http://idi.kennesaw.edu/it7113/


https://www.edocr.com/v/yqwmqeba/jgzheng/Business-Data-Visualization

for Analytics and Business Intelligence
A Comprehensive Overview
IT 7113 Data Visualization
http://idi.kennesaw.edu/it7113/
Dr. Jack Zheng
Version 7.1, Fall 2024
This lecture notes file is hosted at https://www.edocr.com/v/yqwmqeba/jgzheng/Business-Data-Visualization
Overview
Topics:
1. Basic concepts
– What is data visualization?
– What are the purposes and types of visualization?
2. What are the related terms and fields? How are they similar or
different?
3. Data visualization in business intelligence and analytics
– Basic data visualization elements and forms (types)
4. Design and development
– Principles, processes, applications and tools, IT support
5.
Learning and career
2
This lecture notes provides a high-level overview of data visualization
primarily used in business intelligence and analytics. This overview is
comprehensive and covers as many aspects as possible, but it keeps them
at a high level. More details are provided in additional lecture notes.
Sections
3
Data Visualization Concepts
Definition, basic concepts and terms
Values and benefits of data visualization
4
Data Visualization
• Key terms
– Data, visual
– Representation, presentation
– Purpose: perception and cognition
+ Interactivity:
– We emphasize data visualization as (part of or whole) a
software application, which also emphasizes the
interactive feature of this process.
5
Data visualization is the visual representation and
presentation of data for the purpose of enhancing
perception and cognition.
More details about interactivity in IT 7113 module 10

https://chrisluv.medium.com/defining-data-visualisation-daf71c22ec03


https://www.tableau.com/learn/articles/data-visualization


https://www.perceptualedge.com/blog/?p=2636

Notable Definitions
• Some notable definitions also share some
common features of the four key terms.
6
Essential read: Defining Data Visualisation
https://chrisluv.medium.com/defining-data-visualisation-daf71c22ec03
Tableau
https://www.tableau.com/l
earn/articles/data-
visualization
Data visualisation is the graphical representation of
information and data. By using visual elements like
charts, graphs and maps, data visualisation tools
provide an accessible way to see and understand
trends, outliers and patterns in data.
Andy Kirk, in his book
Data Visualisation
“The representation and presentation of data to
facilitate understanding.”
Stephen Few
https://www.perceptualed
ge.com/blog/?p=2636
Data visualization is a collection of methods that use
visual representations to explore, make sense of, and
communicate quantitative data.
Read more comments from users on this page

http://hint.fm/wind

Data, Visual, Visualization
•
Visual (graphic)
–
is related to vision (seeing through eyes) - one of the major human senses to interact with the world.
– meaning it can be seen by human eyes; or can be imagined (even though eyes are closed).
•
Visualization is the process of forming a visual image of things that can be seen through eyes (and/or
imagined in human mind).
• What can be visualized?
–
Visible reality: person, animal, building, mountain
– Hidden reality: earth core, blood vessel, universe
–
Invisible reality: wind (hint.fm/wind), air, heat, electron, sound, smell, magnetic fields
–
Abstract entity: activity, event, idea, hierarchy, process, relationship
•
How to visualize them?
–
These realities and entities can be described using data and information.
– Data are typically numerical values (but can also be qualitative) that describe its associated entity or activity.
– Data itself is abstract. The visualization process creates visible forms to represent the meaning of these abstract data.
– Utilizing a combination of the three elements: spatial substrate (space and area), graphical (visual) elements (shapes and
symbols), and graphical properties (visual variables/properties) like size, color, positions, etc. – see next a few slides
•
Types/features of visualization forms
–
2D vs. 3D objects
–
Static vs. motion visuals
–
Virtual (created in computers) vs. materialized (built/displayed in real world)
– Realistic (using realistic objects) vs. abstract (using abstract shapes)
•
The visualization process (and the result) may change the original form of things, or create new forms, for
better understanding and communication.
–
For example, using 2D squares to represent 50 states on a map; or using arrows for air flow.
7
Visualizing “visualization”
8
Perception:
I see
(or I can
imagine)
Invisible reality
Abstract entity
Visualized forms:
2D vs. 3D
Static vs. motion
Virtual vs. materialized
Realistic vs. abstract
Visible reality
Hidden reality
Visualized forms may be
modified from their original
forms or completely new
(e.g., for invisible or
abstract things).
Cognition:
I learn and
understand

http://wiki.gis.com/wiki/index.php/Visual_Variables


https://blogs.ifgi.de/digital-cartography/symbols/visual-variables/


https://www.interaction-design.org/literature/article/visual-mapping-the-elements-of-information-visualization


https://www.edocr.com/v/631d1wpb/jgzheng/SCOPeS

Representation
•
Representation is an encoding or visual mapping process that connects
visuals to data (meanings)
Visual mapping = data + visual
•
It directly defines how data is coded or mapped to the three elements
1.
Spatial substrate: The spatial substrate is the space in which we’re
going to create the visualization.
2.
Graphical (visual) elements:
–
Visual (or graphical) elements will appear in the spatial substrate. They
represent data items or entities.
–
Visual elements are the basic building blocks in a visualization (a chart or a
diagram).
3.
Graphical properties (visual variables/properties)
–
Visual property, or attribute, or variable, is the “decoration” applied to visual
elements to represent data values
•
http://wiki.gis.com/wiki/index.php/Visual_Variables
•
https://blogs.ifgi.de/digital-cartography/symbols/visual-variables/
–
A visual property is used to encode different values of a particular dimension of
data
9
The + here indicates some
kind of defined associations
(encoding or mapping)
between the data and visuals
[Reference] The Three Elements of Visual Mapping for Information Visualization
https://www.interaction-design.org/literature/article/visual-mapping-the-elements-
of-information-visualization
Size
Color
Orientation
Position
Texture
Shape
Bertin’s Original Visual Variables in his book “The
Semiology of Graphics” (Jacques Bertin, 1967)
Visual properties will be covered in IT 7113
module 2.
The six basic visual properties can be
remembered as “SCOPeS” - my term -
refer to the lecture notes “Visual Encoding
with SCOPeS Visual Variables/Properties
https://www.edocr.com/v/631d1wpb/jgzhen
g/SCOPeS
Presentation
• Presentation of data is not directly related to data
values, but it impacts the overall user experience of
the visual and affects perception and cognition as
well
• Common presentation perspectives
– Design choice, like color scheme, icon set, theme,
animation, etc.
– Annotation: extra help info, which may include the
design of titles, labels, legends, tool-tips, etc.
– Styling for attention shaping and reasoning, including
grouping, sorting, etc.
• From a software app perspective
– UI, composition, layout, position
– Interaction
10
More details about attention shaping and
grouping are in IT 7113 module 2

https://en.wikipedia.org/wiki/Perception


https://www.youtube.com/watch?v=GVkXbQOzKNs&t=233s

Purposes of Data Visualization
• Visualizing is basically a human physiological and psychological capability. It plays an important
role in human information behavior. Enhancing perception and cognition are the two
fundamental purposes and values of data visualization
• Perception
– Perception is the organization, identification, and interpretation of sensory information in order to
represent and understand the presented information, or the environment.
https://en.wikipedia.org/wiki/Perception
– The most basic purpose of data visualization is sensory enhancement to impact human perception.
– Enable fast perception (of patterns) based on instinct.
– Help to shape the attention and focus on key things.
• Cognition
–
Is the interpretation and comprehension of the perceived information and relate to long term experience
and knowledge for sense making.
– Ease the cognitive load of information processing and exploration (especially those with a space/position
factor)
– Recall or memorize data more effectively (long term memory)
– Extract/provoke additional (implicit) perspectives and meanings (related to knowledge and experience)
– Leads to improved explanation, communication, problem solving, decision making, etc.
11
Extended reading/watching
Andy’s Webinar
https://www.youtube.com/watch?
v=GVkXbQOzKNs&t=233s
More details about perception and
cognition in IT 7113 module 2

http://prezi.com/qvhyfup5z7yz/dashboard-design-making-reports-pop/


https://www.edocr.com/v/e6ql9njn/jgzheng/data-visual-foundation


https://www.interaction-design.org/literature/article/visual-mapping-the-elements-of-information-visualization


https://www.interaction-design.org/literature/article/the-properties-of-human-memory-and-their-importance-for-information-visualization


http://dl.acm.org/citation.cfm?id=1082104

Visualizing “Data Visualization”
Image from http://prezi.com/qvhyfup5z7yz/dashboard-design-making-reports-pop/
12
The cognitive visualization process in
human brain and elements of visual
mapping is covered with more details in
module 2
https://www.edocr.com/v/e6ql9njn/jgzhen
g/data-visual-foundation
Key readings
• Visual Mapping – The Elements of
Information Visualization:
https://www.interaction-
design.org/literature/article/visual-mapping-
the-elements-of-information-visualization
• The Properties of Human Memory and Their
Importance for Information Visualization:
https://www.interaction-
design.org/literature/article/the-properties-of-
human-memory-and-their-importance-for-
information-visualization
Plain (tabular) data
Visualized data
Figure “The Visualization Process” from: A survey, classification and analysis of perceptual
concepts and their application for the effective visualisation of complex information
http://dl.acm.org/citation.cfm?id=1082104
Practical Benefits of Data Visualization
• Data visualization helps with higher-level tasks or information
behaviors:
– Exhibitory: showing (presenting) for quick understanding
– Explanatory: analysis, insight generation, problem solving, decision support
– Exploratory: interactive information seeking, browsing, exploration, and
discovery
– Communicative: e.g., story telling (impression/persuasion)
• Note: data visualization are also used for artistic (beauty) expression
and appreciation, entertaining and for fun, which we will not cover in this
class.
• More specifically (see examples in the following slides)
– Direct perception of measurement magnitude (especially for abstract
measures) based on size, color, etc.
–
Identify patterns and trends
–
Identify structures and relationships, especially those hard to express in
words
– Quickly detect and focus on area of interest or area of difference
– Associate with familiar real-world context (e.g., locations and maps)
13
A picture is worth
1000 words (clicks)
Perception of Value Magnitude
• Value recognition directly based on visual
properties like color, size, position, etc.
14
Not everyone has a sharp sense
of comparing numbers (especially
a lot of numbers)
Values associated with
positions. Higher positions
means higher values.
Easier to perceive and
compare the values.
Identify Trends and Patterns
What's the difference between
these two cities? Which one is
Atlanta? In 10 seconds?
15
Monthly average temperature
Monthly average precipitation
The visualization adds a
shape (an arch) perception
that represents a change
pattern.

http://www.slate.com/blogs/the_slatest/2015/10/06/syrian_conflict_relationships_explained.html

Identify Structures/Relationships
• Who Is Fighting Whom
• Does June report to Joy?
Employee
Reports to
Jane
Jack
Jessie
Jane
Jason
Jane
John
Joy
Joseph
Joy
Joy
Jack
June
Jessie
16
http://www.slate.com/blogs/the_slatest/2015/10/
06/syrian_conflict_relationships_explained.html

http://finviz.com/map.ashx

Quickly Focus on Area of Interests
• Which stock performed different from others?
http://finviz.com/map.ashx
17
Associate with Familiar Visual Context
18
Text (non
visual)
Visual
Geo map is the
recognizable familiar
real world visual
context (geo map)

http://visualnomics.com/


https://www.greatschools.org/school-district-boundaries-map/


https://www.vox.com/2018/1/8/16822374/school-segregation-gerrymander-map


http://setosa.io/bus/

Data Visualization Usages
• Broadly used in almost all activities and industries
– Business reporting in many segments: retail, investment, manufacturing, logistics, etc.
– Public communication: media, journalism
– Public management like city planning, election
– Economics http://visualnomics.com
• Sample use cases (depending on the use case, we may need different tools with different
features)
– Presentation and communication
• Static presentations in meetings or conferences – PowerPoint
– Reporting
• Regular/seasonal reports for casual business users and manager – reports, slides
• Real-time or near real-time reporting - dashboard
•
Interactive reporting and exploration by power users – interactive reports or dashboard.
• Executive reporting and decision making - dashboard
– Analytical
• Used in the process of analysis, accompanying queries and calculations - Excel
• Advanced visual driven analysis, often used for research – Power BI/Tableau
– Monitoring: real-time operational monitoring (driving, manufacturing) - dashboard
– Public communication/journalism
• School redistricting https://www.greatschools.org/school-district-boundaries-map/
• Tell a story to the public https://www.vox.com/2018/1/8/16822374/school-segregation-gerrymander-map - web
– Demonstration/simulation: interactive demonstration for complex scenarios - http://setosa.io/bus/
19
A Bigger Impact
• Visual literacy
– The ability to evaluate the advantages and disadvantages of graphic
representations, to improve their shortcomings, to use them to
create and communicate insights, or to devise new ways of
exploring and representing data, information, or knowledge
– Enables the group of managers, technical professionals, and users
to effectively and efficiently communicate and understand on a
common ground.
• Data culture
– Data visualization helps with creating a data culture, especially in an
environment lack of analytical skills.
– It facilitates collaboration among different groups of people with
different professional focus, thus creating better working
environment.
– With modern visual tools, data visualization make data and analytics
more accessible to average people. This contributes to data literacy
and data democratization.
20
Related Terms and Fields
Data presentation
Information design
Information visualization, including infographic and illustration
Text visualization
Big data visualization
Computer graphics, reality visualization (VR, AR), scientific visualization
Data art
Business data visualization
Visual analytics
21
IT 7113 focus

https://www.toppr.com/guides/economics/presentation-of-data/textual-and-tabular-presentation-of-data/


https://www.toppr.com/guides/business-economics-cs/descriptive-statistics/diagrammatic-presentation-of-data/

Data Presentation
Data presentation is the method to summarize, organize, and communicate data
(raw or analysis results) using a variety of tools. Data can be presented in one of
the three forms: text, tables, and/or graphs. The selection of the method of
presentation depends on the type of data, method of analysis, and type of
information sought from the data.
22
Reference reading:
• https://www.toppr.com/guides/economics/presentation-of-data/textual-and-tabular-presentation-of-data/
• https://www.toppr.com/guides/business-economics-cs/descriptive-statistics/diagrammatic-presentation-of-data/
Textual
Narratives and articles, with
lengthier discussions.
Popular in news and story
modes.
This is generally
more aligned with
data visualization.
Structured
layout:
table, grid,
flow list,
cards
charts
maps
diagrams

https://en.wikipedia.org/wiki/Information_design

Information Design
•
Information design is the practice of presenting
information in a way that fosters an efficient and
effective understanding of the information.
– https://en.wikipedia.org/wiki/Information_design
• These include elements like layout, flow, use of text
style, bullets, spacing, etc.
•
It shares some similar data visualization design
practices, but it typically does not rely on graphics
heavily.
•
Information also include more types of content than
just data.
• Applicable fields
– Document design, presentation slides, user interface,
product design, web design, print media design like
books/magazines, and information
visualization/graphics, media imaging, map, etc.
23
Information
design
Information
visualization

https://en.wikipedia.org/wiki/Information_visualization


https://informationisbeautiful.net/


https://www.interaction-design.org/literature/topics/information-visualization


https://www.informationisbeautifulawards.com/showcase?type=awards

Information Visualization
•
Information visualization is the study of visual
representations of information or data to reinforce human
cognition. The data include both numerical and non-
numerical data, such as text and geographic information.
– A branch of information design that utilizes graphical
elements
– A very close field, and very often used as the synonym for,
or even include, data visualization
– Often in the form of illustrations, diagram, and infographics
– https://en.wikipedia.org/wiki/Information_visualization
• Examples: mall/subway map, more at
https://informationisbeautiful.net
• See more resource about information visualization
– https://www.interaction-
design.org/literature/topics/information-visualization
– https://www.informationisbeautifulawards.com/showcase?t
ype=awards
24
Information
design
Information
visualization
infographics

https://informationisbeautiful.net/


http://blogs.scientificamerican.com/sa-visual/2014/10/14/sa-recognized-for-great-infographics/


https://www.visualcapitalist.com/


http://blogs.scientificamerican.com/sa-visual/2014/10/14/sa-recognized-for-great-infographics/


http://blogs.scientificamerican.com/sa-visual/2014/10/14/sa-recognized-for-great-infographics/


https://visual.ly/m/design-portfolio/


http://www.dubberly.com/concept-maps/3x4grid.html

Illustration (of an Idea/Concept)
These can be considered as information
visualization but NOT data visualization.
25
More examples of information visualization can be found at
• https://informationisbeautiful.net
• http://dailyinfographic.com/
• https://www.visualcapitalist.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/
• http://www.dubberly.com/concept-maps/3x4grid.html

http://en.wikipedia.org/wiki/Information_graphics


https://visual.ly/blog/11-infographics-about-infographics/


https://www.business2community.com/digital-marketing/visual-marketing-pictures-worth-60000-words-01126256


https://www.interaction-design.org/literature/article/information-visualization-who-needs-it


https://www.visualcapitalist.com/visualizing-the-94-trillion-world-economy-in-one-chart/


https://www.visualcapitalist.com/visualized-world-leaders-in-positions-of-power/


https://www.easel.ly/blog/endangered-species-infographics/


https://www.visualcapitalist.com/


https://www.visualcapitalist.com/


https://visual.ly/m/design-portfolio/


https://informationisbeautiful.net/


http://www.visualisingdata.com/


http://courses.ischool.berkeley.edu/i247/s18/


https://www.visualcapitalist.com/

Infographics
•
Infographics is a specific type of information visualization that are usually
a mixture of texts, graphics, and data visual forms (charts, diagrams,
tables, maps, etc.) to quickly and vividly communicate complex
information (multiple variables or dimensions).
– http://en.wikipedia.org/wiki/Information_graphics
– https://visual.ly/blog/11-infographics-about-infographics/
– Often used in mass communication (e.g., journalism) and marketing
•
https://www.business2community.com/digital-marketing/visual-marketing-pictures-
worth-60000-words-01126256
•
https://www.interaction-design.org/literature/article/information-visualization-who-
needs-it
– Single block visualization (may be big)
•
https://www.visualcapitalist.com/visualizing-the-94-trillion-world-economy-in-one-chart/
•
https://www.visualcapitalist.com/visualized-world-leaders-in-positions-of-power/
– Composite infographics
•
https://www.easel.ly/blog/endangered-species-infographics/
• More examples:
– https://www.visualcapitalist.com/our-top-21-visualizations-of-2021/
– https://www.visualcapitalist.com
– https://visual.ly/m/design-portfolio/
– https://informationisbeautiful.net (not all but many are)
– http://www.visualisingdata.com (not all but many are)
– http://courses.ischool.berkeley.edu/i247/s18/ (not all but many are)
26
https://www.visualcapitalist.com

https://www.datarevelations.com/balancing-accu-ement-and-tone/

Data Visualization vs. Infographics
27
https://www.datarevelations.com/balancing-accu-ement-and-tone/
vs.

https://visage.co/throwdown-data-visualization-vs-infographics/


http://www.jackhagley.com/What-s-the-difference-between-an-Infographic-and-a-Data-Visualisation

Infographics vs. Data Visualization
More readings: infographics vs. data visualization
– https://visage.co/throwdown-data-visualization-vs-infographics/
– http://www.jackhagley.com/What-s-the-difference-between-an-Infographic-and-a-Data-Visualisation
28
Infographic
Data visualization
Creation
One time creation and use; mostly created
using graphic design tools. Often hand-
crafted.
Using data processing or analytical tools;
automatically populated from a data
source.
Usage
Intended for more casual use
(informational) for general people.
Presentation only.
Allows interactive exploration and supports
analytical needs and decision making.
Data
(binding)
Fixed data set or numbers.
Information often is more general and can
be more qualitative.
Highly quantitative with many measures
and metrics.
Visualizations are bound to a data source
and automatically populated. Data sources
can be dynamic.
Visual styles
Utilizes more free forms (non-standard) of
visual diagrams or illustrations (illustrational
diagrams); emphasizes creativity and
artistically expression to communicate or
impress casual viewers.
Uses more standard and conventional
visualizations that are already familiar to
the audience.

https://courses.cs.washington.edu/courses/cse512/19sp/lectures/CSE512-Text.pdf


https://en.wikipedia.org/wiki/Tag_cloud


https://www.betterevaluation.org/methods-approaches/methods/word-tree


https://textvis.lnu.se/


https://chartexpo.com/blog/text-visualization-examples


https://microvis.info/thesis/#foundation

Text Visualization
• Text visualization is related to text analytics, focusing on its visual
presentation part – text as data
– Articles, documents, web pages, logs, emails, messages, etc.
– https://courses.cs.washington.edu/courses/cse512/19sp/lectures/CS
E512-Text.pdf
• Common visual forms for text analytics
– Word/tag cloud, word tree
– More: https://textvis.lnu.se
•
It is also related to information presentation, which is about
enhancing of textual information presentation and understanding
through decoration of text, using similar visualization techniques
found in visualizing data.
– Examples: https://chartexpo.com/blog/text-visualization-examples
•
In some sense, text visualization can be related to typography
(individual letters and characters)
– https://microvis.info/thesis/#foundation
29

http://projector.tensorflow.org/


https://www.mastersindatascience.org/resources/10-cool-big-data-visualizations/


https://jeffjonas.typepad.com/jeff_jonas/2016/02/data-visualization-outing-hype.html


https://pudding.cool/2018/10/city_3d/


https://pudding.cool/2019/07/book-covers/

Big Data Visualization
• Big data visualization usually refers to a visualization with a large number of
data points (items and attributes) on a large space.
– The goal is to see patterns and relationships beyond a few items or aggregated metrics
– Using more contemporary visualization techniques including real-time changes,
animations, rich interactions, etc.
– Using more illustrative graphics and more artistic visual representation of the data.
• Examples:
– http://projector.tensorflow.org
– https://www.mastersindatascience.org/resources/10-cool-big-data-visualizations/
•
Is big data visualization a hype?
– “Big data visualization is generally not helping humans make novel discoveries.”
https://jeffjonas.typepad.com/jeff_jonas/2016/02/data-visualization-outing-hype.html
• What’s the purpose of big data visualization? And what’s the effective way to
use them?
– https://pudding.cool/2018/10/city_3d/
– https://pudding.cool/2019/07/book-covers/
30

https://ncase.me/polygons/


https://en.wikipedia.org/wiki/Scientific_visualization


http://acko.net/blog/how-to-fold-a-julia-fractal/


https://en.wikipedia.org/wiki/Fractal


https://mathigon.org/world/Fractals


https://ncase.me/polygons/

Computer Graphics and Scientific Visualization
•
Computer graphics (CG) is computer generated graphics and image models
– CG do not feature the use of business or transactional data that are generated from
human or organizational activities.
– Commonly based on computing logic and algorithms.
– Usually more computing intensive.
•
Applications
– Computer image
–
3D model, virtual reality
–
Science (scientific visualization)
– Games and movies
–
Simulation - https://ncase.me/polygons/
•
Physical science visualization
–
“Primarily concerned with the visualization of complex three-dimensional phenomena
(architectural, meteorological, medical, biological, etc.), where the emphasis is on realistic
renderings of volumes, surfaces, illumination sources, and so forth.”
–
Visualization (simulation) of complex reality (entities or events, such as universe, sun,
explosion, atom, climate, etc.)
–
https://en.wikipedia.org/wiki/Scientific_visualization
• Mathematical model/algorithm visualization/simulation – the visualization created
based on math calculations and models
–
http://acko.net/blog/how-to-fold-a-julia-fractal/
–
https://en.wikipedia.org/wiki/Fractal
–
https://mathigon.org/world/Fractals
–
https://ncase.me/polygons/
31

https://www.perceptualedge.com/blog/?p=1245


http://hint.fm/projects/flickr/


https://nightingaledvs.com/tag/data-art/


https://www.data-to-art.com/


https://en.wikipedia.org/wiki/Music_visualization


https://chrisluv.medium.com/defining-data-visualisation-daf71c22ec03

• Data Art (or Information Art) is a field where artists express themselves
artistically using data as a medium (usually using computers).
•
In data art, visualizations of data seek primarily to entertain or produce an
aesthetic experience. It is art that is based on data.
– https://www.perceptualedge.com/blog/?p=1245
• Features
– The input raw material is still data, but the purpose is not to understand or comprehension
– Often using algorithm (simple or complex) to brush up data (visualize) for self-expression
or aesthetics expression
– The understanding of the product is largely subjective and leave multiple ways of
interpretation
• Examples
– http://hint.fm/projects/flickr/
– https://nightingaledvs.com/tag/data-art/
– https://www.data-to-art.com
– Music visualization
https://en.wikipedia.org/wiki/Music_visualization
• Note: artistic data visualization != data art
https://chrisluv.medium.com/defining-data-
visualisation-daf71c22ec03
Data Art
32
Business data
visualization

https://www.ibcs.com/standards

Business Data/Information Visualization
•
Business data visualization is the data visualization mainly related to business data,
and it is used for business activities and purposes.
•
Business is a general term to describe activities, events, and operations of an entity
–
Business includes many activities directly associated with human, like commerce, public service, education, sports, charity,
entertainment, etc.
–
An entity could be an individual, organization, company, government, etc.
– Or even some natural phenomenon and events that impact human, such as ecosystem, weather, universe, animal, etc. (to
some extent)
–
Business data/information records various aspects of these activities and events.
• Main purposes are data exploration, analysis, decision support, monitoring, and communication that is related
to business performance.
• Main features of business data
–
Abstract: this data mainly describes an activity, pattern, trend, etc.; it does not directly define or create (simulate) a real-
world object or phenomenon as close as possible.
– Mostly quantitative
– Often structured or semi-structured, repeated
– Can be aggregated in multi-dimensions
–
Directly comprehendible by skilled humans (in a particular “business”)
• Main features of business data visualization
–
It is part of a BI or analytics process and system, especially in self-service systems
– Using simple, standard, and abstract images (symbol/chart/diagram/map)
– Highly reused and commonly accepted visualization forms – following standard practices https://www.ibcs.com/standards
– Utilizes data binding techniques to generate visualizations in an automated way (using specialized data visualization
software or as part of an analytics software application)
33
IT 7113
focus

https://myit-2019.itdashboard.gov/


https://www.geckoboard.com/learn/dashboard-examples/


https://www.productchart.com/smartphones/


https://finviz.com/map.ashx


https://www.census.gov/dataviz/


https://www.google.com/publicdata/directory


https://www.nytimes.com/interactive/2018/11/06/us/elections/results-dashboard-live.html

Business Data Visualizations Examples
• Operational reports: communication of results in all kinds of reports
(periodical/seasonal or real time) and presentations (e.g. PowerPoint)
– https://myit-2019.itdashboard.gov
• Performance dashboards
– https://www.geckoboard.com/learn/dashboard-examples/
• Visual data exploration and seeking
– https://www.productchart.com/smartphones/
– https://finviz.com/map.ashx
– https://www.census.gov/dataviz/
• Visual analytics
– https://www.google.com/publicdata/directory
• Real-time monitoring (public events, administrative, or operational)
– https://www.nytimes.com/interactive/2018/11/06/us/elections/results-dashboard-live.html
• Presentation of results in statistical analysis, data mining or other advanced
analytics.
34

http://hint.fm/wind/


http://hint.fm/


http://classes.dma.ucla.edu/Spring13/161/projects/students/david/project-5/html/?/image-gallery/


https://weather.com/weather/radar/interactive/l/USGA0028:1:US


https://www.theguardian.com/us-news/ng-interactive/2017/dec/20/bussed-out-america-moves-homeless-people-country-study


http://hci.usask.ca/uploads/173-pap0297-bateman.pdf


https://ritholtz.com/2012/02/the-beatles-song-keys/

[Not] Business Data Visuals
These examples are not really considered to be business data
visualization, but still considered as general data visualizations –
not the focus of this class
• General data visualization (not typical business data related
to business activities)
– http://hint.fm/wind/
– http://hint.fm
– http://classes.dma.ucla.edu/Spring13/161/projects/students/david
/project-5/html/?/image-gallery/
– https://weather.com/weather/radar/interactive/l/USGA0028:1:US
• Artistic data visualization: with many artistic decorations –
commonly used in journalism style report for public
communication
– https://www.theguardian.com/us-news/ng-
interactive/2017/dec/20/bussed-out-america-moves-homeless-
people-country-study
– Visual embellishment http://hci.usask.ca/uploads/173-pap0297-
bateman.pdf
• Not even data visualizations
–
Infographics
– Mathematical visuals
– Scientific visualization
35
https://ritholtz.com/2012/02/the-beatles-song-keys/

https://en.wikipedia.org/wiki/Visual_analytics


https://www.tradingview.com/chart/


https://www.sisense.com/blog/data-visualization-and-visual-analytics-seeing-the-world-of-data/

Visual Analytics
• Visual analytics is "the science of analytical reasoning
facilitated by interactive visual interfaces.“
– https://en.wikipedia.org/wiki/Visual_analytics
• Visual analytics is beyond just visualizing data
– Interactive exploratory and analytical processes
– The major purpose is to discover patterns and relationships
– Visual analytics does not just visualize raw fact data or a few
performance measures; it involves complicated metrics and statistical
measures.
• Example: https://www.tradingview.com/chart/
• Use visual analytics tools or analytical dashboard – see visual
forms in the next section.
36
Extended reading: https://www.sisense.com/blog/data-
visualization-and-visual-analytics-seeing-the-world-of-data/
Comparison of Related Visualization Fields
Content
Visual Forms/Tools
Purpose/Usage
Business data
visualization
Quantitative data related to
business activities; metrics, key
performance indicators (KPIs)
Standard and common types
of charts, diagrams, maps,
dashboards
Data exploration, analysis, decision
making
General data
visualization
General quantitative data, such
as natural phenomenon
Also often using creative and
stylish charts, diagrams,
maps; artistically combining
different forms and elements.
Data exploration, cognition, and
mass communication
Information
visualization
All kinds of information,
quantitative and qualitative
Infographics,
illustrational diagrams
Information seeking, artistic
illustration, casual communication,
story telling
Illustration
Processes, structures concepts,
ideas
Diagrams, images, graphics
Making the content more vivid and
engaging, easier to understand the
complexity.
Scientific
visualization/simul
ation
Real world object or
phenomenon,
mathematical functions and
formulas, calculated data based
on formulas or rules
Computer generated graphics,
3D virtual reality, animated
diagram
Recreate or simulate the real-world
object or phenomenon, or visualize
an algorithm effect. Demonstrate
the effect of scenarios under
certain rules.
Visual analytics
Quantitative data; statistical and
other metrics
Charts, diagrams, maps,
dashboards
Analysis and decision support
37
Data Visualization in BI/Analytics
Basic visual properties and visual forms/styles used in BI and
analytics applications
38
IT 7113 focus

https://www.forbes.com/sites/louiscolumbus/2018/06/08/the-state-of-business-intelligence-2018/#b2fca2878289

Data Visualization in BI/Analytics
• Data visualization is an important part of data exploration and
decision making. Given the power of visualization, it is only
natural to apply the rich communication techniques in the field of
BI and analytics.
• Visualization has been considered as a separate field from BI in
the early days (prior to 2010), but it quickly brought the traditional
business intelligence to life
– As organizations seek to empower non‐technical users to make
data‐driven decisions, they must consider the powers of data
visualization in delivering digestible insights.
– 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.
Dashboards, reporting, end-user self-
service, and advanced visualization
top the most important technologies
and initiatives strategic to BI in 2018.
https://www.forbes.com/sites/louiscolumb
us/2018/06/08/the-state-of-business-
intelligence-2018/#b2fca2878289

https://www.researchgate.net/publication/321804138_Data_Visualization_for_Business_Intelligence

Basic Visual Forms/Styles used in BI/Analytics
40
Form/Style
Description
Typical Types and Examples
Embedded visual
It is embedded in, or directly on top of,
texts and other forms of data
presentation (table, graphic, etc.).
 Conditional formatting (visual
cues)

Inline chart (Sparkline)
Block visual
It is displayed as an independent visual
unit and occupies a larger space. It is
often a part of another product such as
report or dashboard, appearing together
with other content. But sometimes it
can become a standalone visual with
many data points or enough
complexity.
 Chart
 Data diagram
 Map (smaller)
 Table/card with embedded visuals
Visual app
It is a standalone application. It may
consist of a combination of different
types of visuals and other content
types. It supports more complex
interactions, and most interactions are
within the application.
 Dashboard
 Visual report/presentation

Infographic (large)
 Visual analysis tool (or an
analytical dashboard)
 Full map (full screen)

(Data-driven) Story
Refer to Zheng (2017) Book Chapter Data Visualization in Business Intelligence (PDF downloadable on the
site): https://www.researchgate.net/publication/321804138_Data_Visualization_for_Business_Intelligence

http://www.masters.com/en_US/scores/


http://en.wikipedia.org/wiki/Tag_cloud

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
41

https://chartio.com/blog/new-chart-type-sparklines/


http://omnipotent.net/jquery.sparkline/


http://www.klipfolio.com/blog/table-component-overview


https://trumpexcel.com/sparklines/

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.
– https://chartio.com/blog/new-chart-type-sparklines/
• Examples
– http://omnipotent.net/jquery.sparkline/
– http://www.klipfolio.com/blog/table-component-overview
– https://trumpexcel.com/sparklines/
42
Sparkline

http://en.wikipedia.org/wiki/Chart


https://cdn-get.whotrades.com/u8/photoDFC5/20727087415-0/original.jpeg


https://fool.whotrades.com/blog/43151739255

Chart
• A chart is a graphical representation of data
– 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
– These two terms are very similar; they are often used together or
interchangeably in daily life.
– Chart is more abstractly presented and focuses more on quantitative
values.
– Diagrams also cover a lot of qualitative information like process,
concepts, ideas, structures, etc.; they also intergrade more real-
world contexts like maps.
– Diagram is sometimes considered to include chart.
43
We will cover charts and their designs in IT 7113 (three modules).
https://fool.whotrades.c
om/blog/43151739255

http://datavizproject.com/


http://www.datavizcatalogue.com/


https://www.data-to-viz.com/


http://chartmaker.visualisingdata.com/


https://extremepresentation.com/design/7-charts/


https://www.perceptualedge.com/blog/?p=2080


https://excelcharts.com/classification-chart-types/


https://www.dataatworkbook.com/


https://www.juiceanalytics.com/chartchooser


https://policyviz.com/2014/09/09/graphic-continuum/


https://www.ft.com/vocabulary


http://experception.net/

Summary of Chart Categorizations
44
• Simple – simply by purpose or data type without much explanation
• Detailed and interactive
Ferdio
http://datavizproject.com
An interactive resource with a lot of examples. Included diagrams
and maps. Categorization by function and a unique category by data
inputs. It provides details for each chart. I use it for reference a lot.
Data catalog
http://www.datavizcatalogue.com
An interactive catalog with very detailed description for each chart.
Added many smaller and specific categories. I use it for reference a
lot.
From Data to Viz
https://www.data-to-viz.com
A classification of chart types based on input data format. It comes in
the form of a decision tree. It also provide details for each chart.
Chart make directory
http://chartmaker.visualisingdata.com
This is a community effort to catalog charts by function and show
solutions for each major visualization tool (with links to external
resources).
Abela's version
https://extremepresentation.com/desig
n/7-charts/
This is the most widely referred version with a simple visual itself.
But it was criticized by Stephen Few with a lot of details
https://www.perceptualedge.com/blog/?p=2080
Camões’s version
https://excelcharts.com/classification-
chart-types/
Influenced by Abela’s version, added evolution (like trend) and
profiling. The blog is very brief. He has an updated version with more
details in his book “data at work” https://www.dataatworkbook.com.
Juice Analytics
https://www.juiceanalytics.com/chartc
hooser
Provided as an interactive online chooser with templates for Excel
and PowerPoint. Categorized similarly but added an “trend”
category.
Schwabish’s Graphic
Continuum
https://policyviz.com/2014/09/09/graphic-
continuum/
A poster style visual presentation covering nearly 90 charts.
Financial Times Visual
Vocabulary
https://www.ft.com/vocabulary
Financial Times Visual Vocabulary is based on the Graphic
Continuum.
Fraconeri’s version
http://experception.net
A quick reference in PDF that considers data types and inputs,
rather than purposes.
Choosing charts will be
covered in IT 7113 module 3.

http://en.wikipedia.org/wiki/Diagram


https://en.wikipedia.org/wiki/Illustration


http://en.wikipedia.org/wiki/Flowchart


https://flowingdata.com/charttype/network-graph/


http://en.wikipedia.org/wiki/Tree_structure


https://datavizcatalogue.com/methods/timeline.html


http://en.wikipedia.org/wiki/Data_structure_diagram


https://datavizproject.com/family/diagram/


https://en.wikipedia.org/wiki/Sankey_diagram


https://visualime.com/view-behavior-flow-specific-page-google-analytics/

Diagram
•
Illustrational diagrams
– Mainly to visualize quantitative as well as qualitative data to illustrate their
features, relationships, sequences, etc.
–
Also includes position as a feature in a logical (virtual) structure or
process, such as network diagram, process diagram, hierarchy diagram,
etc.
–
http://en.wikipedia.org/wiki/Diagram
–
https://en.wikipedia.org/wiki/Illustration
•
Common examples used in business information visualization
–
Flow chart: http://en.wikipedia.org/wiki/Flowchart
– Network diagram/graph: https://flowingdata.com/charttype/network-graph/
–
Tree diagram: http://en.wikipedia.org/wiki/Tree_structure
–
Timeline: https://datavizcatalogue.com/methods/timeline.html
–
Structure diagram: http://en.wikipedia.org/wiki/Data_structure_diagram
–
Sitemap in web design
– Organization structure
– Workflow
–
Process
–
System architecture
– Road map
–
Strategy map
– Curriculum map
– Concept map
– More: https://datavizproject.com/family/diagram/
•
Diagrams can be data/information driven and incorporate
quantitative data
–
Sankey diagram
https://en.wikipedia.org/wiki/Sankey_diagram
45
https://visualime.com/vie
w-behavior-flow-specific-
page-google-analytics/

http://searchbusinessanalytics.techtarget.com/definition/location-intelligence-LI


https://www.tableau.com/learn/whitepapers/government-mapping


https://www.forbes.com/forbesinsights/pitney_bowes_power_of_place/


https://www.esri.com/news/arcuser/1012/files/morethanamap.pdf

Maps (Location-based Visualizations)
•
Location intelligence (LI) is a business intelligence (BI) tool capability that relates geographic
contexts (usually as a dimension) to business data.
– http://searchbusinessanalytics.techtarget.com/definition/location-intelligence-LI
•
Location based visualization (map) is the base for location intelligence and plays an important
role in business intelligence.
– Within all of the leading front-end BI tools, interactive maps are replacing or augmenting standard table
and chart views of geographic data.
–
involves layering multiple data sets spatially, for easy reference on a map
– Maps provide context … Quickly associate data with familiar position/location – added familiarity
increase comprehension. (Tableau “The Power of Where”
https://www.tableau.com/learn/whitepapers/government-mapping)
– Maps are widely recognized and understood—even by nontechnical professionals—which helps make
the data represented more accessible and understood. (Forbes “The Power of Place”
https://www.forbes.com/forbesinsights/pitney_bowes_power_of_place/)
•
Like business intelligence, location intelligence supports analysis and decision making. But for
the past 20 years, these two data-centric disciplines have forged independent but parallel
paths. Only now are they beginning to converge. The explosion of mobile and IoT devices
facilitates the integration of business and location intelligence.
– The first step toward converging location and business intelligence is plotting business metrics on a map.
– The next step is the interactive process of location driven visual analytics, utilizing more sophisticated
mapping layers and data presentation, even on three-dimensional surface, with the help of VR/AR
technologies.
– https://www.esri.com/news/arcuser/1012/files/morethanamap.pdf

http://luminocity3d.org/WorldCity/


https://maps.google.com/gallery/


https://en.wikipedia.org/wiki/Choropleth_map


https://www.gasbuddy.com/GasPriceMap


https://www.edocr.com/v/npapy5k4/jgzheng/mapping-location-based-visualization


http://www.citylab.com/politics/2014/04/2-very-different-migrations-driving-growth-us-cities/8873/


http://www.270towin.com/

Major Map Types
• Geospatial (geo) maps
– Visualize geo location related data directly on real world
maps
– Data represented as points, areas, paths
– http://luminocity3d.org/WorldCity/
– https://maps.google.com/gallery/
• Proportional Symbol Map
– Proportional symbol maps, or bubble maps, scale the size
of simple symbols (usually a circle/bubble) proportionally
to the data value associated with that location.
• Choropleth Map (Area Filled Map)
– Data is represented using polygons corresponding to
defined geo regions
– Can only use color or texture to visualize data.
– https://en.wikipedia.org/wiki/Choropleth_map
– The layer is divided into different regions, and data will be
mapped to the regions as units
– Common types of regions include pollical areas like
country, state, county, or other defined by businesses like
postal (https://www.gasbuddy.com/GasPriceMap), phone
code, school district, or marketing/sales area.
– Regions generally correspond to geo locations, but they
may be less detailed and accurate.
Maps are covered in IT 7113 https://www.edocr.com/v/npapy5k4/jgzheng/mapping-location-based-visualization
Classic bubble map. Use size (number of people) and color (in-flow or out-
flow) to code two variables. http://www.citylab.com/politics/2014/04/2-very-
different-migrations-driving-growth-us-cities/8873/
http://www.270towin.com

http://luminocity3d.org/WorldCity/


https://maps.google.com/gallery/


https://googletrends.github.io/search-election-election-night/


https://fivethirtyeight.com/features/where-your-state-gets-its-money/


http://fatalities.safer63and881.com/#highway


https://www.facilityquest.com/occupancy-utilization-studies/


https://www.edocr.com/v/npapy5k4/jgzheng/data-maps

Major Map Types
• Geospatial (geo) maps
– Visualize geo location related data directly on real world
maps
– Data represented as points, areas, paths
– http://luminocity3d.org/WorldCity/
– https://maps.google.com/gallery/
• Abstract illustrational geo map (geo chart)
– These are conceptually related to geo location but
presented in an abstract way – an illustration, rather
than accurate geo locations.
– Geo chart: https://googletrends.github.io/search-
election-election-night/
– Sometimes they can even go symbolic like tile grid map:
https://fivethirtyeight.com/features/where-your-state-
gets-its-money/
– Road/path map:
http://fatalities.safer63and881.com/#highway
• Contextual map
– Any data relevant to the positioning in a particular
context or space, e.g., building, campus, mall, stadium,
a just a space (like a hitting area) etc.
– https://www.facilityquest.com/occupancy-utilization-
studies/
Maps are covered in IT 7113 https://www.edocr.com/v/npapy5k4/jgzheng/data-maps

http://www.bidashboard.org/benefits.html


https://www.edocr.com/v/oekl31vr/jgzheng/Dashboard


http://www.perceptualedge.com/articles/ie/dashboard_confusion.pdf


https://www.fairfaxcounty.gov/demographics/fairfax-county-general-overview

Dashboard
• Elements of a dashboard
– Data/information: the most important element
– Visual: data visuals (charts, etc.) provide a high level at-a-glance view
– User interface
•
a clean UI that unifies all elements to work together as a whole
•
supporting interactions as needed
•
The Value of Dashboard
– Provides a one-place presentation of critical information, so users can quickly understand data and
respond quickly at one place.
• Saves time over running multiple reports.
– Allows decision makers to see a variety of data that affects their divisions or departments
• This allows decision makers to focus only on the items over which they have control
• The dashboard is generally customized for each user
– Allows all users to understand the analytics. For non-technical users, dashboards allow them to
participate and understand the analytics process by compiling data and visualizing trends and
occurrences.
– More: http://www.bidashboard.org/benefits.html
49
The two dashboard modules in IT 7113 provide more details:
https://www.edocr.com/v/oekl31vr/jgzheng/Dashboard
Dashboard = data/information + visual + UI
A dashboard is a visual-oriented display of the most
important data and information needed to achieve defined
goals and objectives; consolidated and arranged on a
single screen so the information can be viewed at a glance.
Adapted from: Dashboard Confusion, Stephen Few,
http://www.perceptualedge.com/articles/ie/dashboard_confusion.pdf
https://www.fairfaxcounty.gov/demographics/fairf
ax-county-general-overview

https://datareportal.com/essential-facebook-stats


https://www.cityhealthdashboard.com/ga/atlanta/city-overview


https://www.g2.com/categories/data-visualization?segment=all


http://www.crazybikes.com/mrc/CRAZYBIKES.R00090s

Dashboard vs. Report
•
Reports
–
A report is the presentation of detailed data arranged in defined layouts and formats
–
Based on simple and direct queries: they usually involve simple analysis and transformation of data (sorting, calculating,
filtering, filtering, grouping, formatting, etc.)
•
Traditional reports contain detailed data in a tabular format and typically display numbers and text only.
–
It is geared towards people who need data rather than a direct understanding or interpretation of data.
–
Its purpose is mainly for printing (with styling) or exporting (raw data).
• Modern reports can be interactive and visual, but the focus is still on detailed data. Sometimes the distinction
is a bit blurred with dashboards in some practical cases.
–
Visual intensive report: https://datareportal.com/essential-facebook-stats
–
A report style “dashboard” (or more like a visual intensive interactive report):
https://www.cityhealthdashboard.com/ga/atlanta/city-overview
– Magic Quadrant report vs. https://www.g2.com/categories/data-visualization?segment=all
– Dashboard or report? http://www.crazybikes.com/mrc/CRAZYBIKES.R00090s
50

https://finviz.com/bubbles.ashx


https://finviz.com/map.ashx


https://www.productchart.com/


https://www.google.com/publicdata/directory


https://www.gapminder.org/tools/#$chart-type=bubbles


https://ourworldindata.org/explorers/global-food


https://ourworldindata.org/explorers/coronavirus-data-explorer


https://www.tradingview.com/chart/


https://stockcharts.com/h-sc/ui?s=XOM


https://d5t6zpljmdkvz.cloudfront.net/


https://www.tradingview.com/chart/

Visual Analysis/Exploration Tool
•
A visual analysis/exploration tool is similar to a dashboard in that it uses visualizations intensively to drive data
exploration or analysis (visual analytics).
–
Some consider it a kind of dashboard; some consider it a bit different
•
Key characteristics of a visual analysis tool:
–
The visualization is usually a single (or very few) component (a chart or a map) that occupies a big portion of the screen as
the main UI component, with a large number of data points visualized.
–
It is highly interactive and usually provides abundant settings and configurations (for adjusting factors and parameters)
including filtering or sorting options. In fact, the number of setting combinations can be quite big.
–
The visualization may be more complex with multiple visual layers
–
It is not to visual key metrics, but to visualize patterns, trends, and other complex relationships among data.
–
It fits on one screen, but there may be scroll bars and zooming options.
–
It is primarily used for intensive data exploration or analysis, used by data analysts and researchers.
•
Examples
–
Exploration
•
https://finviz.com/bubbles.ashx
•
https://finviz.com/map.ashx
•
https://www.productchart.com
• Google public data explorer
https://www.google.com/publicdata/directory
•
https://www.gapminder.org/tools/#$chart-type=bubbles
•
https://ourworldindata.org/explorers/global-food
•
https://ourworldindata.org/explorers/coronavirus-data-explorer
– More analysis intensive
•
https://www.tradingview.com/chart/
•
https://stockcharts.com/h-sc/ui?s=XOM
– Map based:
•
https://d5t6zpljmdkvz.cloudfront.net/
•
http://luminocity3d.org/WorldCity
51
https://www.tradingview.com/chart/

https://storymaps.arcgis.com/stories/f74a8fbad837435b8e901cc9c04aa345


https://public.tableau.com/profile/natcen.social.research#!/vizhome/WhatwillBrexitmeantotheUK/Home


https://projects.fivethirtyeight.com/2020-swing-states/


https://ourworldindata.org/energy-offshoring

Story
• Stories are predefined and scripted interaction and
interpretation of data visualizations
– Or, the data and visualizations drive the story
– By allowing users to interact with data presented in a clearly-
visual manner, a data-intensive ‘story’ becomes visible.
• Some examples:
– https://storymaps.arcgis.com/stories/f74a8fbad837435b8e901
cc9c04aa345
– https://public.tableau.com/profile/natcen.social.research#!/viz
home/WhatwillBrexitmeantotheUK/Home
– https://projects.fivethirtyeight.com/2020-swing-states/
– https://ourworldindata.org/energy-offshoring
We do not cover story in depth in IT 7113, but it can be a very good research topic for class project.

http://www.dataversity.net/fact-fiction-smart-data-visualization-tells-tale/


https://www.edocr.com/v/l0pp3ral/jgzheng/visual-interactivity


https://www.slideshare.net/tillnagel/nagel-unfolding-thecityworkshops

Interactivity
•
Interactivity is the functionality provided by the (visualization) system/application to let users interact with the
visualization or the system/application through a user interface.
–
So, the visualization itself becomes dynamic based on user actions, providing different views of data.
–
Interactivity is an important aspect of data exploration and analysis, as both are interactive processes.
–
Visual interactivity focuses on the interactions in using various forms of data visualizations (charts, maps, dashboards, etc.)
–
Interactivity is also essential in visual analytics where discoveries are driven by intensive interactions.
• Why interactive?
–
Enable multiple perspectives
• Static visuals can offer only pre-composed “views” of data, so multiple static views are needed to present a variety of perspectives
on the same information. A fixed image is ideal when alternate views are neither needed nor desired, and required when
publishing to a static medium, such as print. - Quotes from chapter 1 of the book “Interactive Data Visualization for the Web” by
Scott Murray.
– Reduce complexity
•
The number of views can grow significantly in many cases because of the multi-dimensionality of the data. Presenting all of them
is impossible. Even presenting multiple of them maybe cluttered and crowded.
•
Interactivity enables a more prioritized and focused view in a limited space.
–
Ease cognitive load
•
The number of items and data presented at one time may be overwhelming for a user; interaction features can help user focus.
–
Enables customization and exploration
• Dynamic, interactive visualizations can empower people to explore the data for themselves.
–
Encourage engagement with the data
• With animated transitions and well-crafted interfaces, some visualizations can make exploring data feel more like playing a game
or telling a story. Interactive visualization can be a great medium for engaging an audience who might not otherwise care about
the topic or data at hand.
• Make visualizations smart or tell a story: http://www.dataversity.net/fact-fiction-smart-data-visualization-tells-tale/
53
IT 7113 module 10 covers more in depth on this topic, explaining
common types and features of interactivity in data visualization:
https://www.edocr.com/v/l0pp3ral/jgzheng/visual-interactivity
Image from
https://www.slideshare.net/tillnagel/
nagel-unfolding-thecityworkshops
Developing Data Visualizations
The design/development of data visualizations involves
Processes
Principles
Best practices
Tools
IT’s role in business data visualization
54

https://digitalimpact.io/getting-started-a-3-step-approach-to-data-visualization/


https://www.elsevier.com/connect/a-5-step-guide-to-data-visualization


https://depictdatastudio.com/data-visualization-design-process-step-by-step-guide-for-beginners/


https://www.youtube.com/watch?v=GVkXbQOzKNs&t=754s


https://www.interaction-design.org/literature/article/how-to-design-an-information-visualization

Data Visualization Design Process
• A design process involves a defined set of design considerations and tasks
• Why do we need a process?
– A repeatable and defined design process embodies maturity in design capability and
experience
• greatly facilitate the design efficiency and effectiveness
•
reduce the randomness and puts tasks in order
• serve as a guide and a checklist to plan and manage the whole project
•
The following is a basic simple process for the most often scenario: we need
to present all data in just one chart of a common type. This class will focus on
this kind of scenario.
1.
Requirement analysis: set project goals and contexts
2.
Choose one basic chart type (general or industry specific) based on a number of factors
(mainly purposes and data features)
3.
Representation design: determining visual data coding, involving visual mapping and
visual properties (SCOPeS)
4.
Presentation design: apply perceptual and attention shaping best practices (for example,
pre-attentive processing and Gestalt principles) to make charts more effective and
efficient
55
There are other ways to define the designing process or factors. For example:
• A 3-Step Approach To Data Visualization https://digitalimpact.io/getting-started-a-3-step-approach-to-data-visualization/
• A 5-step guide to data visualization https://www.elsevier.com/connect/a-5-step-guide-to-data-visualization
• The Data Visualization Design Process: A Step-by-Step Guide for Beginners https://depictdatastudio.com/data-visualization-design-
process-step-by-step-guide-for-beginners/
• Andy Kirk’s 4 stages: https://www.youtube.com/watch?v=GVkXbQOzKNs&t=754s or Andy Kirk’s book “Data at Work” Chapter 2
• Design process for information visualization https://www.interaction-design.org/literature/article/how-to-design-an-information-visualization
We will cover more about
design process in IT 7113
module 4.

https://www.ibcs.com/standards/

Clarity
The chart delivers the message and makes
the point clearly.
Accuracy
Avoid data visual distortion and
disinformation.
Simplicity
Perceptually easy to locate and identify key
data and other information.
Elegance
Visual quality to attract audience and sustain
that sentiment and interest – Andy Kirk.
Basic Design Principles and Guidelines
• The CASE principles
• Also follow conventions, design patterns, and standards.
– Standards and conventions are great to promote consistency and perception alignment.
– For example, IBCS https://www.ibcs.com/standards/
56
We will cover principles in IT 7113 module 5.

https://www.edocr.com/v/9oqqrzoo/jgzheng/designing-dashboards

Dashboard Design Principles
In addition to general data visualization design principles, dashboards share many
principles and practices of general UI design (on usability):
1.
Meeting the goals and objectives (focus on data and insights)
– Focus on data, instead of visual – “Dashboards are not an appropriate venue for artistic
impression.” - Stephen Few
– All visuals and data needs to be relevant and directly support the objectives of the
dashboard
2.
Clarity and effectiveness
– Effective visuals that clearly reveal the insight and deliver the message
– Artistic expression in Data Visualization: use more memorable, less abstract, real world
iconic representations
3.
Simplicity and efficiency
– Simple and clear: use the simple design to meet the objectives and deliver messages
– Easy to understand, explore, and interact
4.
Consistency
– Design as a whole: dashboard level design beyond single chart
– Be consistent for the complete application, and consistent with the other organization
applications and cultures. multiple charts, pages
– Follow conventions, norms, and standards
57
We will cover dashboard design principles in IT 7113 module 9
https://www.edocr.com/v/9oqqrzoo/jgzheng/designing-dashboards

https://www.ibcs.com/standards/


https://www.eea.europa.eu/data-and-maps/daviz/learn-more/chart-dos-and-donts


https://xdgov.github.io/data-design-standards/

Standards, Conventions, and Guidelines
• Standards and conventions are great to promote consistency and
perception alignment.
• Two theories and design practices are widely referenced (next two
slides)
– Pre-attentive processing
– Gestalt principles
• Are there any standards in an industry or a particular sector?
–
It is difficult and to make and require standards in design. They are more
like guidelines.
– For example, IBCS https://www.ibcs.com/standards/
•
If not, it’s always good to establish organizational guidelines, and
follows conventions and best practices
– For example, European Environment Agency (eea.europa.eu) has a set of
usability guidelines for improving visualisations
https://www.eea.europa.eu/data-and-maps/daviz/learn-more/chart-dos-and-
donts
– https://xdgov.github.io/data-design-standards/
58

https://www.researchgate.net/publication/245623481


https://www.csc2.ncsu.edu/faculty/healey/PP/index.html


http://kenhirakawa.com/significance-of-contrast/


https://www.coursera.org/lecture/dataviz-design/strategic-use-of-contrast-sDV6C


https://www.researchgate.net/publication/245623481


https://www.csc2.ncsu.edu/faculty/healey/PP/index.html

Pre-Attentive Processing
•
Any visual processing of that item prior to the act of selection can be called “preattentive”.
– Wolfe et. al. 2010 https://www.researchgate.net/publication/245623481
• Preattentive processing can help to rapidly draw the focus of attention to a target with a unique
visual feature (i.e., little or no searching is required in the preattentive case).
– Healey, 2005, https://www.csc2.ncsu.edu/faculty/healey/PP/index.html
•
The technique is commonly used in many fields involving visual designs, including:
– UX/UI and interaction design
– Data/information visualizations (charts, maps, dashboards)
– Web design, product design, shelf display, painting, etc.
• Basic technique: using contrast to differentiate the part that needs to draw attention
– http://kenhirakawa.com/significance-of-contrast/
– https://www.coursera.org/lecture/dataviz-design/strategic-use-of-contrast-sDV6C
59
Some examples by using various
distinctive visual properties
Extended reading:
“What shall we do with the preattentive processing stage”
https://www.researchgate.net/publication/245623481
More examples in “Perception in Visualization” by
Christopher Healey
https://www.csc2.ncsu.edu/faculty/healey/PP/index.html
Pre-Attentive Processing are
covered with more details in
module 2 and emphasized
throughout the course.

https://www.webfx.com/blog/web-design/gestalt-principles-applied-in-design/


https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception

Gestalt Principles of Perception
• Gestalt principles describes a set
of ways how human perceives
images and how visual information
are identified and related from
images.
• These principles have profound
implication on many fields involving
visual designs, including:
– UX/UI and interaction design
– Data/information visualizations
(charts, maps, dashboards)
– Web design
– Graphical design
– Painting/Photography
– Shelf display, catalog, form, etc.
– See how it is applied in general visual
designs
https://www.webfx.com/blog/web-
design/gestalt-principles-applied-in-
design/
60
Proximity
Objects that are close
together are perceived as a
group.
Similarity
Objects that share similar
attributes (e.g., color or
shape) are perceived as a
group.
Enclosure Objects that appear to have a
boundary around them (e.g.,
formed by a line or area of
common color) are perceived
as a group.
Closure
Open structures are
perceived as closed,
complete, and regular
whenever there is a way that
they can be reasonably
interpreted as such.
Continuity Objects that are aligned
together or appear to be a
continuation of one another
are perceived as a group.
Connection Objects that are connected
(e.g., by a line) are perceived
as a group.
Table from: https://www.interaction-design.org/literature/book/the-encyclopedia-
of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception
Gestalt Principles are covered with
more details in module 2 and
emphasized throughout the course.

https://www.interaction-design.org/literature/article/information-visualization-a-brief-20th-and-21st-century-history

Data Visualization and IT
• Modern advanced and interactive visualizations are driven by the need
for technology and tool support (design, development/programming,
automation, delivery, and administration).
• Michael Friendly offers some key points how IT drives the modern data
visualization (https://www.interaction-
design.org/literature/article/information-visualization-a-brief-20th-and-
21st-century-history)
– The field of information (data) visualization has broadened to encompass
many new forms of data, data structure and problem solving.
– Highly interactive computing systems have been developed and are in
common use. This is compared to early command-driven systems which
used compiled, batch processing.
– The information visualization field has begun to implement cognitive and
perceptual aspects of displaying data in addition to delivering simple static
visualizations which were aesthetically pleasing.
– Data with large volumes of dimensions can be better explored and
analyzed.
• Application of automation and AI
61

http://idashboards.com/


http://www.klipfolio.com/


http://www.benlcollins.com/spreadsheets/dynamic-dashboard-in-google-spreadsheets/


https://developers.google.com/chart/


http://selection.datavisualization.ch/


https://www.g2crowd.com/categories/data-visualization


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://bigdata-madesimple.com/review-of-20-best-big-data-visualization-tools/

Data Visualization Tools
•
Modern visualizations are largely dependent or enabled by visualization tools. Visualization products have been evolving fast, and there is
increasing overlap. But they generally fall into three major categories.
•
Standalone tools
–
They are specifically designed to produce stunning visualizations, and they can work with multiple platforms and data sources.
–
Some of them are growing to more full stack analytics tools.
–
They can be desktop based and/or cloud based
–
Examples: Tableau, Power BI, QlikView, Dundas, Spotfire, SAP Lumira, etc.
–
Cloud: Google Data Studio, http://idashboards.com, http://www.klipfolio.com
•
Embedded tools
–
Broader analytics, business intelligence, and reporting platforms (and even advanced spreadsheet programs) that often incorporate visualization
capabilities. These products can address more complex data platform needs and often provide wide-ranging capabilities but may require more training
in order to exploit their full potential. In some cases, IT may need to be looped in to assist in integrating these tools with underlying data and related
applications.
–
Examples like SSRS, IBM, Oracle, MicroStrategy, SAP Crystal, and others.
–
Microsoft Excel, Google Docs Spreadsheet http://www.benlcollins.com/spreadsheets/dynamic-dashboard-in-google-spreadsheets/
•
Developer-oriented visualization libraries and APIs
–
These tools are offered as programming libraries or services for general applications (web, mobile, etc.).
–
These tools can be useful when the visualization requires complete customization, substantial interactivity, or for developing a framework that allows
you to reuse code.
–
Examples
•
Programming library:, D3, dotNetCharting, Telerik, Nevron, amCharts, etc.
• Web API: Google Charts (https://developers.google.com/chart/)
•
Programming language capabilities: R, Python
•
More tools
–
http://selection.datavisualization.ch
–
https://www.g2crowd.com/categories/data-visualization
–
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://bigdata-madesimple.com/review-of-20-best-big-data-visualization-tools/
62
We will cover these topics with more details in IT 7113 module 11.

https://www.linkedin.com/pulse/why-so-many-visualization-bi-tools-adam-roderick/


https://www.g2.com/categories/data-visualization


https://www.mordorintelligence.com/industry-reports/data-visualization-applications-market-future-of-decision-making-industry

The Industry
• Why are there so many
visualization tools?
– https://www.linkedin.com/pulse/why
-so-many-visualization-bi-tools-
adam-roderick/
•
Industry consolidation (as with the
BI industry consolidation)
– Atlassian acquired Chartio (2022)
– Airtable acquired Bayes (2021)
– Google bought Looker (2020)
– Salesforce bought Tableau (2019)
63
https://www.g2.com/categories/data-visualization
The global data visualization market is
expected to register a CAGR of over 9%
during the forecast period (2020 - 2025).
https://www.mordorintelligence.com/industry-
reports/data-visualization-applications-market-
future-of-decision-making-industry
Learning Data Visualization
Skills, jobs, career, and learning resources
64
Skills in Data Visualization Dev.
• Data visualization draws knowledge and experience from multiple fields
including computing, business, and design.
• Most important
– Visualization design: charts, diagrams, maps, etc.
– UI and interaction design
– Knowledge of the dev tool
– Business domain knowledge
• Highly useful
– Communication, story telling
– Programming/scripting
– Data literacy, statistics
• Very helpful
– Data models
– Data preparation
– Analytics methods
– Artistic design
–
Information behavior
65

https://www.linkedin.com/jobs2/view/12915000

Data Visualization: Sample Real Jobs
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
Data Visualization Analyst (originally posted
on LinkedIn):
• 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.
66

https://www.usaspending.gov/#/explorer


https://itdashboard.gov/


https://www.vox.com/2018/1/8/16822374/school-segregation-gerrymander-map


https://www.jato.com/station-wagons-are-disappearing-but-wait-theres-hope/


https://medium.com/nightingale/2019-was-the-year-data-visualization-hit-the-mainstream-d97685856ec

Data Visualization Trends
• Public communication with intensive visualizations - used creatively in
many public media like
– Journalism (US News Election coverage)
– Government report (https://www.usaspending.gov/#/explorer,
https://itdashboard.gov)
• More common and easy interactive maps
• Visualization intensive stories (narrative with creative and interactive
data visualizations)
– https://www.vox.com/2018/1/8/16822374/school-segregation-gerrymander-
map
– https://www.jato.com/station-wagons-are-disappearing-but-wait-theres-
hope/
• Dashboards and visualizations in more types of display media and
interfaces
– Mobile friendly visualizations
–
Interactive super big displays
– VR/AR environments
67
Interesting read from Elijah Meeks
https://medium.com/nightingale/2019-was-the-year-data-
visualization-hit-the-mainstream-d97685856ec

http://zheng.kennesaw.edu/teaching/it7113


http://ccse.kennesaw.edu/it/programs/cert-dm.php


http://idi.kennesaw.edu/it7113/


https://www.edocr.com/user/jgzheng/collection/datavisualizationlecturenotes


https://www.coursera.org/specializations/data-visualization


https://courses.cs.washington.edu/courses/cse442/


https://courses.cs.washington.edu/courses/cse512/

Learning Data Visualization
•
IT 7113 Data Visualization (MSIT)
– http://zheng.kennesaw.edu/teaching/it7113
– An elective course in the KSU MSIT and “certificate on data
analytics and technology”
http://ccse.kennesaw.edu/it/programs/cert-dm.php
– Open educational resources at http://idi.kennesaw.edu/it7113/
• Lecture notes serials
– https://www.edocr.com/user/jgzheng/collection/datavisualizationlectu
renotes
• DATA 3230 Data Visualization
• Other good courses
– UC Davis on Coursera
https://www.coursera.org/specializations/data-visualization
– University of Washington CSE 442/512:
https://courses.cs.washington.edu/courses/cse442/
https://courses.cs.washington.edu/courses/cse512/
68

https://www.highcharts.com/blog/post/role-data-visualization-business-intelligence/


https://chrisluv.medium.com/defining-data-visualisation-daf71c22ec03


https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed/data-visualization-for-human-perception


https://www.researchgate.net/publication/321804138_Data_Visualization_for_Business_Intelligence

Key Readings
• The Role of Data Visualization in Business Intelligence:
https://www.highcharts.com/blog/post/role-data-visualization-business-
intelligence/ - this is a very practical article for some quick reading
• Defining Data Visualisation https://chrisluv.medium.com/defining-data-
visualisation-daf71c22ec03
• Data Visualization for Human Perception (by Stephen Few):
https://www.interaction-design.org/literature/book/the-encyclopedia-of-
human-computer-interaction-2nd-ed/data-visualization-for-human-
perception - this is a very conceptual and intensive reading
• Zheng (2017) Book Chapter Data Visualization in Business Intelligence
(PDF downloadable on the site):
https://www.researchgate.net/publication/321804138_Data_Visualizatio
n_for_Business_Intelligence (note: this chapter generally corresponds
to the lecture notes but the lecture notes is more recent and updated.
Use it together with the lecture notes).
69

https://www.youtube.com/watch?v=GVkXbQOzKNs


https://www.tableau.com/learn/articles/data-visualization


https://www.perceptualedge.com/blog/?p=2636


http://aisel.aisnet.org/cgi/viewcontent.cgi?article=2483&context=cais


https://en.wikipedia.org/wiki/Data_visualization


https://en.wikipedia.org/wiki/Information_visualization


https://en.wikipedia.org/wiki/Infographic


https://en.wikipedia.org/wiki/Scientific_visualization


https://en.wikipedia.org/wiki/Visualization_(graphics)


https://en.wikipedia.org/wiki/Visual_analytics

Additional Good Resources
• Data Visualisation - A Game of Decisions with Andy Kirk
https://www.youtube.com/watch?v=GVkXbQOzKNs
• What Is Data Visualization? Definition, Examples, And Learning
Resources https://www.tableau.com/learn/articles/data-visualization
• What is data visualization:
https://www.perceptualedge.com/blog/?p=2636
• Tegarden (1999) CAIS Business Information Visualization (a bit aged
but still classic):
http://aisel.aisnet.org/cgi/viewcontent.cgi?article=2483&context=cais
• Some general Wikipedia resources
– https://en.wikipedia.org/wiki/Data_visualization
– https://en.wikipedia.org/wiki/Information_visualization
– https://en.wikipedia.org/wiki/Infographic
– https://en.wikipedia.org/wiki/Scientific_visualization
– https://en.wikipedia.org/wiki/Visualization_(graphics)
– https://en.wikipedia.org/wiki/Visual_analytics
70

http://www.perceptualedge.com/


https://www.edwardtufte.com/tufte/


https://en.wikipedia.org/wiki/Ben_Shneiderman


https://www.visualisingdata.com/about/


https://excelcharts.com/


https://homes.cs.washington.edu/~jheer/


https://bost.ocks.org/mike/


http://alignedleft.com/


http://ugamarkj.blogspot.com/


https://www.dataplusscience.com/insights.html


http://www.vizwiz.com/


https://www.ryansleeper.com/


http://duelingdata.blogspot.com/


https://www.kenflerlage.com/


https://public.tableau.com/app/profile/stanke


https://public.tableau.com/app/profile/datavizard


https://www.sirvizalot.com/


https://www.dataatworkbook.com/


https://www.amazon.com/dp/0970601972/


http://www.amazon.com/gp/product/1938377001/


https://clauswilke.com/dataviz/


https://www.datavisualizationsociety.org/


http://www.visualizing.org/


http://www.interaction-design.org/


http://www.storytellingwithdata.com/


http://flowingdata.com/


https://ourworldindata.org/


https://nightingaledvs.com/


https://www.interaction-design.org/literature/topics/information-visualization


https://www.techtarget.com/searchbusinessanalytics/resources/Data-visualization


http://understandinggraphics.com/


https://visage.co/blog/


https://informationisbeautiful.net/


https://www.ted.com/playlists/56/making_sense_of_too_much_data


https://www.sas.com/en_us/insights/big-data/data-visualization.html


https://www.sas.com/en_us/insights/big-data/data-visualization.html


https://material.io/design/communication/data-visualization.html


http://blog.visual.ly/


https://www.darkhorseanalytics.com/


https://playfairdata.com/

General Resources
•
Influencers
–
Stephen Few http://www.perceptualedge.com/
–
Edward Tufte https://www.edwardtufte.com/tufte/
–
Ben Shneiderman https://en.wikipedia.org/wiki/Ben_Shneiderman
–
Andy Kirk https://www.visualisingdata.com/about/
–
Jorge Camoes https://excelcharts.com/
–
Jeffrey Heer https://homes.cs.washington.edu/~jheer/
–
Mike Bostock https://bost.ocks.org/mike/
–
Scott Murray http://alignedleft.com
•
Tableau Zen Masters
–
Mark Jackson http://ugamarkj.blogspot.com
–
Jeffrey Shaffer https://www.dataplusscience.com/insights.html
–
Andy Kriebel http://www.vizwiz.com
–
Ryan Sleeper https://www.ryansleeper.com
–
Adam McCann http://duelingdata.blogspot.com
–
The Flerlage twins https://www.kenflerlage.com
–
Luke Stanke https://public.tableau.com/app/profile/stanke
–
Jacob Olsufka https://public.tableau.com/app/profile/datavizard
–
Matt Chambers https://www.sirvizalot.com
•
Books
–
Andy Kirk, Data Visualisation: A Handbook for Data Driven Design
–
Jorge Camoes, Data at Work https://www.dataatworkbook.com
–
Stephen Few, Show Me the Numbers,
https://www.amazon.com/dp/0970601972/
–
“Information Dashboard Design” 2nd, by Stephen Few, 2013,
http://www.amazon.com/gp/product/1938377001/
–
https://clauswilke.com/dataviz/
–
Designing Data Visualizations, by Julie Steele, Noah Iliinsky, O’Reilly,
2011
•
Communities and organizations
–
https://www.datavisualizationsociety.org
–
http://www.visualizing.org/
–
http://www.interaction-design.org/
–
http://www.storytellingwithdata.com
–
http://flowingdata.com
–
https://ourworldindata.org
•
News, media, and magazines
–
https://nightingaledvs.com
–
https://www.interaction-design.org/literature/topics/information-
visualization
–
https://www.techtarget.com/searchbusinessanalytics/resources/Data-
visualization
–
http://understandinggraphics.com/
–
https://visage.co/blog/
–
https://informationisbeautiful.net/
–
TED videos:
https://www.ted.com/playlists/56/making_sense_of_too_much_data
•
Company resources
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https://www.tableau.com/learn/articles/data-visualization
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https://www.sas.com/en_us/insights/big-data/data-visualization.html
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https://material.io/design/communication/data-visualization.html
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http://blog.visual.ly/
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https://www.darkhorseanalytics.com
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https://playfairdata.com
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