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Overview:

One of the objectives of this course is to help you think about how you interact with and respond to data you encounter and the way in which it is communicated to you. This assessment provides you the opportunity to systematically think about each topic that we consider in class, reflecting on what you have learned, what you observe in the world around you and how you will use these learnings in the future.  

Required:

At the end of the course, you will complete a 1000-1200 word course reflection, integrating the reflections from your weekly submissions.

This will be worth 15.5% of your final grade.

In this final reflection you need to discuss THREE key takeaways for you from this course with specific reference to how you will act on these takeaways in the short or long term.  Note that a good review will also articulate whether you feel you have achieved the course learning outcomes. 

There is no peer review required for this final submission.

Course Learning outcomes addressed:

· Create a data visualisation, from a provided dataset, that delivers a compelling narrative to a specified audience. 

· Create data visualisations in a data visualisation tool. 

· Evaluate, critique, and suggest improvements to, visual representations of data. 

· Identify, and suggest improvements to, unethical uses of data visualisations in business settings. 

· Design, and deliver effective, engaging presentations to a live audience that carefully consider the audience’s perspective and address their needs. 

Visualisation Basics: Introduction to Tableau

Tutorial 1| Week 1

BUSMGT 708: Communicating Business Insights

Title Slide

Introduction – Lab’s format

Data Culture

Tableau installation

Introduction to Tableau

Tableau Tools

Tableau Interface

Connecting with databases

Data Connection: Live vs extract

Tableau Public

Contents

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Table of Contents

Lab Format

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BUSMGT 708 | Tutorial 1

Learn

Practices

Deliver

Data Culture

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What is data culture?

A Data Culture is the collective behaviors and beliefs of people who value, practice, and encourage the use of data to improve decision-making. As a result, data is woven into the operations, mindset, and identity of an organization. A Data Culture equips everyone in your organization with the insights they need to be truly data-driven, tackling your most complex business challenges.

Practice data-driven behaviors – Align data and analytics to business outcomes.

Value strategic data use – Prioritize data in decision-making and business processes.

Encourage sharing & community -Unite over a shared mission to lead with data.

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IDC Whitepaper, Sponsored By Tableau, How Data Culture Fuels Business Value In Data-driven Organizations, Doc. #Us47605621, May 2021.

BUSMGT 708 | Tutorial 1

https://www.tableau.com/why-tableau/data-culture

https://www.tableau.com/sites/default/files/2021-05/Tableau_WhitePaper_US47605621_FINAL-2.pdf

Data-Driven Organization

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83% of CEOs want a data-driven organization

87% of CXOs prioritize becoming an intelligent enterprise

74% require data in decision-making

*IDC is International Data Corporation – a global market intelligence firm.

According to IDC survey research, organizations with strong Data Cultures were more likely than their peers to be data-driven, using data in three distinct ways:

Integrated into Daily Meetings and Discussions

When Recommending Next Steps or Actions

To Support Major Decisions

BUSMGT 708 | Tutorial 1

Why Tableau?

Tableau is a visual analytics platform transforming the way we use data to solve problems—empowering people and organizations to make the most of their data.

Tableau helps people and organizations be more data-driven.

Tableau disrupted business intelligence with intuitive, visual analytics for everyone.

Tableau helps people drive change with data.

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https://www.tableau.com/why-tableau/what-is-tableau

BUSMGT 708 | Tutorial 1

Tableau Tools

Tableau Prep: Prepare, clean, and format data to make analysis easier.

Tableau Desktop: Connect to data and start seeing what the data has to say.

Tableau Server: Share and store data on this web-based, customer-hosted platform.

Tableau Online: Share and store data in the cloud with this web-based, Tableau-hosted platform.

Tableau Public: Tableau Public is a free platform to publicly share and explore data visualizations online.The Tableau Community create, share data, visualisations with Tableau Public.

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BUSMGT 708 | Tutorial 1

Tableau Use

In Class

Learn, Practice, Create, Share

For Fun

Unleash your creativity with beautiful visualizations on topics you are passionate about. Instagram data,  Marvel Cinematic Universe

For Career

Tableau visualizations are your e-Portfolio

For Social Good

Make vizzes to promote a cause close to your heart such as the International Coastline
Cleanup or Gender Equality. Post your own on Tableau Public with the hashtag #VizForSocialGood.

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BUSMGT 708 | Tutorial 1

Tableau Installation

Availability:

Tableau Desktop has been installed in the OGGB computer labs.

You can also get a free copy of Tableau Desktop for your own personal use.

Download the latest version of Tableau Desktop and Tableau Prep Builder

Click on the link above and select “Download Tableau Desktop” and “Download Tableau Prep Builder”. On the form, enter your school email address and enter the name of your school for Organization.

Activate with your product key: TC9N-0EE1-97D0-540C-E487

Already have a copy of Tableau Desktop installed? Update your license in the application: Help menu ? Manage Product Keys

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*The Tableau licenses and resources we use in this course are provided through the Tableau for Teaching program.

BUSMGT 708 | Tutorial 1

Getting started

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Tableau guides you with connecting to or importing data. On the left-hand side of the screen, you will see the Connect bar.

The choices for the data types you can use in Tableau are listed under Connect.

BUSMGT 708 | Tutorial 1

Instructor: You may want to explain here that there are many file formats that contain data. But the bottom line is that Tableau and most database programs work primarily with structured data, data that is organized in rows and columns. Data can come in those rows and columns in a database management program, which works with more complex file formats, or in spreadsheet such as Excel or Google Sheets. Or, data can come in a text file (see next slide). We’ll get to more definitions of the more complex database programs later in the modules. But for now, we’ll focus on text files and spreadsheets in terms of how we import data into Tableau.

Connecting to data sources and

databases

Tableau can connect to various types of data sources including excel files, text files, PDF files, JSON files, Spatial files, statistical files, and so on.

Find list of compatible file types here: https://help.tableau.com/current/pro/desktop/en-us/exampleconnections_overview.htm

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BUSMGT 708 | Tutorial 1

Connecting to Excel and Text Files

You can add different types of data formats into Tableau.

You can use excel or text file, Access or statistical files.

In Tableau Desktop, you can also connect with multiple types of data sets from your desktop, online or from tableau server set by your organization.

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Connecting to Google Sheets

A new feature of the Tableau 10 (desktop and public) enables you to connect with live data from google sheets.

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BUSMGT 708 | Tutorial 1

Connecting to Web Data Connectors

The web data connector helps to build connections with live web data. Any data to almost any data accessible over http.

You can also build your own live data sets.

These data sets are designed by individuals or organizations and may vary in their design.

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BUSMGT 708 | Tutorial 1

Connecting to Spatial Files

You can create maps with geographic entities like cities, countries, postal codes, zips code etc.

To plot other geographical maps, you can use spatial files – to create maps with election districts, school zones, climate zones, conference zones etc.

You can connect to the following spatial file types:

Shapefiles,

MapInfo tables,

KML (Keyhole Markup Language) files,

GeoJSON files,

TopoJSON files, and

Esri File Geodatabases

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BUSMGT 708 | Tutorial 1

Connecting to PDFs

You can connect PDFs to tableau. There might be two types of PDFs files:

Tabulated data structured: Each page will show up as separate sheets. If the data is structured in same format, you can union all pages to connect and show as a single sheet.

Unstructured tabulated data: Most PDFs are not perfectly setup as tabulated data. For this you need to select pages with tabulated data and then clean it manually

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BUSMGT 708 | Tutorial 1

Data Connections: Live and Extract

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Live connection. This refers to a data source that contains direct connection to underlying data, which provides real-time or near real-time data.

Extract. Extract connection is a snapshot of data. An extract (.tde or .hyper file) might be created from a static source of data, like an Excel spreadsheet. Make sure that the path to an original file stays same.

BUSMGT 708 | Tutorial 1

Users working with Tableau Desktop can publish data sources that contain extract or live connections.

Extract data is snapshot of data on a particular time or phase.

Live: With a live connection, Tableau makes queries directly against the database or other source and returns the results of the query for use in a workbook. Users can create live connections and then share them on Tableau Server so that other Tableau users can use the same data using the same connection and filtering settings. As the Tableau Server administrator, you can manage credentials and the permissions associated with the data source to control what data users can access.

Saving your work

Save a workbook – Saves all open worksheets.

Make sure to continuously saving your work.

Save a packaged workbook – Saves the workbook along with all referenced local file data sources and images into a single file.

These workbooks are saved with a .twbx file extension.

Sharing Workbooks – You can share workbooks with team mates, provided that they can access the relevant data sources that the workbook uses.

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https://help.tableau.com/current/pro/desktop/en-us/save_savework.htm

BUSMGT 708 | Tutorial 1

Tableau Interface and Basics

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Workspace Area

A. Workbook name. A workbook contains sheets. A sheet can be a worksheet, a dashboard, or a story.

B. Cards and shelves – Drag fields to the cards and shelves in the workspace to add data to your view.

C. Toolbar – Use the toolbar to access commands and analysis and navigation tools.

D. View – This is the canvas in the workspace where you create a visualization (also referred to as a “viz”).

E. Click this icon to go to the Start page, where you can connect to data.

F. Side Bar – In a worksheet, the side bar area contains the Data pane and the Analytics pane.

G. Click this tab to go to the Data Source page and view your data.

H. Status bar – Displays information about the current view.

I. Sheet tabs – Tabs represent each sheet in your workbook. This can include worksheets, dashboards, and stories.

https://help.tableau.com/current/pro/desktop/en-us/environment_workspace.htm

Worksheet, Dashboard

and Story

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Worksheet

Dashboard

Story

Add new worksheet, dashboard, story

BUSMGT 708 | Tutorial 1

Dimensions and Measures

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Dimensions

Measures

Tableau assigns each field in the data source as dimension or measure in the Data pane, depending on the type of data the field contains.

It is important to understand type of data in different columns, how tableau understood it by categorising into different pills (dimensions or measure). As it will impacts every level of functionality in the analysis, from the way the data displays to the deeply technical, behind the scenes approach to how data is processed.

BUSMGT 708 | Tutorial 1

Instructor: If you want to explain a little bit more,

Tableau is similar to Excel in that its files are called workbooks and the sheets inside the workbook are called, well, sheets. There are a few additional features as well. For example, once you have created all the sheets you want and visualized data in the sheets, you add a dashboard tab to your workbook. The dashboard is where you place your sheets and design how you want them to look. Confused? Don’t worry; it will all become clear.

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Dimensions are typically those columns or fields that are text or that you are not going to do math on.

Dimensions are typically:

Discrete data, not continuous as in numbers, but there is an exception: date fields are dimensions.  

Qualitative data like names, dates, places, etc. 

It is shown as blue pills 

Dimensions

BUSMGT 708 | Tutorial 1

Dimensions contain qualitative values (such as names, dates, or geographical data). You can use dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of detail in the view.

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Measures are data you can calculate, so the compensation and expenses are measures. Measures are continuous data.

Continuous data: quantitative data that can be measured in some way.

It is shown as green pills

Measures

BUSMGT 708 | Tutorial 1

Instructor: Once you are in the Tableau workspace, you need to explain how to navigate around a little bit. Important points you will explain are the definitions of Dimensions, Measures and the Show Me panel. Tableau is basically a drag and drop interface, meaning once your students understand the basics, they can do some ambitious data analysis and visualization.

In this class, the number of students is discrete data. There cannot be half of a student. The age of each student is continuous data. It can be any age (within the range of possible human age).

Tableau Public

Tableau Public is a free platform to publicly share and explore data visualizations online.The Tableau Community create, share data, visualisations with Tableau Public.

The Tableau Community, that you can access via Tableau Public has more than one million members, spanning over 500 user groups worldwide and our active Community Forums and programs. The Tableau Community is active, diverse, creative, and supportive of one another on and offline, sharing connections, experiences, and best practices.

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BUSMGT 708 | Tutorial 1

Create Tableau Public Profile

Subscribe to “Viz of the Day”

Exercise

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Travel Planner + Emissions Calculator

https://help.tableau.com/current/pro/desktop/en-us/publish_workbooks_tableaupublic.htm

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Publish work on Tableau Public

To publish your workbook on Tableau Public >

Go to server > Save to Tableau Public

Sign in with your Tableau Public Account

If you see an errors, make sure that your data connection is set as “Extract”

Save and copy the link to share with your tutors.

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BUSMGT 708 | Tutorial 1

BUSMGT 708 | Tutorial 1

Show during lab

BUSMGT 708 | Tutorial 1

Frameworks
Week 02b
BUSMGT 708 Communicating Business Insights

1

Learning outcomes:

By the end of this session you should be able to:

Understand and apply the Design Triangle

Understand and apply the Nested Model of Visualization Design and Validation

Understand and apply Fung’s Junk Chart Trifecta

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Agenda:

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Design Triangle

Nested Model

Fung’s Junk Chart Trifecta

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Design Triangle

Nested Model

Fung’s Junk Chart Trifecta

Design Triangle

Source: Miksch & Aigner (2014).

Representation

& Interaction

Data

Task

User

scale (quantitative vs. qualitative)

frame of reference (abstract vs. spatial) 

kind of data (events vs. states)

number of variables (univariate vs. multivariate)

Group factors:

application domain (e.g., health-care, business etc.)

physical environment (e.g., poor lighting)

social factors (e.g., collaborative work or cultural specifics technical specifics (e.g., hardware, screen resolution)

Individual factors:

level of technical and domain expertise (e.g., experts, apprentices, or novices)

specific metaphors and mental models that are used

disabilities (e.g., color-blindness).

Elementary tasks address individual data elements (individual or individual groups of data)

Synoptic tasks involve a general view and consider sets of values or groups of data in their entirety.

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Design Triangle

Representation

& Interaction

Data

Task

User

Expressiveness

Source: Miksch & Aigner (2014).

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Expressiveness

A visualization is considered to be expressive if the relevant information of a dataset (and only this) is expressed by the visualization.

The term “relevant” implies that expressiveness of a visualization can only be assessed regarding a particular user working with the visual representation to achieve certain goals.

“A visualization is said to be expressive if and only if it encodes all the data relations intended and no other data relations.” [Card, 2008, p. 523]

Source: Miksch & Aigner (2014).

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Design Triangle

Representation

& Interaction

Effectiveness

Data

Task

User

Expressiveness

Source: Miksch & Aigner (2014).

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Effectiveness

A visualization is effective if it addresses the capabilities of the human visual system. Since perception, and hence the mental image of a visual representation, varies among users, effectiveness is user-dependent.

Nonetheless, some general rules for effective visualization have been established in the visualization community.

“Effectiveness criteria identify which of these graphical languages [that are expressive], in a given situation, is the most effective at exploiting the capabilities of the output medium and the human visual system.” (Mackinlay, 1986)

Source: http://www.infovis-wiki.net/index.php?title=Effectiveness

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Design Triangle

Representation

& Interaction

Expressiveness

Effectiveness

Appropriateness

Data

Task

User

Source: Miksch & Aigner (2014).

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Appropriateness

Appropriateness regards the trade-off between efforts required for creating the visual representation and the benefits yielded by it. If this trade-off is balanced, the visualization is considered to be appropriate.

Source:http://www.infovis-wiki.net/index.php?title=Appropriateness

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Design Triangle

Representation

& Interaction

Expressiveness

Effectiveness

Appropriateness

Data

Task

User

Source: Miksch & Aigner (2014).

Relevance

Usefulness

Cost

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Design Triangle

Nested Model

Fung’s Junk Chart Trifecta

Nested Model of Visualization Design and Validation

Source: Munzer (2009)

Domain Situation

Data/Task Abstraction

Encoding/Interaction Technique

Algorithm

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Nested Model of Visualization Design and Validation

Source: Munzer (2009)

Domain Situation

describing a group of target users, their domain of interest, their questions, and their data

Data/Task Abstraction

abstracting the specific domain questions and data from the domain specific form into a generic, computational form

Encoding/Interaction Technique

decide on the specific way to create and manipulate the visual representation of the abstraction

Algorithm

crafting a detailed procedure that allows a computer to automatically and efficiently carry out the desired visualization goal

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Nested Model of Visualization Design and Validation

Source: Munzer (2009)

Threat: Wrong problem Avoid: Observe and interview target users

Threat: Bad data/task abstraction

Validate: Test on target users, document usage for utility

Threat: Ineffective encoding/interaction technique

Validate: Test on users using qualitative/quantitative measures

Threat: Slow algorithm

Avoid: Analyze computational complexity

Validate: Measure algorithm speed

Implement System

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Design Triangle

Nested Model

Fung’s Junk Chart Trifecta

Kaiser Fung

Columbia University

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

How to identify junk charts?

What is the QUESTION?

What does the DATA say?

What does the VISUAL say?

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The Trifecta

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

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Single Issue: Type Q

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

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Single Issue: Type D

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

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Single Issue: Type V

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

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Double Issue: Type QD

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

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Double Issue: Type QV

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

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Double Issue: Type DV

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

http://musically.com/2014/03/04/how-digital-music-services-may-be-fuelling-a-superstar-artist-economy/?curator=MediaREDEF

HOW DIGITAL MUSIC SERVICES MAY BE FUELLING A ‘SUPERSTAR ARTIST ECONOMY’

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Triple Issue: Type QDV

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

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Triple Issue: Type QDV

Source: http://junkcharts.typepad.com/junk_charts/junk-charts-trifecta-checkup-the-definitive-guide.html

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Recap:

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Design Triangle

Nested Model

Fung’s Junk Chart Trifecta

References:

Card,S. (2008) Information visualization, in A. Sears and J.A. Jacko (eds.), The Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications, Lawrence Erlbaum Assoc Inc, 2007.

Mackinlay, J. (1986). Automating the design of graphical presentations of relational information. ACM Transactions on Graphics,5(2), 110-141. doi:10.1145/22949.22950

Miksch, S., & Aigner, W. (2014). A matter of time: Applying a data–users–tasks design triangle to visual analytics of time-oriented data. Computers & Graphics, 38, 286-290. doi:10.1016/j.cag.2013.11.002

Munzner, T. (2015). Visualization analysis and design. Boca Raton: CRC Press, Taylor & Francis Group.

Tufte, E. (2001) The visual display of quantitive information.

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Hello! ?
We’ll start soon

Who am I?

3

Do only Nerds do
Dataviz?*

*Betteridge’s law applies (mostly)!

CW: Suicide, Illness

Pre-attentive attributes

A brief history lesson

1985 2013

Visualisation is everywhere

Visualisation is everywhere

Because it works!

https://www.pentagram.com/work/starbucks

How do you get into
Data Visualisation?

Start a job!

Build your skills!

Data

Domain Design

Data

Domain Design

Data

Domain Design

Build your portfolio!

1. MakeoverMonday
2. WorkoutWednesday
3. IronQuest
4. IronViz
5. Real World Fake Data
6. Back 2 Viz Basics
7. SportsvizSunday
8. ProjectHealthViz
9. 30DayChartChallenge
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11. Viz for Social Good
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