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Business Data Visualization
IT 7113 Data Visualization
J.G. Zheng
Spring 2017
http://jackzheng.net/teaching/it7113/
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”
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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
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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
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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 4 customers.
2
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”
Quickly identify the credit patterns for these 4 customers.
3
Overview
• This lecture is a high level overview of data visualization and brief introduction of its basic areas:
– What is (business) data visualization? What are the types of visualization? What are the related terms and fields? How are they similar or different?
– The role and value of data visualization in information seeking and decision making (BI, analytics, etc.)
– Basic data visualization elements and forms
– Data visualization tools
– Skills, jobs, and career
4
Visualization
• Visualization– To form a concrete and directly vision-perceivable image
utilizing a combination of visual elements (shapes) and variables like color, positions, etc.
• What to be visualized– Visible reality: person, world, nature,
– Hidden reality: earth core, blood, universe
– Invisible reality: wind, air, heat, electron, sound, smell
– Abstract: data, idea, hierarchy, process
• Types of visualization forms– 2D vs. 3D
– Virtual vs materialized
– Static vs. motion
5
Data Visualization
• Data visualization is the visual and interactive exploration and graphic representation of data of any size, type (structured and unstructured) or origin.– To form a mental imagery representation of
data/information (meaning)
– The process of presenting data as a visual images
• The purpose of data visualization– Analysis and decision support
– Information seeking, browsing, navigation
– Understanding – comprehension of ideas
– Artistic (beauty) expression and appreciation
– Entertaining – have fun
6
Data Visualization
http://prezi.com/qvhyfup5z7yz/dashboard-design-making-reports-pop/
7
Related Terms and Fields
• Data presentation
• Information visualization (including
infographic)
• Scientific visualization
• Computer graphics
• Reality visualization (VR, AR)
• Simulation http://setosa.io/bus/
8
Data Presentation
• (In the field of math) data presentation is the method by which people summarize, organize and communicate information using a variety of tools, including tables and diagrams/charts.
http://www.slideshare.net/ahsanshafiq90/data-presentation-2-15572325
9
Information Visualization
• A very close field, and very often used as the synonym to data visualization
• Information more often more general and more qualitative– Process/movement
– Concepts and ideas
• Utilizes more free forms of visual diagrams or illustrations (illustrational diagrams)
• Infographics is another common form– http://www.jackhagley.com/What-s-the-difference-
between-an-Infographic-and-a-Data-Visualisation
10
Illustration of an Idea/Concept
11
Scientific Visualization
• “Primarily concerned with the visualization of three-dimensional phenomena (architectural, meteorological, medical, biological, etc.), where the emphasis is on realistic renderings of volumes, surfaces, illumination sources, and so forth.”– https://en.wikipedia.org/wiki/Scientific_visualization
• Physical science visualization– Visualization (simulation) of reality (universe, sun,
explosion, atom, climate, etc.)
• Mathematical model/algorithm visualization– http://acko.net/blog/how-to-fold-a-julia-fractal/
12
What is Business Data/Information
Visualization?• Business is a general term to describe everyday human activities
and operations that make an system running, including commerce, education, sports, entertainment, etc.
• Business data features– Abstract
– Often structured or semi-structured
– Multidimensional
– Often quantitative
– Directly comprehendible by average human
• Business data visualization– Visualization of business data mainly for communication,
information seeking, analysis, and decision support
– Using simple, standard, abstract, direct image/chart/diagram
– Utilizes data binding techniques to generate visualizations
13
Yes Business Data Visualization
• Charts and diagrams in reports
• Performance dashboards
• Visual information presentation
• https://en.wikipedia.org/wiki/Chart
• https://www.geckoboard.com/learn/dashboard-examples/
• https://www.productchart.com/smartphones/
• http://www.mapsdata.co.uk/showcase/
• https://www.census.gov/dataviz/
14
Not Business Data Visual
• These examples are not really considered to
be business data visualization which aims at
decision support – not the focus of this class
– http://classes.dma.ucla.edu/Spring13/161/projec
ts/students/david/project-5/html/?/image-gallery/
– https://en.wikipedia.org/wiki/Fractal
– https://en.wikipedia.org/wiki/Scientific_visualizati
on
– https://visual.ly/m/design-portfolio/
15
Why use visualization?
• The Value of Data Visualization: https://www.youtube.com/watch?v=xekEXM0Vonc
• 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
16
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
17
Identify Trends and PatternsWhat's the difference between these two cities? Which one is Atlanta? In 10 seconds?
18
Identify Trends and Patterns
Monthly average temperature
Monthly average precipitation
What's the difference between these two cities? Which one is Atlanta? In 10 seconds?
19
Quickly Focus on Area of Interests
• Which stock performed different from others?
http://finviz.com/map.ashx
20
More Comprehendible with Reality
21
Data Visualization Concepts
• 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.
• Visual variables (visual properties, or visual attributes)– Visual variables 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"
• Visual forms/styles – Visual form is the basic style a visualization is presented.
22
Visual Variables: SCOPeS
• Visual variable or 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
• The following six can be summarized as “SCOPeS”– Shape
– Color
– Orientation
– Position
– Texture
– Size
• Relevant sources:– http://www.infovis-wiki.net/index.php?title=Visual_Variables
– http://wiki.gis.com/wiki/index.php/Visual_Variables
23
Basic Visual Forms/Styles
Style Description Types/Examples
Embedded
visuals
Embedded in a pre-define
presentation (paragraphs of
text, tables, etc.) in a larger
context
• Conditional formatting
(Visual cues)
• Inline chart: Sparkline
block visuals Occupy a larger space and
coherently displayed as an
complete entity
• Data table
• Charts
• Illustrational diagrams
(illustrations)
• Map
Standalone
visuals
Usually not mixed with other
type of content; can be
standalone by itself as an
application. A combination
of different types of visuals.
• Dashboard
• Infographics
• Scorecards
• Visual analysis tools
24
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
25
Sparkline
• 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.
– http://en.wikipedia.org/wiki/Sparkline
• Examples– http://omnipotent.net/jquery.sparkline/
– http://www.klipfolio.com/blog/table-component-overview
Sparkline
26
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
– https://en.wikipedia.org/wiki/Illustration
• Examples– http://extremepresentation.com/design/7-charts/
– Flow chart: http://en.wikipedia.org/wiki/Flowchart
– http://familydoctor.org/familydoctor/en/health-tools/search-by-symptom/cough.html
– 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/
– Time line: http://vizualize.me/
27
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
28
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
29
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 https://finviz.com/map.ashx
• More chart types– http://en.wikipedia.org/wiki/Chart
– http://www.excelcharts.com/blog/classification-chart-types/
– http://labs.juiceanalytics.com/chartchooser/index.html
– http://www.amazon.com/Information-Graphics-Comprehensive-Illustrated-Reference/dp/0195135326
– http://www.inetsoft.com/business/chart_gallery/
30
Choose a Chart
– Figure from http://extremepresentation.com/design/7-charts/ or
http://extremepresentation.typepad.com/blog/2008/06/visualization-taxonomies.html
– Online chooser with templates: http://labs.juiceanalytics.com/chartchooser/31
Map Based Visualization
• Real world location based
– Geo location, Geo Map
– Internal structure (building, hospital, mall, airplane)
– Geo chart
• Tile map: an abstract representation of space/map
– hex-tile map
• Logical (virtual) structure
– Network diagram
– Process diagram
– Strategy map
32
Infographics
• 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 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/
– https://visual.ly/m/design-portfolio/
• Not exactly same as data visualization– http://www.jackhagley.com/What-s-the-difference-between-an-
Infographic-and-a-Data-Visualisation
33
Digital Dashboard
• A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.
– Dashboard Confusion, Stephen Few, http://www.perceptualedge.com/articles/ie/dashboard_confusion.pdf
• Provides an high level or focused overview of key data– The data is generally KPIs and shows trends, breakdowns, and comparisons against a
forecast or historical data
– A Dashboard generally contains a variety of different views of data: charts, diagrams, tables, standalone numbers, interactive controls (such a filters)
• Dashboard vs. charts, visualization, animation, diagram, interactive screen, simulation
– http://www.dashboardinsight.com/articles/digital-dashboards/fundamentals/what-is-a-dashboard.aspx
• The Values of Dashboard– Allow decision makers to see a variety of relevant data that affects their divisions or
departments
– Quickly understand data and respond quickly at one place; save time over running multiple reports
– More: http://www.bidashboard.org/benefits.html
34
34
Dashboard Uses and Examples
• Where is it used?– Public report: The IT Dashboard http://it.usaspending.gov
• http://www.youtube.com/watch?v=4fe39dh6xFQ
– Performance monitoring• http://www.google.com/appsstatus
• https://www.google.com/analytics
– Election: http://elections.nytimes.com/2012/results/president
– Sports: http://games.idashboards.com/winter2010/?guestuser=vancouver
– Business: • Performance dashboard
• Scorecard
• Strategy map
• More real examples– http://www.klipfolio.com/resources/dashboard-examples/
– http://www.idashboards.com/solutions/
– http://dashboardsbyexample.com
– http://www.dashboardzone.com
35
Visual Analysis Tool
• These are visualizations or dashboards with intensive selections, filters, and other controls to manipulate the visualization frequently– http://www.dashboardinsight.com/articles/digital-
dashboards/fundamentals/what-is-a-dashboard.aspx
36
Scorecards
• A scorecard is special type of dashboard
typically with a tabular visualization of
measures and their respective targets with
visual indicators to see how each measure is
performing against their targets at a glance
37
More Visualization Forms/Methods
• A periodic table of visualization methods (Interactive)
– http://www.visual-literacy.org/periodic_table/periodic_table.html
38
Composition of Multiple Elements/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.
39
Data Visualization (Dashboard) Tools
• Enterprise reporting tools (usually as a part of the complete BI system)
– SSRS, SAP Crystal, etc.
• Standalone visualization tool (desktop)– Tableau:
http://www.tableausoftware.com/public/
– Power BI
– QlikView, Dundas, etc.
• Cloud (web) based– http://idashboards.com
– http://www.klipfolio.com/
• Embedded tools– Microsoft Excel, Visio
– Google Docs Spreadsheet http://www.benlcollins.com/spreadsheets/dynamic-dashboard-in-google-spreadsheets/
• Developer oriented libraries and APIs– Programming library:, D3, dotNetCharting,
Telerik, Nevron, amCharts, etc.
– Web API: Google Charts (https://developers.google.com/chart/)
• Casual charting tools– 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)
• More– http://selection.datavisualization.ch
– 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
– https://www.g2crowd.com/categories/business-intelligence
40
Notes on Excel
• Excel is the best tool to learn and apply sound data visualization principles and best practices
• “Many individuals and small business users will discover that MS Excel offers much of what they need without the need.”– Data Visualization - HorizonWatch 2015 Trend Report
http://www.slideshare.net/HorizonWatching/data-visualization-horizon-watch-2015-trend-report-client-version-28jan2015
• Excel is the best tool for executive dashboard prototyping, because of its flexibility and development costs.– http://www.excelcharts.com/blog/prototype-executive-dashboard-excel/
• Main visualization features provided by Excel (practice these following the lab instructions)– Conditional formatting
– Chart (Pivot Chart)
– Slicer (visual filter)
– Sparkline
41
Skills in Data Visualization Dev
• Human information behavior and cognition
• Visualization design
– Charts, diagrams
• UI design, interaction design
– Data exploration, information seeking, navigation
• Artistic design
• Data processing
• Programming
• Domain knowledge
42
Data Visualization: Sample JobsDesired Skills
• Intermediate skills with SQL, HTML, CSS and
Javascript/Javascript libraries
Comfortable in working with large, multi-dimensional data sets
(data manipulation and analysis)
• Experience with any of the data visualization software will be
added advantage: Tableau, Qlikview, Spotfire, R or any other
data visualization software
Advanced Excel skills
• Basic understanding of GIS concepts and how they can be
included in visualizations
• Basic experience working with IT server architectures and
production deployments
• Degree in Statistics/Mathematics/MIS/Computer Science
/Graphic Designhttp://www.jeffersondavis.com/job-description-data-visualization-analyst-i.html
The Data Visualization Analyst will be responsible for understanding the
strategic needs of the business and translating high-level objectives into the
development of visual data analysis and dashboards to support the category
management and product strategy teams. The candidate will need to need to
understand how to create and manipulate large data sets and use various
visualization tools to meet the needs of needs of their customers. To ensure
adoption by the business, this position will be required to ensure the quality of
each dashboard release, data refresh and adhere to a regular refresh and
dashboard publishing schedule.
https://www.linkedin.com/jobs2/view/12915000
https://www.linkedin.com/groups/Im-looking-
Data-Visualization-Analyst-
80552.S.131082745 Job Description:
• 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.
43
44
More Resources• General textbook and reference
– “Introduction to Information Visualization”, by Riccardo Mazza, Springer, 2009, ISBN 1848002181
– “Information Dashboard Design” 2nd, by Stephen Few, 2013, http://www.amazon.com/gp/product/1938377001/
– “Business Dashboards: A Visual Catalog for Design and Deployment”, by Nils Rasmussen, et al. ,Wiley, 2009, ISBN 0470413476
– 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/
– http://flowingdata.com/
– https://plus.google.com/111053008130113715119
– https://plus.google.com/112388869729541404591
– https://www.linkedin.com/topic/data-presentation
• Company– http://www.perceptualedge.com/
– http://blog.visual.ly/
45