Group 4 Research Presentation

1. IT 7113 Research Project
Report
Joselyn Giron
Ethan Chandler
December 15th 2019

2. • In this report we take a look at four visualization tools: Tableau,
Google Data Studio, Qlikview, and Datawrapper in order to clearly
explain the differences that each platform has.
• Business Intelligence operations in a company with low data
governance will need different capabilities than a business with
multiple DBA’s. Our goal for this report is to:
• Help better understand the proper use case for each product
• What abilities each platform provides that helps make business decisions.
• Better understand what business needs help make determinations for
data visualization tools and platforms
Abstract/executive
overview

3. DATA
VISUALIZATIO
N TOOLS
GOOGLE DATA STUDIO
DATAWRAPPER
TABLEAU
QLIKVIEW
Problem Statement
Which data visualization tool is the right one to use?

4. • Tableau has become one of the most trusted names in data visualization
software. Its design is more user friendly than most and focuses on creating
visualizations and putting them together in Stories or Dashboards. Tableau can
scale to the user's ability because of its ability to make very good visualizations
for users with no experience but with an experienced user the possibilities of
Tableau make it one of the most powerful all-around data visualization tools
today.
• On the initial start Tableau offers a view like many visualization software's with
the option to import data. When this is done in multiple tables the tables can
be joined in any way the user sees fit. With this option larger schemas can be
used. Unlike quicker visualization tools Tableau can handle large data sets. Once
loaded the data source view shows the data in a column and row view where
the user can refine the data types and columns that will be needed for
visualization creation. Once the load is completed Tableau becomes a click and
drag interface with a UI that is easy to operate. By simply dragging data from
the dock on the left onto the canvas Tableau can begin to try and interpret the
type of chart the user is trying to create. If Tableau chooses incorrectly the user
can select from many different options.
Tableau

5. • When considering data visualization tools Tableau both delivers the ease of
design but also the ability to derive data from inside the software. This ease of
use transfers well to the syntax used in Tableau and it is its own version of a
standard development language. Simple syntax helps the user be able to create
and extrapolate on the data that the user has imported. Tableau gives the user
the ability to create these derived columns but also manipulate them with
measures and switch statements. All of these options make Tableau incredibly
flexible, especially for a power user. To be able to write proprietary filters and
create calculations that are not originally in the data inside of the visualization
tool is a very important feature included in Tableau. Most other visualization
software is not as user friendly when developing.
• Tableau is also set apart in its geographical abilities. With Esri mapping software
plugins Tableau now has one of the leaders in GIS software inside of its
analytical visualization tool. This pairing can help create maps easily without any
experience needed. Geographical data can be mapped easily because of
Tableau’s built in catalogue of mapping knowledge. Zip codes and Cities are
already there to be used in filled maps and heat maps.
Tableau

6. • Tableau in case studies on helping with management is considered a
logical next step from standard visualizations like ones available in
MacroSoft's Excel. (3) The ability to create visualizations without the need
for programming is a great strength of Tableau.
• Salesforce is a large CRM software company. Its recent acquisition of
Tableau it has created a greater market for Tableau. Having the link
between Tableau and Salesforce data will make visualizations for
businesses of that are already employing Tableau even easier. Salesforce is
in use in all business sizes and types and this makes Tableau even easier
to begin creating visualizations. A connection between the two will make
Tableau the choice of those already using Salesforce and create a
workflow between the two platforms so that the visualization developer
has to spend less time cleaning and transforming the data for use in
Tableau.
Tableau

7. Tableau- Sheet
Sheet
1. Data Source
2. Dimensions
3. Measures
4. Parameters
5. Filters Card
6. Marks Card
7. Columns &
Row Data
8. Visualization

8. Tableau- Dashboard
Sheet
9. Screen Type
10. Sheets
11. Objects
12. Toolbar for
Viewing
13. Dashboard
14. Filters
15.
Sheets/Dashboard
Tabs

9. Tableau- Data Connections
Data Connections
16. Data Connection
17. Tables
18. Joins
19. Data
20. Connection to
Data

10. • Google Data Studio is a web-based only data visualization tool that
allows raw data to be presented in interactive dashboards.
• It is a very recent tool- launched in 2016 and was released from
beta mode in 2018.
• Connectors to Google Data Sources- It is not only a single BI tool, it
can work with other tools from the Google Analytics Solutions data
(software suite for analyzing data)
• Allows the transformation of raw data into interactive visualizations
dashboards and has a library of built-in visual types
• It is a great tool for collaboration- can allow others to view and edit
the dashboard you are working with (the same way as other Google
tools such as Google Docs and Google Drive)
Google Data Studio
Features

11. Homepage
1. Button to create new file
2. Search bar
3. File type tabs (reports,
data sources, explorer)
4. Option icons
5. Filter file list
6. Report samples and
templates
7. File list
Google Data Studio
Features

12. Report Editor
1. Logo to return to Reports Home page
2. Menu bar
3. Embed reports, full screen, data
freshness, copy report, view/edit toggle,
google marketing platform product
switcher, google profile icon
4. Page controls
5. Undo/Redo
6. Add a chart button
7. Text, image, and shape tools
8. Data range, filter control, data controls
9. Share report button
10. Where charts will be displayed
11. Properties panel
12. Available fields panel
Google Data Studio
Features

13. Data Source editor
1. Data source name
2. Version history
3. Data source options
4. Copy
5. Create report
6. Add a field
7. Edit connection
8. Fields
9. Field type
10. Aggregation
11. Calculated fields
12.Refresh fields
13.Field count
Google Data Studio
Features

14. Google Data Studio
Chart Types
Area Charts
Bar Charts
Bullet Charts
Geo Charts

15. Google Data Studio
Chart Types
Treemaps
Other charts types include:
 combo
 scorecard
 pie
 pivot table
 tables

16. • Fully integration with other
Google products
• Simple to use
• Great collaboration
capabilities
• Not as flexible when it
comes to dashboards
interactivity
• Cannot add custom visuals
only modify the ones available
• No functionality for mixing
and blending data- the data
itself must be ready for
visualization
• There is no desktop version
of this tool
Google Data Studio
Advantages and Disadvantages

17. • Qlikview is one the most frequent used analytics tools due to its
reliability and ease-of-use.
• Combines some of the industry standard tools (artificial intelligence,
internet of things, analytics engine) for efficient data analysis.
• Qlikview’s focus is on the user as receiver of data. Maintains
association between data and retrieval of relative items.
• Is a flexible software that allows customization to the look and feel
of any visualizations and dashboards.
• Enables conduction of data cleansing operations (extract, transform,
load engine)
Qlikview

18. • Manipulation of data associations automatically- can recognized
relationship between various data items in a set without any explicit
pre-configuration work by the user.
• Useful dashboard features that allow creation of advance
dashboards based on data from multiple sources.
• Faster queries and more memory-efficient due to keeping the data
input in memory, for example keeping data input in the RAM of a
server. Quick computation of aggregation instead of querying
precomputed aggregated values.
Qlikview- Features

19. Qlikview- Features

20. Types of charts include:
 bar
 line
 combo
 scatter
 pie
 pivot table
 straight table
Qlikview- Chart Types
To add a chart in QlikView right-click on dashboard, go to new
sheet object, and click on Chart option. The window above will
appear.

21. Qlikview- Chart Types
Block Charts Scatter chart

22. • Qlikview provides prebuilt
dashboards application and
associative dashboards that are
innovative and intuitive to use.
• Provides advanced search
capabilities by pulling data in-
memory with the use of the
associative dashboards
• Dashboard and reports are
easy to navigate
• Building reports requires high
level of developer skills and
have proficiency in SQL and
Qlikview’s query language
• Pricing can be expensive
and its pricing policy can be
confusing and not
straightforward
Qlikview- Advantages
and Disadvantages

23. • Pacific Life Insurance Company- a company that offers variety of life
insurance products, annuities, mutual funds, and services for both individuals
and businesses, choose to use Qlikview due to its user-driven solution.
• Tim Shaheen, VP of strategy and shared services in Pacific Life’s Life Division, stated that
the quick turnaround is a major benefit of Qlikview:
• “We don’t wait for everything to be fully fleshed out before we start putting information and
contents in front of folk, instead we iterate through designs to get to a solution.”
• Their company wanted a BI tool that would apply agile methodology as users would
build applications, test these, and then rebuild again.
• Before using Qlikview, the company was using Excel for static reports and Microsoft SQL
Server Reporting Services to generate reports.
• One of the challenges with Qlikview was with data governance- tracking data
transformation and lineage within the files has been difficult: to help manage the issue
used software called Informatica for metadata management and have staff member
specialize in data governance
• For the future, would like to expand Qlikview’s usage to other departments such as their
Finance Department.
Qlikview Case Studies

24. • Accounting firm called Armanino also decided to use QlikView in order
to solve it’s issue with spending days pulling data from various sources
for monthly meetings.
• Created an executive dashboard with metrics such as revenue,
realization, staff utilization, effective rate per hour, and accounts
receivable aging. The firm’s users can have different permissions rights.
• The results of using Qlikview was that it enable their users to better
understand their business in a real-time basis (uptick on key metrics that
impacted profitability).
Qlikview Case Studies

25. • DataWrapper is a data visualization tool that is open source and
available on the web or can be locally installed and run.
• Unlike the larger data visualization tools in use
today DataWrapper focuses on the ease of creating a quick and
effective chart, graph, or map. The approach is one that does not
require any coding or design to create a visualization.
• While most visualization software requires knowledge of the platform
or software to create DataWrapper does not require anything from
the user. This makes DataWrapper very simple to create and publish
charts for consumption by embedding online or as a report image.
For the user who rarely needs visualizations DataWrapper would be
the most efficient option.
Datawrapper

26. • While it is possible to use live data with a locally installed version
of DataWrapper this research will focus on the most common
application of DataWrapper which is online access via the browser.
“Datawrapper, was developed for data journalism and powers
the interactive graphs in online news services.”
• Users of DataWrapper may be using data from a flat text file or csv
and need a graph very quickly and that is what DataWrapper offers.
• As cost is prohibitive of most BI platforms specifically Tableau
and PowerBI with their monthly subscription fees for
use, DataWrapper is completely free to use and publish visualizations.
These visualizations are limited but there is no concern of licensing or
publishing.
Datawrapper

27. The cost and steps that take it to create a
visualization set DataWrapper apart from the other
visualization tools because of their ease of use. No
account creation is required which makes this the
best for purposes that are quick and no need to
save the work for future changes. After the data is
uploaded then it can be cleaned and transformed if
needed. Calculated columns can be created
using JavaScript as the syntax to perform any
functions on the data such as average or sum. Then
it takes the user to the visualize phase where the
user simply adds labels, determines groups that the
data might need to be colored in and sorting. If
dates are in the data here in the visualization stage
can the user set up max and min dates. After all
steps have been taken the user proceeds to the
publish phase where an email is used to send the
embed code and an iframe is sent for the final
product to be embedded into a webpage or report.
Once this is finished the chart is hosted
by Datawrapper. This is much easier than most BI
software that requires a server or cloud subscription
to host the queried data and visualization.
Datawrapper

28. • In a use case where business dashboards with multiple visualizations and
data sets are needed DataWrapper will not be useful. It excels in producing
quick easy to understand visualizations. Charting maps is a newer feature
of DataWrapper and it allows for a more immersive ability to use
geographical data and see more than simple charts and graphs that are
available in excel. This option has helped expand DataWrapper from a
quick solution to a more full-service visualization tool while still not being a
reporting tool like Tableau, PowerBI or Google Data Studio. Mapping
however is a very good use of DataWrapper because of its ease of use. A
smaller company looking to investigate CRM data that includes geographic
data could use this to visualize their customer base and more with the
offerings that are in their newly added mapping portfolio.
Datawrapper

29. • There are very little analysis abilities in DataWrapper. The only calculations
that are possible are calculated columns written in JavaScript. This is useful
but cannot be used to help make business decisions and stakeholders can
view the charts, but the underlying information will be required to be put
through the ETL phases before it arrives at DataWrapper. This makes it less
useful for projects or users with data that can change quickly and should
be monitored. Reports should be run in another visualization tool because
each time the data is updated it will require the visualization to be rebuilt
or reloaded to be current.
• The initial abilities of DataWrapper are very similar to Google Data Studio
with its layout and its quick visualization creation. But it lacks the ability to
create multiple visualizations or filters to help users drill down into data on
a more granular level. Unlike Tableau the charts are not initially well
designed and may take some color changes and formatting to ensure that
they are visually appealing and useful for a report or end user.
Datawrapper

30. • Overall DataWrapper does not offer many options that Microsoft Excel
could offer. In a time where most computing has moved from the local
machine and into the browser DataWrapper will have some use cases. Data
wrapper also gives the user the ability to create one visual and not need an
account but also the ability to create an account if they would like to edit
visualizations later. By creating a quick visualization creator DataWrapper is
the solution for users who need visualizations for reports that are not
transactional data that changes regularly or for journalistic reasons where
the story being told is not dynamic and will only be used once.
Datawrapper

31. DataWrapper- Upload Data
Upload Data
1. Data Import
Options
2. Copy and Paste
Field

32. DataWrapper- Data
Check & Describe
3. Create Calculated
Colum
4. Review Data

33. DataWrapper- Visualize
Visualize
5. Select Chart Type
6. Select Color Scheme

34. DataWrapper- Visualize
Visualize -
Refine
7. Annotate and
Tool Tip design
8. Publish &
Embed

35. • The average DataWrapper user is one with the following needs:
• Quick Visualization Creation
• No cost to create and use
• Can be used anywhere without software
• Simple Visualizations with some interactive features like tooltip
• Embedding into website
• Historical data that will not be dynamic
• The average Tableau user is one with the following needs:
• Pre-cleaned data
• Looking for clean UI
• Easy to understand when creating new measures
• The average Qlikview user is one with the following needs:
• Is the right solution for a business if they are prepared to apply and use a software that has a
programmatic interface.
• Users of this tool must have the right question from the beginning and be willing to put extra effort in
maintaining proper reporting of data.
• Speed and efficiency in creating dashboards
• The average Google Data Studio user is one with the following needs:
• Simple to use tool
• Sharing dashboards and reports with other users for collaboration work.
Conclusion

36. Agarwal, A. (2019). Hands-on dashboard development with QlikView : Practical
guide to creating interactive and user-friendly business intelligence dashboards.
Birmingham ; Mumbai : Packt Publishing.
ALEXANDER, A. (2014). Case Studies: Business intelligence. Accounting Today,
28(6), 32. Retrieved from
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&AN=96516056&site=ehost-live&scope=site
Bobriakov, I. (2018). A Comparative Analysis of Top 6 BI and Data Visualization
Tools in 2018. Medium. Retrieved from https://medium.com/activewizards-
machine-learning-company/a-comparative-analysis-of-top-6-bi-and-data-
visualization-tools-in-2018-658490665973
Briggs, L. (2015). BI Case Study. Business Intelligence Journal, 20(1), 30–32.
Retrieved from
http://search.ebscohost.com.proxy.kennesaw.edu/login.aspx?direct=true&db=bth
&AN=101605387&site=eds-live&scope=site
References

37. Chart References. Data Studio Help. Google Support. Retrieved from
https://support.google.com/datastudio/topic/7059081
Ertug, G., Gruber, M., Nyberg, A., & Steensma, H. K. (2018). From the Editors-A Brief
Primer on Data Visualization Opportunities in Management Research. Academy of
Management Journal, 61(5), 1613–1625. https://doi-
org.proxy.kennesaw.edu/10.5465/amj.2018.4005
Find your way around. Data Studio Help. Google Support. Retrieved from
https://support.google.com/datastudio/?hl=en#topic=6267740
Lisa Maria Perkhofer, Peter Hofer, Conny Walchshofer, Thomas Plank, & Hans-
Christian Jetter. (2019). Interactive visualization of big data in the field of accounting :
A survey of current practice and potential barriers for adoption. Journal of Applied
Accounting Research, 20(4), 497–525. https://doi-
org.proxy.kennesaw.edu/10.1108/JAAR-10-2017-0114
MACPHERSON, S. (2019). CHOOSING THE RIGHT BUSINESS INSIGHT TOOLS:
Business intelligence and data visualisation tools make translating complex financial
information into something useful for stakeholders a much easier task. Acuity, 6(5),
50–53.
http://search.ebscohost.com.proxy.kennesaw.edu/login.aspx?direct=true&db=bth&A
N=138905569&site=eds-live&scope=site
References

38. Resource/Reading List
• Tableau:
• Learning Tableau 2019: Tools for Business Intelligence, data prep, and visual
analytics, 3rd Edition by Joshua N. Milligan
• Visual Analytics with Tableau by Alexander Loth
• https://playfairdata.com/blog/ Design and Tableau Information
• https://www.tableau.com/community Forum and Walkthroughs
• Google Data Studio:
• Report Gallery: https://datastudio.google.com/gallery
• Google Analytics YouTube channel playlist:
https://www.youtube.com/watch?v=6FTUpceqWnc&list=PLI5YfMzCfRtag7tB
fbVvA4_a6YZxWHEO4
• Blog post: An overview of all Google Data Studio Chart types in 2019 by
Michael Howe-Ely https://michaelhoweely.com/2019/04/14/an-overview-of-
all-google-data-studio-chart-types-in-2019/

39. Resource/Reading List
• Qlikview:
• QlikView Essentials by Chandraish Sinha
• For other books see article: Best books for Qlikview Learning
https://medium.com/@bansalhimani136/best-books-for-qlikview-learning-
451d5a715e1e
• Qlikview help guide: https://help.qlik.com/en-
US/qlikview/April2019/Content/QV_HelpSites/Home.htm
• DataWrapper:
• DataWrapper’s blog: https://blog.datawrapper.de/
• Thoughts & How to do’s category: https://blog.datawrapper.de/category/thoughts-how-
to-s/

40. Appendix
Google Data Studio Qlikview Tableau DataWrapper
Importing File type MySQL, Google
Sheets, CVS,
BigQuery
Excel, SQL CSV, Excel, Copy and Paste,
XLS, CSV, Google
Sheet, Link External
Dataset
Publishing Style Reports,
Dashboards
Reports,
Dashboards
Dashboard Single Visualization
Live Yes Yes Yes No
Data Manipulation
Language
Javascript SQL Proprietary Javascript

41. Appendix
• Offered Natively
— Can be Developed
Legend
Chart Type Google Data
Studio
Qlikview Tableau DataWrapper
Bar Chart • • • •
Split Bars • • • •
Stacked Bars • • • •
Grouped Bars • • • •
Bullet Bars • • •
Dot Plot • •
Range Plot — •
Arrow Plot — •
Column Chart • • • •
Grouped Column Chart • • • •
Stacked Column Chart • • • •
Area Chart • • • •

42. Appendix
Chart Type Google Data
Studio
Qlikview Tableau DataWrapper
Line Chart • • • •
Pie Chart • • — •
Donut Chart • • — •
Multiple Pies • • — •
Multiple Donuts • • — •
Scatter Plot • • — •
Election Donut • — •
Table • • — •
Heat Maps • • •
Highlight tables •
Packed Bubbles •
Gantt Chart — •
Circle View •
Maps • — • •
Symbol Maps — • •
Legend • Offered Natively
— Can be Developed

43. Thank You