The Eastasouth Journal of Information System and Computer Science
Vol. 01, No. 01, August, pp. 55 - 59
Journal homepage
: https://esj.eastasouth-institute.com/index.php/esiscs
Comparative Analysis of Data Visualization Tools: Tableau, Power
BI & Looker
Dip Bharatbhai Patel
University of North America
Article Info
ABSTRACT
Article history:
Received Aug, 2023
Revised Aug, 2023
Accepted Aug, 2023
Data visualization tools are now becoming common due to the
usability and function that they offer in different sectors. We are in the
era of big data, which means that the usability that is needed for data
visualization to work on the data is growing. Data is a growing part of
our lives as there comes the need for understanding, analyzing,
visualizing, and being able to use the data, which is key to how it is
being used in various sectors.
Keywords:
Data Visualization
Looker
Power BI
Tableau
This is an open access article under the
CC BY-SA
license.
Corresponding Author:
Name: Dip Bharatbhai Patel
Institution: University of North America, Virginia, United States of America
Email:
dbpatel9897@gmail.com
1.
INTRODUCTION
The growth of big data is bringing
more focus to the rise of data visualization
tools. The paper provides a comparative
analysis of the three tools, Tableau, Power BI,
and Looker, which are the three tools of focus
of this paper. These tools are common and can
make data analysis seem like a simple
method. Data visualization tools make
everything
a
success
in
terms
of
understanding different aspects of how to
handle data and what benefits that can come
out of the data [1]
.
With these three tools to discuss, it
offers so much insights to what data
visualization
can
offer
different
users
depending on the tools that they decide to use.
The paper provides more information in how
the three tools to be discussed compares to
each other down with the pros and cons of
each.
2.
Comparative Analysis Of Data
Visualization
Tools:
Tableau,
Power Bi & Looker
In order to make the right distinction
and comparison between the three tools, it
would be easier to compare the three tools
based on different aspects: ease of use, data
connectivity,
visualization
capabilities,
collaboration and sharing, and then, finally,
customization and extensibility.
2.1
Ease of Use
a)
Tableau:
Tableau can be said to be
more of a drag-and-drop, which
adds more functionality to how it
can be used. It makes everything
easier to use and gives its users
the
ability
to
accommodate
power users within the scripting
options. Tableau basics are easy
to understand, and the tool can
even be used for different basic
analyses for data options [2]
.
At
The Eastasouth Journal of Information System and Computer Science (ESISCS)
Vol. 01, No. 01, August, pp. 55 - 59
56
the same time, its advanced
analytics part would need more
knowledge and skills on the LOD
functions, which requires more
advanced analysis skills and
knowledge to make everything
work.
b)
Looker:
Looker is well known for
its user-friendly interface. With
this approach, it makes it possible
to appeal to beginners and even
technical users. Looker offers
more ability to create simple and
good
reports,
including
dashboards, which is good for
user content creation. A user can
also analyze and visualize data
within the tool; knowledge and
training
in
data
modelling
concepts could be required to get
seamless and quality results. In
order for a user to do complicated
and advanced work like building
queries,
reports,
and
even
models, it could require reliance
on experts on the tool for them to
find results and work [3]
.
c)
Power BI:
with this tool, users are
able to get a better experience and
integration for Microsoft-centred
organizations,
with
the
tool
offering better usability with so
many Microsoft products. Power
BI offers a user-friendly interface
that also provides drag-and-drop
functionalities. In this way, users
are
able
to
create
reports,
dashboards
and
clear
visualizations without having
expertise in the tool. Power BI
offers more capabilities with the
Power Query Editor, including
the Pivot functionalities, which
would offer more ways of data
visualization
from
cleaning,
manipulating and transforming
data in different capabilities.
2.2
Visualization Capabilities
a)
Power BI:
this tool is so capable
within
the
visualization
capabilities with more expertise
on having a huge range of
extensive
customization
and
visual capability. Power BI is
capable
of
offering
more
visualization options to offer
more specifications for the tools
that it would offer. Compared to
the others, it is more competitive
with tools like matrices, maps,
charts, and even tree maps, which
have other specialized visual
functionalities. Power BI also
offers
Q&A,
which
enables
asking
questions
in
natural
language and then offers the
generation
of
visualizations
based on queries provided.
b)
Looker:
Looker offers a wide
array of visualization functions
from charts to graphs and even
specialized
visualizations
like
box plots, tree maps, heat maps,
and so much more. It is not so
much into data visualization
capabilities as it is limited and
lacks
advanced
customized
features. Looker also offers more
interactivity
and
more
capabilities
like
drill-down
abilities. It also allows users to
explore data using a hierarchy
based on filters and parameters
that users can set.
c)
Tableau:
Tableau is well known
for its rich visualizations. Users
are able to create better, intricate
and
interactive
reports
and
dashboards,
making
it
the
supreme tool for visualization.
Tableau offers more functions
with drag-and-drop interfaces for
building
better
visualization
capabilities.
It
also
brings
functionality by enabling the use
of storytelling to be a key towards
creating data visualizations with
more options surrounding the
interaction as the main stage. It
adds
more
interactive
dashboards for the users to take
advantage of to guide what
The Eastasouth Journal of Information System and Computer Science (ESISCS)
Vol. 01, No. 01, August, pp. 55 - 59
57
would work with better insights
and narratives, making the tool
better to use in creating intuitive
visualizations [4]
.
2.3
Data Connectivity
a)
Looker:
Looker excels at this
capability
by
offering
more
functions
within
the
data
transformation and modelling as
the cornerstone of the tool. It
offers users the ability to support
different data sources, which is a
good one as there are so many
sources of data. Looker also offers
support for data connections,
which can include traditional
SQL databases like Oracle, SQL
server and even MySQL. Users
can also integrate with other
modern data warehouses like
Snowflake,
Amazon
Redshift,
and even Google Big Query.
Looker is also capable of enabling
direct connection to the data
sources, which can also enable
data extraction capabilities.
b)
Tableau:
Tableau is capable of
offering more connections to
handling large datasets easily
with no problem. It is also
capable
of
connecting
data
sources
from
traditional
databases like Oracle down with
cloud-based
warehouses
like
Snowflake and Google BigQuery.
Tableau
is
also
capable
of
supporting live connections and
data extraction, which is key to its
usability options.
c)
Power BI:
This tool is versatile
and has many functions, such as
connecting
to
data
sources
through the integration of Azure
services [5]
.
Power BI offers more
connectivity by offering a huge
range of data sources, with its
best seamless integration with
Microsoft products like Excel,
cloud services like Salesforce, and
even
other
databases
like
PostgreSQL.
With
these
integrations, Power BI becomes a
shining tool when it is used with
Microsoft products and tools.
Power BI also offers direct query
connections to various sources,
including
the
import
and
transformation of data extracted.
2.4
Customization And Extensibility
a)
Tableau:
Tableau is very much
focused on customization for
users based on their work and
preferences. The tool also offers
support for the scripts to offer
more functions, which makes it
ideal for complex queries and
visualization work. Users get
better customization with the
ability to play with different
tools, from labels, colours, and
even formatting based on their
preferences.
Tableau
offers
support extensions for better
custom visualization, making the
tool the best in terms of the
functionalities and customization
that it would bring to users.
b)
Looker:
looker is limited in its
ability
to
offer
complex
customization for the preferences
that users would require. It
cannot integrate custom code or
plugins for user customization
options. At the same time, users
would put more emphasis on
better customization efforts by
offering LookML. Looker offers
users the ability to define their
data models, customize data
visualizations, add custom logic
for business and even create
reusable definitions.
c)
Power BI:
This tool is capable of
offering
support
for
custom
visuals,
which
adds
to
its
integration with Azure services.
This
integration
offers
more
extensions
in
terms
of
functionality opportunities that it
would add to the specific choices
used. Users using this tool would
add more creation of custom
The Eastasouth Journal of Information System and Computer Science (ESISCS)
Vol. 01, No. 01, August, pp. 55 - 59
58
visuals through Visual SDK. This
tool would bring more functions
for
building
and integrating
custom visualizations through
the reports and dashboards [6]
.
2.5
Collaboration And Sharing
a)
Power BI:
Power BI is a simplified
tool that offers more capable
services that would integrate
with other Microsoft tools for
better
collaboration.
Better
collaboration
with
Microsoft
products and SharePoint offers
more sharing options than other
tools. Users are able to get role-
based access control systems,
which is key for managing
collaboration
and
sharing
depending on managing user
roles and access permissions. It
also allows users to create app
workspaces, including sharing
reports and dashboards, which is
good for a centralized location for
the users.
b)
Tableau:
this tool is robust in
terms
of
offering
better
collaboration features for users.
This ability allows users to
publish reports to the Tableau
server for sharing, which is good
for
collaboration.
Tableau
is
capable of a content management
system
that
enables
better
organization of files or content
that
should
be
shared
and
categorized.
c)
Looker:
Looker excels in this
aspect. Users get the ability to
facilitate
reporting
and
a
dashboard, which is key for
platform sharing and is a good
tool for collaboration. Users have
control over permissions, user
roles,
and
access.
Better
collaboration offers users access
to
the
same
dataset
while
reducing
issues
in
data
interpretation [7]
.
3.
CONCLUSION
With so many comparisons between
the three tools, it adds more details to decide
on which tool one can choose, depending on
which aspect is important for their work.
These three tools are capable of making data
visualization work easier based on queries
and types [8]
.
The
tool
that
offers
so
much
capability would be tableau that I can choose
given that it almost does everything as
compared to the other depending on context
and application that it offers. It would be the
best for what one would choose as it does
everything which shows how it can be the best
tool for use to show how data visualization
works and its benefits.
ACKNOWLEDGEMENTS
I would like to express my sincere
appreciation to my peers and tutors for the
coursework on data visualization. More
thanks go to the research team and peer-
reviewed
authors
for
their
invaluable
information and articles that made up the
basis for this paper. Thank You.
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