomation.com/googlechartgenerator.php Other free online charting tools http://www.onlinecharttool.com/ http://nces.ed.gov/nceskids/createagraph(for kids) Enterprise reporting tools (usually as a part of the complete BI system) SSRS, SAP Crystal, etc. Standalone visualization tool (desktop or web based) Tableau: http://www.tableausoftware.com/public/ QlikView, Dundas, iDahsboard, etc. Developer oriented libraries and APIs Programming library:, dotNetCharting, Telerik, Nevron, amCharts, D3, etc. Web API: Google Chart API (https://developers.google.com/chart/) More http://www.creativebloq.com/design-tools/data-visualization-712402 http://www.computerworld.com/article/2506820/business-intelligence/chart-and-image-gallery-30- free-tools-for-data-visualization-and-analysis.html
  • 33. Data Visualization: Sample (Real) Job https://www.linkedin.com/groups/Im-looking-Data-Visualization-Analyst- 80552.S.131082745Job Description highlights: Responsible for the management of database analysis projects in support of business initiatives. Data visualization (DV) expertise to design, develop and implement clear, interactive and succinct visualizations by processing and analyzing large quantities of (un)structured data. Candidate should have ability to turn raw data into compelling, lively stories, enriched with powerful, clear visualizations. These visualizations would also provide end-users an ability to discover relationships within related data in fresh and innovative ways. Updates visualization items as defined by department, in accordance with system protocol and requests from relevant departments. Serves as a liaison between business stakeholders and technology resources to optimize processes and designed visualization functionality. Assists with user acceptance testing for new information dashboards and/or analytical systems. More: https://www.linkedin.com/jobs2/view/12915000 http://www.jeffersondavis.com/job-description-data-visualization-analyst-i.html
  • 34. BI and Visualization Resources General textbook and reference “Introduction to Information Visualization”, by Riccardo Mazza, Springer, 2009, ISBN 1848002181 http://www.amazon.com/Information-Graphics-Comprehensive-Illustrated- Reference/dp/0195135326 News, blog, magazines http://mashable.com/category/data-visualization/ http://hbr.org/special-collections/insight/visualizing-data http://apandre.wordpress.com/ http://nbremer.blogspot.com/ http://understandinggraphics.com/ https://plus.google.com/photos/+AndreiPandre/albums/5481981245951662737?banner=pwa Communities and organizations http://www.visualizing.org/ http://www.interaction-design.org/ Company http://www.perceptualedge.com/ http://blog.visual.ly/ 34
  • 35. BI and Visualization Resources 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 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 Visualizations in specific application domains “Visual Explorations in Finance,” edited by G. Deboeckand T. Kohonen, Springer, 1998, ISBN 3540762663 “Performance Dashboards: Measuring, Monitoring, and Managing Your Business”, by Wayne W. Eckerson, Wiley, 2005, ISBN 0471724173 35