Lecture for IT 7123 at Kennesaw State University - updated in 2024.
About Jack Zheng
Faculty of IT at Kennesaw.edu
Data Presentation in
BI/Analytics
Jack G. Zheng
Spring 2024
http://zheng.kennesaw.edu/teaching/it7123
IT 7123 BI
Overview
• Basic methods of presenting data
– Textual
– Structured (flow list, grid, table, card)
– Graphical (data visualization)
• Selected Power BI visuals for data
presentation
Data visualization has become a significant part in analytics and business
intelligence. In IT 7123 we only briefly touch the topic. For more coverage on data
visualization and dashboard design, see
•
IT 7113 Data Visualization http://idi.kennesaw.edu/it7113/
• Data Visualization Lecture Notes Serials
https://www.edocr.com/user/jgzheng/collection/datavisualizationlecturenotes
Data/Information 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.
3
Key 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
Textual Presentation
•
Textual presentation of data means presenting data in the form of words, sentences and
paragraphs.
•
The textual presentation of data is used when the data is not large and can be easily
comprehended by the reader just when he reads the paragraph.
•
This data presentation is useful when some qualitative statement is to be supplemented with
key data that is directly supporting the statement.
• An advantage of the textual form is the content can be delivered through voice
• Various textual forms
– Paragraph
– Bulleted/numbered list
• Use examples
– News
– Story mode
– Reporting highlights
https://finance.yahoo.com/news/exxon-mobil-rides-again-tech-205233533.html
https://investor.bankofamerica.com/fixed-income Fixed Income Investor Materials
Textual Presentation in Power BI
• Power BI offers “smart narratives”
• Use smart narrative summaries in your
reports to address key takeaways, to
point out trends, and to edit the
language and format for a specific
audience.
•
In PowerPoint, instead of pasting a
screenshot of your report's key
takeaways, you can add narratives that
are updated with every refresh.
• Your audience can use the summaries
to understand the data, get to key points
faster, and explain the data to others.
• Resources
– https://learn.microsoft.com/en-us/power-
bi/create-reports/power-bi-reports-add-text-
and-shapes
– https://learn.microsoft.com/en-us/power-
bi/visuals/power-bi-visualization-smart-
narrative
Structured Layout Presentation
6
• Flow list
– A single column/row of items
• Grid
– Exact grid with rows and columns (each cell is one data
item)
– Tiles (cells) with different sizes
– Horizontal or vertical flow of items
• Table
– Strict rows and columns, with headers
– Each row is typical for one data item (record)
• Card
– Grouping a various piece of data and information in a
card-like style
Example:
Three Display Layouts for Windows Files
7
Flow List
Table
Grid
Flow List
•
In a flow list, items are presented like a list.
• Flow list is one column (or row) based, while
grid has more columns.
• Flow list and grid are more flexible in
arranging information. Each list/grid item can
have a more complex local layout for its
attributes.
• Real world examples
– Simple list:
https://atlanta.craigslist.org/d/automotive-
services/search/aos
– More complicated flow list:
https://www.apmex.com/search?q=eagles&vt=l
(change view at the top)
– https://www.google.com/search?tbm=shop&q=nu
c
– http://camelcamelcamel.com/search?sq=shoe
8
Extended reading: Google’s design practice on mobile
https://material.io/components/lists/
There is only one column
(one item per row).
Grid
• Grid is similar to flow list but
consists of multiple columns and
rows; and each item is narrower
in width.
• Grid is suitable for ultra wide
screens; flow list items are
difficult to read if the screen or
report page is too wide.
• Real world examples
– http://atlanta.craigslist.org/cta
(click on the “gallery” view link)
– https://www.google.com/search?t
bm=shop&q=nuc&&tbs=vw:g
– http://www.newegg.com/Store/Ca
tegory.aspx?Category=19
9
The number of columns may
change in a responsive design.
Data Table
10
•
A data table is a concise way to show a lot of structured short information. Tables can accommodate data in a
very dense format; the focus is on the data itself without much distractions
–
Sometimes still utilized limited visual aid to help readability. Just like grid and list, information in each cell may have additional
formatting and local layout.
•
Types of table: flat table, pivot (matrix) table, complex table, transposed table
•
Often used for
– Much needed in printouts and exports.
–
Pure data set: https://www.nba.com/hawks/stats
–
Simple collection of related items; examples:
•
http://apps.atl.com/Passenger/FlightInfo/Search.aspx?FIDSType=A
•
https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average
–
comparison of items with many attributes, such as products, versions, services, etc.
•
https://www.newegg.com/Product/Productcompare?CompareItemList=14%2D137%2D467%2C14%2D932%2D208%2C14%2D487
%2D454%2C14%2D487%2D486
A flat table has column
or/and row headers.
https://www.goodcarbadcar.net/2022
-us-vehicle-sales-figures-by-model/
Transposed Data Table
11
Many applications offer display
style choices in list, table, and grid.
In this example, the
table is transposed,
meaning each data
record is present in a
column rather than in a
row. This is often seen
in product comparisons.
Image from https://uxmag.com/articles/designing-search-results-pages
Complex Table
12
• A complex data table has at least one
heading that spans multiple rows or columns.
https://www.oreilly.com/library/vie
w/universal-design-
for/9780596155681/ch06s03.html
Pivot Table
• Pivot table: Results are commonly presented
in a two- dimension table, called
– Pivot table, PivotTable (Excel)
– Matrix (Power BI)
– Cross tab (Access)
– https://en.wikipedia.org/wiki/Pivot_table
– See module 8 multi-dimensional analysis
Cards
14
• Card is Google’s term to describe a way to display
multiple piece of data/information as a visually cohesive
unit
– A card is like a small space with more complex layout within.
– A popular concept to design information presentation for web
and mobile applications.
– Reference: https://material.io/components/cards/
• Uses
– Can also be used for organizing presentation of data
– Commonly used for presenting KPI (key performance indicator)
• Example
https://investor.bankofamerica.com/fixed-income Fixed Income Investor Materials
2022Q3
Cards in Power BI
• Power BI card only offer some basic functionality and
style settings
– Card
– Multi-line card visual can have multiple measures
– KPI card showing vs. target and trend
• For more info
– https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-
visualization-card
– https://www.spguides.com/power-bi-card/
– https://zebrabi.com/power-bi-custom-visuals/cards/
– https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-
visualization-kpi
• KPI cards in Tableau
– https://public.tableau.com/app/profile/adam.e.mccann/viz/KPI
Options/AllDaKPIs
15
Graphical: Data Visualization
• Data are typically numerical values (but can also be qualitative)
that describe its associated entity or activity.
• Data itself is abstract. The visualization process will create visible
forms to represent the meaning of these abstract data.
– Utilizing a combination of visual elements (shapes and symbols)
and visual variables/properties like size, color, positions, etc.
• Modern systems and software applications also emphasizes the
interactive feature of this process.
16
More details about visual properties in IT 7113 module 2
https://www.edocr.com/v/631d1wpb/jgzheng/SCOPeS-Visual-Properties
More details about interactivity
in IT 7113 module 10
Data visualization is the visual representation and
presentation of data for the purpose of perception and
cognition.
Visualizing “Data Visualization”
Image from http://prezi.com/qvhyfup5z7yz/dashboard-design-making-reports-pop/
17
The cognitive visualization process in human brain and elements of visual mapping is covered with
more details in IT 7113 module 2 https://www.edocr.com/v/e6ql9njn/jgzheng/data-visual-foundation
Visualized data
Plain (tabular) data
Why Data Visualization?
• Visualizing is basically a human physiological and
psychological capability, and plays an important
role in human information behavior and decision
making
– Recall or memorize data more effectively
– Enable fast perception based on instinct (see the figure
on the right)
– Helps data comprehension and enhance problem
solving capabilities (cognition)
– Extract/provoke additional (implicit) perspectives and
meanings
– Ease the cognitive load of information processing and
exploration
– Help to shape the attention and focus
– Effective communication (story telling)
• More specifically (see examples in the following
slides)
–
Identify patterns and trends
– Quickly focus on area of interest or area of difference
Identify structures or relationships
– More comprehendible with familiar visual context
–
Identify structures and relationships that are hard to
express in words
18
A picture is worth
1000 words (clicks)
Source: How Data Visualization Empowers
Decision Making
https://community.watsonanalytics.com/wp-
content/uploads/2015/04/BlueHill_HowDataVi
sualizationDrivesDecisionMaking_Dec14.pdf
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
Basic Visual Forms/Styles used in BI and Analytics
• Conditional formatting (visual cues)
• Inline chart (Sparkline)
• Chart
• Illustrational diagram
• Map
20
A more detailed summary of visual forms and styles can be found in IT 7113 module 1 lecture:
https://www.edocr.com/v/yqwmqeba/jgzheng/business-data-visualization
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
21
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
– https://trumpexcel.com/sparklines/
22
Sparkline
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.
23
We will cover charts and their designs in IT 7113 (three modules).
https://fool.whotrades.
com/blog/43151739255
Purposes in Categorizing Charts
Purpose/function Description
Basic Charts
Comparison
Comparing and sorting data points; can
also compare to benchmarks or norms.
Column/bar
Trend/evolution
Variation of comparison involving
temporal data.
Line/area chart
Composition
A hierarchy relationship. Also, it may
imply part-to-whole comparisons.
Pie chart
Stacked column/bar chart
Tree map
Distribution
Aggregated value (usually count) of data
points placed in categories; the category
can be value ranges or time (trend).
Histogram
Scatter plot
Relationship
How things (data items) are related or
positioned in a bigger context.
Scatter plot
Bubble chart
Profiling
To comprehend things through visual
shapes and patterns.
Spider/radar chart
24
Charts are commonly categorized by the following purposes and functions. Please refer to the
following for details
– https://www.qlik.com/blog/third-pillar-of-mapping-data-to-visualizations-usage (the basic four)
– http://www.excelcharts.com/blog/classification-chart-types/ (added evolution and profiling)
A more detailed summary of chart categories can be found in IT 7113 module 3 lecture:
https://www.edocr.com/v/lonn6pal/jgzheng/chart-types-and-purposes
Chart Catalog and Selection Tool
25
• The following are detailed and interactive
references for charts. They are good resources.
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).
* I use this resource for reference a lot.
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
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.
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
Maps are covered in IT 7113 lecture https://www.edocr.com/v/npapy5k4/jgzheng/data-maps
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.
28
Data Presentation/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
29
We will cover these topics with more details in IT 7113
Microsoft Visualization Choices
• Excel
– https://excelcharts.com/10-reasons-why-take-excel-dashboards-seriously/
– 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/
• Power BI
– A more powerful self-service analytics tool that includes pretty good
visualization tools. Visual capabilities go beyond chart creation:
• Data maps
• Single and multi-page reports
•
Interactive dashboards (at this time, not through Power BI Desktop)
– https://us.hitachi-solutions.com/blog/8-reasons-why-you-should-shift-
reporting-from-excel-to-power-bi/
Key Readings
• Textual And Tabular Presentation Of Data
– https://www.toppr.com/guides/economics/presentation-
of-data/textual-and-tabular-presentation-of-data/
• Diagrammatic presentation of data
– https://www.toppr.com/guides/business-economics-
cs/descriptive-statistics/diagrammatic-presentation-of-
data/
• The Role of Data Visualization:
– https://www.highcharts.com/blog/post/role-data-
visualization-business-intelligence/
• Chart categories by purpose
– https://www.qlik.com/blog/third-pillar-of-mapping-data-to-
visualizations-usage
Power BI Visual Resources
• Create reports and dashboards in Power BI – documentation
https://learn.microsoft.com/en-us/power-bi/create-reports/
• Power BI visual reference: https://www.sqlbi.com/ref/power-bi-
visuals-reference/
• The Complete Guide to Power BI Visuals + Custom Visuals
https://www.numerro.io/guides/power-bi-visuals-guide
• Visualization types in Power BI https://learn.microsoft.com/en-
us/power-bi/visuals/power-bi-visualization-types-for-reports-and-
q-and-a
• Check the items on the left menu under “Visualizations”:
https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-
report-visualizations
• For developers https://learn.microsoft.com/en-us/power-
bi/developer/visuals/
Additional Good Resources
•
IT 7113 Data Visualization
– http://idi.kennesaw.edu/it7113/
– Business data visualization lecture notes: https://www.edocr.com/v/yqwmqeba/jgzheng/Business-Data-
Visualization
– Zheng (2017) Book Chapter Data Visualization in Business Intelligence (PDF downloadable):
https://www.researchgate.net/publication/321804138_Data_Visualization_for_Business_Intelligence
– Lecture notes collection https://www.edocr.com/user/jgzheng/collection/datavisualizationlecturenotes
• Data presentation
– Statistical data presentation https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5453888/
– http://www.slideshare.net/ahsanshafiq90/data-presentation-2-15572325
– https://www.slideshare.net/31mikaella/presentation-analysis-and-interpretation-of-data
• Data Visualization
– https://www.sas.com/en_us/insights/big-data/data-visualization.html
– How Data Visualization Empowers Decision Making: https://community.watsonanalytics.com/wp-
content/uploads/2015/04/BlueHill_HowDataVisualizationDrivesDecisionMaking_Dec14.pdf
– Tegarden (1999) CAIS Business Information Visualization (a bit aged but still classic):
http://aisel.aisnet.org/cgi/viewcontent.cgi?article=2483&context=cais
– https://www.tableau.com/learn/articles/data-visualization
• Microsoft data visualization tool choices:
https://sqlserverbiblog.files.wordpress.com/2013/04/data-visualization-choices-dav-204-
4089.pdf (a bit outdated but still a good reading)
33
BI/Analytics
Jack G. Zheng
Spring 2024
http://zheng.kennesaw.edu/teaching/it7123
IT 7123 BI
Overview
• Basic methods of presenting data
– Textual
– Structured (flow list, grid, table, card)
– Graphical (data visualization)
• Selected Power BI visuals for data
presentation
Data visualization has become a significant part in analytics and business
intelligence. In IT 7123 we only briefly touch the topic. For more coverage on data
visualization and dashboard design, see
•
IT 7113 Data Visualization http://idi.kennesaw.edu/it7113/
• Data Visualization Lecture Notes Serials
https://www.edocr.com/user/jgzheng/collection/datavisualizationlecturenotes
Data/Information 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.
3
Key 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
Textual Presentation
•
Textual presentation of data means presenting data in the form of words, sentences and
paragraphs.
•
The textual presentation of data is used when the data is not large and can be easily
comprehended by the reader just when he reads the paragraph.
•
This data presentation is useful when some qualitative statement is to be supplemented with
key data that is directly supporting the statement.
• An advantage of the textual form is the content can be delivered through voice
• Various textual forms
– Paragraph
– Bulleted/numbered list
• Use examples
– News
– Story mode
– Reporting highlights
https://finance.yahoo.com/news/exxon-mobil-rides-again-tech-205233533.html
https://investor.bankofamerica.com/fixed-income Fixed Income Investor Materials
Textual Presentation in Power BI
• Power BI offers “smart narratives”
• Use smart narrative summaries in your
reports to address key takeaways, to
point out trends, and to edit the
language and format for a specific
audience.
•
In PowerPoint, instead of pasting a
screenshot of your report's key
takeaways, you can add narratives that
are updated with every refresh.
• Your audience can use the summaries
to understand the data, get to key points
faster, and explain the data to others.
• Resources
– https://learn.microsoft.com/en-us/power-
bi/create-reports/power-bi-reports-add-text-
and-shapes
– https://learn.microsoft.com/en-us/power-
bi/visuals/power-bi-visualization-smart-
narrative
Structured Layout Presentation
6
• Flow list
– A single column/row of items
• Grid
– Exact grid with rows and columns (each cell is one data
item)
– Tiles (cells) with different sizes
– Horizontal or vertical flow of items
• Table
– Strict rows and columns, with headers
– Each row is typical for one data item (record)
• Card
– Grouping a various piece of data and information in a
card-like style
Example:
Three Display Layouts for Windows Files
7
Flow List
Table
Grid
Flow List
•
In a flow list, items are presented like a list.
• Flow list is one column (or row) based, while
grid has more columns.
• Flow list and grid are more flexible in
arranging information. Each list/grid item can
have a more complex local layout for its
attributes.
• Real world examples
– Simple list:
https://atlanta.craigslist.org/d/automotive-
services/search/aos
– More complicated flow list:
https://www.apmex.com/search?q=eagles&vt=l
(change view at the top)
– https://www.google.com/search?tbm=shop&q=nu
c
– http://camelcamelcamel.com/search?sq=shoe
8
Extended reading: Google’s design practice on mobile
https://material.io/components/lists/
There is only one column
(one item per row).
Grid
• Grid is similar to flow list but
consists of multiple columns and
rows; and each item is narrower
in width.
• Grid is suitable for ultra wide
screens; flow list items are
difficult to read if the screen or
report page is too wide.
• Real world examples
– http://atlanta.craigslist.org/cta
(click on the “gallery” view link)
– https://www.google.com/search?t
bm=shop&q=nuc&&tbs=vw:g
– http://www.newegg.com/Store/Ca
tegory.aspx?Category=19
9
The number of columns may
change in a responsive design.
Data Table
10
•
A data table is a concise way to show a lot of structured short information. Tables can accommodate data in a
very dense format; the focus is on the data itself without much distractions
–
Sometimes still utilized limited visual aid to help readability. Just like grid and list, information in each cell may have additional
formatting and local layout.
•
Types of table: flat table, pivot (matrix) table, complex table, transposed table
•
Often used for
– Much needed in printouts and exports.
–
Pure data set: https://www.nba.com/hawks/stats
–
Simple collection of related items; examples:
•
http://apps.atl.com/Passenger/FlightInfo/Search.aspx?FIDSType=A
•
https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average
–
comparison of items with many attributes, such as products, versions, services, etc.
•
https://www.newegg.com/Product/Productcompare?CompareItemList=14%2D137%2D467%2C14%2D932%2D208%2C14%2D487
%2D454%2C14%2D487%2D486
A flat table has column
or/and row headers.
https://www.goodcarbadcar.net/2022
-us-vehicle-sales-figures-by-model/
Transposed Data Table
11
Many applications offer display
style choices in list, table, and grid.
In this example, the
table is transposed,
meaning each data
record is present in a
column rather than in a
row. This is often seen
in product comparisons.
Image from https://uxmag.com/articles/designing-search-results-pages
Complex Table
12
• A complex data table has at least one
heading that spans multiple rows or columns.
https://www.oreilly.com/library/vie
w/universal-design-
for/9780596155681/ch06s03.html
Pivot Table
• Pivot table: Results are commonly presented
in a two- dimension table, called
– Pivot table, PivotTable (Excel)
– Matrix (Power BI)
– Cross tab (Access)
– https://en.wikipedia.org/wiki/Pivot_table
– See module 8 multi-dimensional analysis
Cards
14
• Card is Google’s term to describe a way to display
multiple piece of data/information as a visually cohesive
unit
– A card is like a small space with more complex layout within.
– A popular concept to design information presentation for web
and mobile applications.
– Reference: https://material.io/components/cards/
• Uses
– Can also be used for organizing presentation of data
– Commonly used for presenting KPI (key performance indicator)
• Example
https://investor.bankofamerica.com/fixed-income Fixed Income Investor Materials
2022Q3
Cards in Power BI
• Power BI card only offer some basic functionality and
style settings
– Card
– Multi-line card visual can have multiple measures
– KPI card showing vs. target and trend
• For more info
– https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-
visualization-card
– https://www.spguides.com/power-bi-card/
– https://zebrabi.com/power-bi-custom-visuals/cards/
– https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-
visualization-kpi
• KPI cards in Tableau
– https://public.tableau.com/app/profile/adam.e.mccann/viz/KPI
Options/AllDaKPIs
15
Graphical: Data Visualization
• Data are typically numerical values (but can also be qualitative)
that describe its associated entity or activity.
• Data itself is abstract. The visualization process will create visible
forms to represent the meaning of these abstract data.
– Utilizing a combination of visual elements (shapes and symbols)
and visual variables/properties like size, color, positions, etc.
• Modern systems and software applications also emphasizes the
interactive feature of this process.
16
More details about visual properties in IT 7113 module 2
https://www.edocr.com/v/631d1wpb/jgzheng/SCOPeS-Visual-Properties
More details about interactivity
in IT 7113 module 10
Data visualization is the visual representation and
presentation of data for the purpose of perception and
cognition.
Visualizing “Data Visualization”
Image from http://prezi.com/qvhyfup5z7yz/dashboard-design-making-reports-pop/
17
The cognitive visualization process in human brain and elements of visual mapping is covered with
more details in IT 7113 module 2 https://www.edocr.com/v/e6ql9njn/jgzheng/data-visual-foundation
Visualized data
Plain (tabular) data
Why Data Visualization?
• Visualizing is basically a human physiological and
psychological capability, and plays an important
role in human information behavior and decision
making
– Recall or memorize data more effectively
– Enable fast perception based on instinct (see the figure
on the right)
– Helps data comprehension and enhance problem
solving capabilities (cognition)
– Extract/provoke additional (implicit) perspectives and
meanings
– Ease the cognitive load of information processing and
exploration
– Help to shape the attention and focus
– Effective communication (story telling)
• More specifically (see examples in the following
slides)
–
Identify patterns and trends
– Quickly focus on area of interest or area of difference
Identify structures or relationships
– More comprehendible with familiar visual context
–
Identify structures and relationships that are hard to
express in words
18
A picture is worth
1000 words (clicks)
Source: How Data Visualization Empowers
Decision Making
https://community.watsonanalytics.com/wp-
content/uploads/2015/04/BlueHill_HowDataVi
sualizationDrivesDecisionMaking_Dec14.pdf
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
Basic Visual Forms/Styles used in BI and Analytics
• Conditional formatting (visual cues)
• Inline chart (Sparkline)
• Chart
• Illustrational diagram
• Map
20
A more detailed summary of visual forms and styles can be found in IT 7113 module 1 lecture:
https://www.edocr.com/v/yqwmqeba/jgzheng/business-data-visualization
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
21
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
– https://trumpexcel.com/sparklines/
22
Sparkline
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.
23
We will cover charts and their designs in IT 7113 (three modules).
https://fool.whotrades.
com/blog/43151739255
Purposes in Categorizing Charts
Purpose/function Description
Basic Charts
Comparison
Comparing and sorting data points; can
also compare to benchmarks or norms.
Column/bar
Trend/evolution
Variation of comparison involving
temporal data.
Line/area chart
Composition
A hierarchy relationship. Also, it may
imply part-to-whole comparisons.
Pie chart
Stacked column/bar chart
Tree map
Distribution
Aggregated value (usually count) of data
points placed in categories; the category
can be value ranges or time (trend).
Histogram
Scatter plot
Relationship
How things (data items) are related or
positioned in a bigger context.
Scatter plot
Bubble chart
Profiling
To comprehend things through visual
shapes and patterns.
Spider/radar chart
24
Charts are commonly categorized by the following purposes and functions. Please refer to the
following for details
– https://www.qlik.com/blog/third-pillar-of-mapping-data-to-visualizations-usage (the basic four)
– http://www.excelcharts.com/blog/classification-chart-types/ (added evolution and profiling)
A more detailed summary of chart categories can be found in IT 7113 module 3 lecture:
https://www.edocr.com/v/lonn6pal/jgzheng/chart-types-and-purposes
Chart Catalog and Selection Tool
25
• The following are detailed and interactive
references for charts. They are good resources.
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).
* I use this resource for reference a lot.
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
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.
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
Maps are covered in IT 7113 lecture https://www.edocr.com/v/npapy5k4/jgzheng/data-maps
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.
28
Data Presentation/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
29
We will cover these topics with more details in IT 7113
Microsoft Visualization Choices
• Excel
– https://excelcharts.com/10-reasons-why-take-excel-dashboards-seriously/
– 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/
• Power BI
– A more powerful self-service analytics tool that includes pretty good
visualization tools. Visual capabilities go beyond chart creation:
• Data maps
• Single and multi-page reports
•
Interactive dashboards (at this time, not through Power BI Desktop)
– https://us.hitachi-solutions.com/blog/8-reasons-why-you-should-shift-
reporting-from-excel-to-power-bi/
Key Readings
• Textual And Tabular Presentation Of Data
– https://www.toppr.com/guides/economics/presentation-
of-data/textual-and-tabular-presentation-of-data/
• Diagrammatic presentation of data
– https://www.toppr.com/guides/business-economics-
cs/descriptive-statistics/diagrammatic-presentation-of-
data/
• The Role of Data Visualization:
– https://www.highcharts.com/blog/post/role-data-
visualization-business-intelligence/
• Chart categories by purpose
– https://www.qlik.com/blog/third-pillar-of-mapping-data-to-
visualizations-usage
Power BI Visual Resources
• Create reports and dashboards in Power BI – documentation
https://learn.microsoft.com/en-us/power-bi/create-reports/
• Power BI visual reference: https://www.sqlbi.com/ref/power-bi-
visuals-reference/
• The Complete Guide to Power BI Visuals + Custom Visuals
https://www.numerro.io/guides/power-bi-visuals-guide
• Visualization types in Power BI https://learn.microsoft.com/en-
us/power-bi/visuals/power-bi-visualization-types-for-reports-and-
q-and-a
• Check the items on the left menu under “Visualizations”:
https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-
report-visualizations
• For developers https://learn.microsoft.com/en-us/power-
bi/developer/visuals/
Additional Good Resources
•
IT 7113 Data Visualization
– http://idi.kennesaw.edu/it7113/
– Business data visualization lecture notes: https://www.edocr.com/v/yqwmqeba/jgzheng/Business-Data-
Visualization
– Zheng (2017) Book Chapter Data Visualization in Business Intelligence (PDF downloadable):
https://www.researchgate.net/publication/321804138_Data_Visualization_for_Business_Intelligence
– Lecture notes collection https://www.edocr.com/user/jgzheng/collection/datavisualizationlecturenotes
• Data presentation
– Statistical data presentation https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5453888/
– http://www.slideshare.net/ahsanshafiq90/data-presentation-2-15572325
– https://www.slideshare.net/31mikaella/presentation-analysis-and-interpretation-of-data
• Data Visualization
– https://www.sas.com/en_us/insights/big-data/data-visualization.html
– How Data Visualization Empowers Decision Making: https://community.watsonanalytics.com/wp-
content/uploads/2015/04/BlueHill_HowDataVisualizationDrivesDecisionMaking_Dec14.pdf
– Tegarden (1999) CAIS Business Information Visualization (a bit aged but still classic):
http://aisel.aisnet.org/cgi/viewcontent.cgi?article=2483&context=cais
– https://www.tableau.com/learn/articles/data-visualization
• Microsoft data visualization tool choices:
https://sqlserverbiblog.files.wordpress.com/2013/04/data-visualization-choices-dav-204-
4089.pdf (a bit outdated but still a good reading)
33