Business Data Visualization

IT 6713 BI

J.G. Zheng

Fall 2014

http://jackzheng.net/teaching/it6713/

Credit Card Payments ReportLegend:

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.

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”

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

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

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

Identify Structures/Relationships

Does June report to Joy?

Employee Reports to

Jane Jack

Jessie Jane

Jason Jane

John Joy

Joseph Joy

Joy Jack

June Jessie

Jack

Jane

Joy

Jessie

Jason

John

June

Joseph

Identify Trends and PatternsWhat's the difference between these two cities? Which one is Atlanta? In 10 seconds?

Identify Trends and PatternsWhat's the difference between these two cities? Which one is Atlanta? In 10 seconds?

Monthly average temperature

Monthly average precipitation

Quickly Focus on Area of Interests

http://finviz.com/map.ashx

More Comprehendible with Reality

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

Visual Forms/StylesStyle 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

Occupy a larger space and coherently displayed as an complete entity

Illustrational diagramsInfographicsMapChartsMotion chartsTable

Combined visuals A combination of different types of visuals

DashboardInfographics

Conditional FormattingConditional 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

SparklineA 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. http://en.wikipedia.org/wiki/Sparkline

Examples http://omnipotent.net/jquery.sparkline/ http://www.klipfolio.com/blog/table-component-overview

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/

InfographicsInformation 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 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/

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

Common Chart Types

Bar chart

Uses rectangular bars with lengths proportional to the values they represent.

Often used to display and compare discrete data, or categorical data

Line chart

Displays continuous (or semi-continuous) data serials

Often used to visualize a trend in data over intervals of time

Pie 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

Other Common ChartsGeneral 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/

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/

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/

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

Visual Property: ShapeShapes 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

Visual Property: Color

Color 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.as

px (color to represent gas price)

http://en.wikipedia.org/wiki/Pie_chart (colors in pie chart commonly represent categories)

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

Visual Property: PositionData 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/resear

ch/methodologies/research_mq.jsp http://en.wikipedia.org/wiki/Cluster_analysi

s

Visual Property: Texture

Texture is important when color sensitivity is an issue. Implementations include fill patterns, border patterns, shadow, etc.

Examples

Visual Property: SizeThe 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

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.

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.

Data Visualization ToolsUser 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

Data Visualization: Sample (Real) Job

https://www.linkedin.com/groups/Im-looking-Data-Visualization-Analyst-80552.S.131082745 Job 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

BI and Visualization ResourcesGeneral 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?banne

r=pwa

Communities and organizations http://www.visualizing.org/ http://www.interaction-design.org/

Company http://www.perceptualedge.com/ http://blog.visual.ly/

34

BI and Visualization ResourcesInformation 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. Deboeck and T. Kohonen, Springer, 1998, ISBN

3540762663 “Performance Dashboards: Measuring, Monitoring, and Managing Your Business”, by Wayne W.

Eckerson, Wiley, 2005, ISBN 0471724173

35