Ashwin Patel

Data Visualization Using Tableau

Metropolia University of Applied Sciences

Master of Engineering

Information Technology

Master’s Thesis

27 December 2021
PREFACE

This is one of the most important articles I've ever written in my amazing college life.
My education at Metropolia University of Applied Science will come to an end with
this piece of paper and a Master of Engineering degree in Information Technology.

First and foremost, I want to thank my coach (Ville Jääskeläinen) at Metropolia UAS
for his encouragement, talks, comments, and guidance in the writing of this thesis.
Unfortunately, owing to the COVID-19 virus, I was not always able to attend college,
but he was very generous in helping me write my thesis and gain experience for my
first thesis.

Second, I want to express my gratitude to my Indian friends and fellow Master of

Engineering students for the stimulating discussions, as well as all of the hours spent
on online and different discussions. More particularly, after the remarkable COVID-19
virus, for all the fun we've had in the last year.

Finally, I'd like to express my gratitude to my parents (Manilal and Maya) and
grandparents for allowing me to participate in this incredible educational and social
journey. Finally, I want to express my gratitude for my sister's unwavering support
(Vandana).

Espoo, 27/12/2021
Ashwin Patel
Abstract

Author: Ashwin Patel

Title: Data visualization using Tableau
Number of Pages: 80 pages
Date: 27 December 2021

Degree: Master of Engineering

Degree Programme: Information Technology
Professional Major: Information Technology
Supervisors: Ville Jääskeläinen (Principal Lecturer)

A graphical depiction of information and data is known as data visualization. Data

visualization tools, which include visual aids such as charts, graphs, and maps, give
an easy method to observe and analyze data styles, outliers, and trends.

The goal of this thesis was to study different visualization methods, understand the
various tools, and compare Tableau and Excel tools.

The data given contains information about daily historical stock prices. The dataset
contains index values of different business segments from the years 2016 to 2021.
Using this historical data, this study found out the returns based on calculations in
Excel sheet and then using these returns, it showed the results with different
visualisation methods in Tableau.

At the end of the study, main differences between Excel and Tableau are listed.

Keywords: visualization, charts, Tableau, Excel

Contents

List of Abbreviations
1 Introduction 1

2 Method and Material 4

3 Data Visualization 7

3.1 Overview of Data Analytics 7

3.2 Overview of Business Analytics 9

3.3 Types of Graphs and Charts 10

4 Visualization Tools 28

4.1 Tableau 28

Derived Chart 32

Importing Data 33

Dashboard Creation 36

4.2 Power BI 39

4.3 Cognos 41

4.4 Qlik view 44

4.5 SAP Analytics 46

4.6 Excel 50

5 Results and Analysis 51

5.1 Case Study Description 51

5.2 Sources Of Data 53

5.2.1 Data Based On Selected BSE Indices 56

5.2.2 Description of Data 57

5.3 Data Analysis 58

6 Recommendations and Conclusions 77

List of Abbreviations

BI Business intelligence

BRICS Brazil, Russia, China and South Africa

BSE Bombay Stock Exchange

BW Business Warehouse

CDSL Central Depository Services Ltd

ERP Enterprise Resource Planning

FMCG Fast-moving consumer goods

INX International Exchange Limited

IT Information Technology

PDF Portable Document Format

RBI Reserve Bank of India

SaaS Software as a service

SAP Systems Applications and Products in Data Processing.

XML Extensible Markup Language

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1 Introduction

As the "Big Data Age" begins in high gearIn the big data era the collection of
data has become simple and cost-effective, and visualization and related tools
have become increasingly important for making sense of the billions of lines of
data generated on a daily basis. Data visualization helps to tell stories by
presenting data in an easy-to-understand way, highlighting trends and other
important properties. Good visualization tells a story, removes noise from data,
and highlights useful details.

Data visualization is a graphical representation of information and data. By

using visual aids such as charts, graphs, and maps, data visualization tools
provide an accessible way to see and understand styles, outliers, and patterns
in data. In the Big Data world, data viewing tools and technologies are essential
for analysing large amounts of information and making data-driven decisions. A
simple graph can be very tedious to capture any notification or make a strong
point and excellent vision can completely fail to convey the right message or
can say too much. Data and visuals require interaction, and the art is to
combine good analysis with a story.

When one thinks about data visualization, one may first think just simple graphs
or charts. While this can be an important part of visualizing data and a common
basis for many data drawings, good visualization should be paired with the right
set of information. Simple graphs are simply the tip of the iceberg. There is a
complete selection of ways to visualize and present data in an effective and
attractive way. Common types of data visualization are charts, tables, graphs,
maps, info graphics, and dashboards.
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There are multiple data visualization tools available. In the strictest sense,
Microsoft Excel is a spreadsheet software, not a data visualization tool. Even
so, it has useful data visualization capabilities. Given that Microsoft products are
widely used at the enterprise level, one typically have access to it. Zoho
Analytics is a data visualization tool specifically designed for professionals
looking to visualize business intelligence related data. As such, it’s most
commonly used to visualize information related to sales, marketing, profit,
revenues, costs, and pipelines with user-friendly dashboards.

Tableau is often regarded as the grand master of data visualization software

and for a good reason. Tableau has a very large customer base of 57,000+
accounts across many industries due to its simplicity of use and ability to
produce interactive visualizations far beyond those provided by general BI
solutions. Qlik with their QlikView tool is the other major player in this space and
Tableau’s biggest competitor. The vendor has over 40,000 customer accounts
across over 100 countries, and those that use it frequently cite its highly
customizable setup and includes a wide feature range as a key advantage.

At this time, the most widely used tool for data analysis and visualization is
Tableau. Tableau is software that can help users to explore and comprehend
their data by creating interactive visuals. The software has advantages that can
be used in conjunction with almost any database, and is easy to use by
dragging and dropping to create interactive visuals that display the format one
needs. Tableau is a tool supporting complex visualization methods and
simplifying complex data.

The research problem of this study is to understand challenges related to data

visualization. The challenges are demonstrated by analyzing data of the impact
of demonetization, made at 2016 in India, on sectorial indices at Bombay Stock
Exchange Ltd. For this study, the calculation of selected indices were analyzed
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based on the return in the last 5 years that is after demonetization. For the
calculations, MS Excel was used and for the visualization Tableau was be used.

Objectives

The main aim of the thesis is to identify an effective visualization method for
representing the unstructured data into meaningful information.

● The study is conducted to know about different visualization methods.

● To understand the various tools used for data visualization.
● To assess the proposed visualization tool & provide recommendations.
● Do a comparison of Tableau and MS Excel.

The thesis has been divided into 6 sections. The first section introduces the
problem statement and information about the overall data visualization tools.
The second section gives ideas about method and material. The third section
includes data analytics, business analytics and charts. The fourth section is
about theory information related to the visualization tools. The fifth section gives
ideas about visualization of calculated data of the selected indices using
Tableau software. The last section will be focused on the output of
implementation.
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2 Method and Material

This thesis mainly consists of two parts: theoretical and practical. The
theoretical part is based on literature review that provides understanding about
numerous data visualization methods. It also includes analysis of the current
market of visualization tools and provides understanding about widely used top
applications. The practical part is about utilizing the learned topics and
implementing them in the best possible manner. The tool used for the purpose
of analysis is Tableau.

The analysis provides information about the advantages of applications and

difficulties in using them. It also describes the steps for creating the design of
the dashboard as well as the suitable interactive visualizations of the specific
data using Tableau.

Data Used for Visualization Analysis

Five years ago, Prime Minister Narendra Modi appeared on national television
and said that all Rs 500, Rs 1,000 high value notes will turn invalid by midnight.
The announcement at 8 pm, aimed at flushing out money hidden from the
taxman, known as black money, led to nearly 86 percent of the currency in
circulation becoming invalid by midnight.

Expectedly, mayhem followed. The move, known as demonetization, caused a

lot of hardship for many people who were forced to form serpentine queues in
front of banks to exchange notes. Several small businesses that were
dependent on cash took hard knocks. There were three main economic
objectives of demonetization: fighting against black money, fake notes and
creating a cashless economy by pushing digital transactions.
 5

In 2016, the year when demonetisation was launched, 6,32,000 counterfeit

notes were seized across the country. In the next four years (including the year
2020 so far), a total of 18,87,000 fake notes have been seized across the
country in various denominations, according to the RBI (Reserve Bank of India)
data.

A significant negative impact of demonetization on stock market returns was

evidenced from Nifty 50 Index and sectoral indices such as Nifty Auto Index,
Nifty Financial Services Index, Nifty FMCG Index, Nifty IT Index, Nifty Media
Index, Nifty Private Bank Index, and Nifty Realty Index.

Founded in 1875, Bombay Stock Exchange Ltd. (BSE), is the fastest stock
exchange in the world which has a median trade speed of 6 microseconds. It
provides an efficient, integrated, transparent and secure market for trading in
equity, currencies, debt instruments, derivatives, and mutual funds. It provides
an array of services such clearing, settlement, risk management, education and
market data services. It has a global reach with overseas customers and a
nation-wide presence. It provides depository services through its Central
Depository Services Ltd. (CDSL) arm. The S&P BSE SENSEX is India’s most
widely tracked stock market benchmark index. It is traded internationally on the
EUREX as well as leading exchanges of the BRICS nations (Brazil, Russia,
China and South Africa).

A stock market index is a statistical measure which shows changes taking place
in the stock market. To create an index, a few similar kinds of stocks are chosen
from amongst the securities already listed on the exchange and grouped
together. The criteria of stock selection could be the type of industry, market
capitalization or the size of the company. The value of the stock market index is
computed using values of the underlying stocks. Any change taking place in the
underlying stock prices impact the overall value of the index. If the prices of
most of the underlying securities rise, then the index will rise and vice-versa.
The data required for the analysis is available on the stock exchange portal as
 6

open source to be accessed by anyone globally. The more details about the
data is mentioned in section 5.
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3 Data Visualization

This section gives first an overview of data analytics and business analytics and
then different charts and graph used for the data analysis are presented.

3.1 Overview of Data Analytics

Data analysis is the science of raw data analysis to make conclusions about
that information. Many data analysis techniques and processes are
automatically developed into machine processes and algorithms that work with
raw data for human use. Data analysis helps a business to improve its
performance.

Data analytics is a broad term that encompasses many different types of data
analysis. Any type of information can be viewed with data analysis techniques
to gain insight that can be used to improve things. Data analysis techniques can
reveal styles and metrics that would be lost in the bulk of the information. This
information can be used to add processes to increase the effectiveness of a
business or program.

For example, manufacturing companies often record the operating time,

downtime, and lines of operation of various machines and then analyze the data
to increase the productivity. Data statistics is important because it helps
businesses increase their performance. Applying it to a business model means
that companies can help to reduce costs by identifying more efficient ways of
doing business and generate more revenue. The company can also use data
analytics to make better business decisions and help to analyze customer
behaviour and satisfaction, which can lead to new and better products and
services.
 8

The process involved in data analysis includes several different steps. The first
step is to determine what kind of data is needed and how the data can be
collected. The second step in data analytics is the process of collecting it. This
can be done through a variety of sources such as computers, online sources,
cameras and various other sensors, environmental sources, or by staff. Once
the data has been collected, it needs to be edited (preprocessed) for analysis.
Editing may take place in a spreadsheet or other type of software that can
capture statistical data. The data is then cleaned before analysis to ensure that
there is no duplications or other errors

Types of Data Analytics

Data statistics can be divided into four basic categories.

Descriptive analytics describe what happened over a period of time. Has the
number of ideas increased? Are sales stronger this month than last?

Diagnostic analytics focus on why something happened. This includes a

variety of data entry and a bit of speculation. Has the weather affected the sales
of beer? Has that recent marketing campaign contributed to sales?

Predictive analytics are likely to occur in the near future. Predictive analytics
makes predictions about future outcomes using historical data.

Data analysis is a complicated process which includes various data formats and
modifications of the formats, tools and mathematical models.

The patterns and trends become more understandable when information is

presented graphically and it helps businesses to identify the right priorities and
focus on them (The Data Visualization Catalogue, 2020).
 9

3.2 Overview of Business Analytics

Business Analytics is the process by which businesses use different

technologies and skills to analyse historical data in order to gain new insights
and to improve strategic decision-making. Business analytics uses methods
such as data mining, forecasting statistics, and statistical analysis to convert
data into useful information, identify and anticipate trends and results, and
ultimately make wise business decisions driven by data.

Key elements in the standard business analytics dashboard include:

Data aggregation: prior to analysis, data must first be collected, organized, and
sorted.

Data mining: digging data for business statistics using big data sets, statistics,
and machine learning to identify trends and build relationships.

Association and Sequence Identification: identification of unexpected actions

performed in conjunction with other actions or sequences.

Text Mining: scans and organizes large, informal data sets for quality and
quantity analysis.

Forecasting: analyzes historical data from time to time to make informed

predictable estimates of future events or behaviour.

Optimization: once trends have been identified and forecasts have been
created, businesses can engage in simulation strategies to test the best
conditions.
 10

Data Visualization: provides visual presentations such as charts and graphs

for easy and fast data analysis.

Modern, state-of-the-art software analytics software and platforms have been

developed to capture and process large data sets that businesses encounter
and can be used for efficient business operations. Business analytics and data
mining systems are software applications that provide business users tools for
analyzing fixed, structured data. One of the main advantages of such programs
are the availability of visual and analytical data tools for multiple users [1].

3.3 Types of Graphs and Charts

Graphs and charts covering large amounts of data can be edited into
easy-to-understand formats to present clearly and effectively the main points of
the data. When choosing the best way to present the data, one should think
about it the purpose of the graph or chart and what one wants to introduce, and
then decide how it should be presented.

Figure 1: Visual perception in terms of accuracy.

 11

In above Figure 1, visual perception in terms of accuracy is presented. The line

indicates the less accurate types of charts at the right side of a picture and more
accurate types of charts at the left side of the picture. For example, visual acuity
clarifies eyesight and can be measured by the ability to recognize letters or
number based on standard eye chart from a specific distance. A dimension
represents categorical data such as year, salary range, product and country.

A few simple steps make the chart less congested:

● Value labels (percent written above bars) add clarity.

● The title uses direct language; "Internal smoking control workshops" are
less understandable than "Workplace smoking restrictions."
● Grid lines add depth and size, which helps readers to see the differences
between each data bar.
● Although the y-axis data label may seem unwanted, it ensures that
readers know what the values mean.

Line chart

​Line charts represent a group of data points joined together by a straight line.
Each of these data points describes the relationship between the horizontal and
the vertical axis on the graph. The Y-axis shows the numeric value and X-axis
shows the key measurements or time dimensions such as month, quarter or
year [2]. Line and area charts are typically used for representing the trends such
as data over a certain time period or temporal patterns and correlation.
 12

Figure 2: Sample of line chart (Source: www.excel-easy.com)

Typical features of a line chart:

● It helps studying data trends over a period of time.

● Easy to read and plot.
● It can be used to visualize data over both short and long period of time.

Area chart

Area charts are used to collectively measure data trends over a period of time
by colouring the area between the line segment and the x-axis. In simpler
terms, an area chart is an extension of the line chart.
 13

Figure 3: Sample of Area chart (Source: www.displayr.com)

Typical features of Area Chart:

● It is visually appealing.
● It gives a clear comparison of different groups of data.

● It may be difficult to read when compared to other data types.

Column line chart

The column line chart is a combination of line chart as well as column chart.
This type of chart indicates one measure as a column and another as a line.
These two measures are showed under the time dimensions such as months,
quarters and years. This chart is more suitable for indicating relationship
between two measures over a period of time. For example, gross margin, net
income, and sales revenue [3].
 14

Figure 4: Sample of the column line chart (Source: www.microsoft.com)

In Figure 4, there is a chart that represents the number of units sold along with
the total transactions line.

The column line charts are typically used for describing trends, data over time,
temporal pattern and correlation, for displaying two different data sets together
and for displaying the sets of same type of data which have very wide ranges
between them.

Implementation suggestions:

1. Use column line chart to display two trends of different types over a certain
period of time. For example, returning customers and sold items.

2. This type of chart can also be used to indicate the changes over a certain
time period.

Bar chart
 15

Bar charts are often used to show comparisons and are easy to create. Note
that footnotes shown in Figure 5 are defined in the same way in these two
studies, making the findings similar in the youth population, the findings could
not be compared. The Figure 5 below just an example of bar chart.

Figure 5: Sample of Bar chart (Source: www.istockphoto.com)

Bar chart is the most frequently used chart among other chart types. Bar charts
are majorly used for following [4]:

● Positioning the data from largest to smallest and vice versa.

● Filtering the data which is not important for the message.
● For grouping data.

Bar chart is usually used for comparing different values of categorical data
which includes grouping the data by combining values in a chart. If there are
 16

various categories available, then the less relevant categorical values should be
grouped into another group.

Stacked area chart

Stacked area chart is an extension of the base area chart. The values of each
group are displayed on top of each other, which allows one to see from the
same picture both the total of a numeric variable and the significance of each
group.

The lines can be drawn, for instance, to track the change in population of
various states across a particular time period. The area below each line can be
coloured with different colours in order to represent the state it depicts, resulting
in a graph which represents trends of population and shows data of each state
in order from least to most populous state [5].

Figure 6: Sample of Stacked chart (Source: www.data-to-viz.com)

 17

The Figure 6 illustrates the emergence of baby names in the US between 1880
and 2015.

Horizontal chart

Figure 7: Sample of Horizontal bar chart (Source: www.alamy.com)

Horizontal bar chart is often the best graphical tool for representing
comparisons between categories of data. The presenter can show large data
labels easily with the help of horizontal bar chart as the horizontal rectangles
have enough room for displaying textual information. The example above shows
the revenue data of clothing, equipment, and accessories of different
companies.

Waterfall chart

A waterfall chart is a way of seeing data that helps to understand the effect of
aggregation of positive or negative values. These intermediate values can be
time-based or phase-based. The waterfall chart is also known as the flying brick
chart or Mario chart due to the apparent formation of columns (bricks) in the
 18

middle of the air. Usually in finance, it is called a bridge. This type of a chart is
useful for visualizing the fluctuation in values in terms of positive and negative
values [6].

Figure 8: Sample of Waterfall chart (Source: en.m.wikipedia.org)

More information can be added to the waterfall charts by including many

complete columns and axis crossing values. Additions and decreases in
sufficient quantities may cause the accumulated value to fall above and below
the axis in various locations. Middle footnotes, shown in full columns, can be
added to the graph between floating columns. In Figure 8, the net cash flow is
indicated along with each month. Waterfall charts are typically used for
demonstrate how an initial value is increased and lowered by a sequence of
intermediate values to yield a final result.

Trellis Layout of Multiple Charts

A Trellis chart (also called multiple small charts) is a series of similar graphs or
charts that use the same scale and axes, allowing them to be easily compared.
 19

This chart shows the same chart grid of values of different sizes and can be
used to compare metrics for different data groups.

Figure 9: Trellis layout of Multiple Charts sample (Source: www.linkedin.com)

These types of charts are used for:

● Finding out patterns across multiple categorical values.

● For comparing values within a category. For example, to display the
sales values for each category in a different or separate chart.

Part-to-whole chart

This type of chart is used for a Part-to-Whole relationship which indicates how
to measure values that form the whole of something. For example, number of
containers sold as compared to one another and how the each container
compare itself with the whole.
 20

Figure 10: Part-to-whole chart sample (Source: www.anychart.com)

The Pie or Ring chart

If one tries to figure out the percentage structure of the value, the first type of
chart that often comes to mind is the Pie chart. These charts visualize the whole
structure as a circle (100%) and its parts as "pieces" related to their size.

Pie, Ring and Funnel Charts (presented next) are used for comparisons to
either give importance to a certain portion of the data or to examine values of
certain categorical values. It is suggested to not include many segments in this
type of charts because the viewer may face problem while distinguishing
objects between numerous different colours [7].
 21

Figure 11: Sample of the Pie chart (Source: www.statisticshowto.com)

Figure 11 indicates the example of sales by channel. The pie chart can easily,
quickly, and effectively forecast numerous population segments and It can also
provide responses to questions related to market-research as compared to ring
and funnel charts [8].

Funnel chart

When one checks out a process stages that start at 100% and end with a
smaller percentage, to see the steps, and to point out the problems (the decline
in which the stages occur and how much), one may like the Funnel chart type.
 22

Figure 12: Sample of Funnel chart (Source: https://charito.com)

The Figure 12 shows conversion of website visitors into paying customers.

Box plot chart

In descriptive statistics, the structure of a box or boxplot is a way of clearly

showing groups of numerical data by their quartiles. Box sites can have lines
from boxes (beards) showing distinction except for the upper and lower
quartiles, hence the names of the box-and-whisker box and the box-beard
drawing. Outliers can be constructed as individual points.

The Figure 13 illustrates how to create box plot chart. Apart from this, the
parameters of labels are used to give x-tick (x-axis) labels for every sample [9].
 23

Figure 13: Sample of Box Plot of data from the Michelson–Morley experiment
(Source: en.m.wikipeadia.org)

The box plot chart is mostly used for:

● Comparison - Box plot chart compares data distribution for numerous

categorical values.
● Distribution of values - The box plot chart indicates the distribution of
values in data.
● Identifying outliers - Box plot adds a reference line to the overall median
in data.

Scatter chart

The scatter plot (scatter chart, scatter graph) uses dots to represent the
numbers of different numeric variables. The position of each dot indicates the
values of each data point. Scatter plots are used to view relationships between
variables.
 24

An example of scatter plot Figure 14 shows the width and length of the sample
of the felled trees. Each dot represents one tree; the horizontal position of each
point indicates the width of the tree (in inches) and the vertical position indicates
the height of the tree (in meters). From the structure, we can see a good solid
positive connection generally between the width of the tree and its height. We
can also see the outer point, a tree that is much larger than the others. The tree
appears to be too short for its height, which may ensure further investigation.
Scatter plot chart indicates scatter plots in a Trellis layout with a view to
compare various scatter plots in a single chart.

Figure 14: Sample of Scatter plot chart (Source: https://chartio.com)

Different colours and or different symbols for the dots can be used for different
categories of the data. However, one should not show too many categories in
one chart, as it may become difficult to separate those categories.The creation
of geo hierarchy on top of location data for example: states, cities etc. allows
drilling up to higher levels of details of geography [10].
 25

Choropleth map chart

Choropleth Map is a type of map chart used to show geographically segregated

areas such as countries, regions, etc. That are collared, patterned, or inserted
in relation to shown data. In this way, it allows one to visualize data values in a
particular area, giving an understanding of how they differ throughout the area
shown on such a map.

When one creates a large data map in Choropleth Maps, a certain colour
continuity should be used to display the data properly. Choropleth Map uses
different shading, colouring and the placing of symbols within defined regions to
show measured values in those areas [11].

Figure 15: Sample of Choropleth map (Source: www.anychart.com)

 26

Choropleth Map is used for supporting location based comparisons of

standardized data such as rates, densities, percentages.

This type of map is usually used for similar size of locations as the size of the
area coloured may overemphasize larger areas. For example, the total area of
Canada is larger than Japan despite being smaller in context of population.
Choropleth Map may present visually clear information using various colours
and shapes for the viewer.

Geo Bubble chart

Geo charts show map data by location. They are geo, geo bubble, and geo
heatmap charts. This type of chart indicates measured values in the form of
bubbles on a map. The more the measured values are, the larger bubble will be
formed on the map. Geo bubble charts, such as bubble charts, show the
average value for a relative bubble size. Zip code data is a good choice for geo
bubble charts. [12]

Figure 16: Sample of Geo Bubble chart (Source: https://docs.thoughtspot.com)

 27

​In Figure 16, the bubble chart indicates increase in sales, where it can be
observed that the bigger the bubble, the larger the number of sales and the
lower the bubble, the smaller the number of sales.

Treemap chart

Figure 17: Sample of Treemap chart (Source: developers.google.com)

Looking at the sequence data, where the design is complex and organized by
tree, the Treemap chart is a great solution. With this type of chart, the whole
(“tree”) is seen as a rectangular diagram with smaller rectangles showing
branches, making it easier to understand the structure and compare the shares.
In fact, while Pie chart works with a small number of points, Treemap charts are
ideal for large data sets. The Figure 17 indicates an example of export by
country of destinations.
 28

4 Visualization Tools

This section gives first an overview of visualization tools and what kind of tools
are available in the market and their features.

In the Big Data world, efficient and feature-rich tools are essential for analysing
large amounts of information and making data-driven decisions.

4.1 Tableau

Tableau Software is an American computer software company based in Seattle

and it offers BI-based data consulting products. The company was established
in the Department of Computer Technology at Stanford University between
1997 and 2002.

The various products made by the Tableau are shown in the Figure 18.

​Figure 18: Image of Tableau products offerings (Source: https://intellipaat.com)

 29

Tableau Desktop

Tableau Desktop is a data recognition application to help to scan almost any

type of structured data and generate highly interactive graphs, beautiful
dashboards, and reports within minutes. Once installed, someone can link to
almost any data source from spreadsheets to data repositories and display
details in several clicks. Designed for easy use, one can work much faster than
before.

Tableau Server

It is a business spy app that provides browser-based analytics that anyone can
use. It is the fastest way to fire in the slow pace of traditional BI software. It is an
online solution designed for the sharing, distribution, and interaction of content
created in Tableau. What makes Tableau different? Everyone is recommended.
No script is required, so everyone can grow up to be a mathematician.
Someone can increase postage, as per need. Train online for free. Get answers
in minutes, not months.

Tableau Online

Tableau Online is a secure, cloud-based solution used to share, distribute, and

collaborate on Tableau views and dashboards. Tableau online puts the flexibility
and simplicity of a powerful cloud-based data recognition solution for us -
without servers, server software, or IT support. Tableau Online can measure as
much as someone needs and someone can use it wherever need. Someone
does not need to purchase, set up or manage any infrastructure.
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Tableau Public

Tableau Public is free software to help anyone connect to a spreadsheet or file

and build interactive web visibility. It is provided as a service that allows the user
to get up and work through the night. With Tableau Public users they can create
amazing interactive views and publish them instantly, without the help of
program or IT.

Features of Tableau

● It is very easy to use.

● Someone doesn’t have to be familiar with programs of any kind,
someone needs a few data and tables to produce visually appealing
reports and tell a story which user should tell their supervisors or please
their professor in class.
● It has a drag and drop feature where the user can simply generate
stories or reports with drag and drop and a few thoughts.
● This may be due to VizQL (VizQL is a visual query language that
translates the action of drag and drop to data queries and renders that
data visually Query and analysis.

Such a tool does not require any special technical or organizational skills to
collaborate or create any feature. It has a collective interest among people from
a variety of business, researchers or industries. Tableau Software has an
intuitive, easy-to-use interface, which allows business users to discover,
analyze and display the results of their data without technical and system
capabilities. Tableau's capabilities include advanced features such as
forecasting, integration, default geocoding, and a visual formula editor. It allows
users to do more research and use their data faster and more efficiently than
most competing platforms, as well as the ability to downgrade data distribution.
 31

Figure 19: Sample of Tableau Desktop (Source: https://intellipaat.com)

There is also an online community called Tableau Public for development

training and support. Some of the weaknesses are high product costs, difficulty
modeling when combining data from different sources, low performance and
large amounts of data.

Dashboards can be shared with others as a static file. While launching the
Tableau, data connectors are available, and allow someone to connect to any
database needed.

In summary, Tableau is a business platform designed for collaboration,

distribution, management, security model and automated features. End
customers are better experienced accessing files stored in all locations such as
desktop, mobile phone or email. [13]
 32

Derived Chart

It is important to define what types of charts are supported by Tableau based on

the list of mostly used ones listed in the literature review. [14]

Figure 20: The possible chart types supported by Tableau

● Stacked Bar and Column Charts

● 100% Clustered Bar and Column charts
● Clustered Bar and Column Chart
● Line and Area Charts
● Line and Stacked / Clustered column charts
● Waterfall chart
● Scatter and Funnel Charts
● Pie and Donut charts
● Tree map chart
● Map and 3-D filled map
● Other items such as Gauge, Card, Multi-Row card, KPI11, Slicers and
Interactive Tables to describe the visuals effectively.
 33

Importing Data

The first step for importing the data is to run the desktop application or online
Tableau software. In the following Figure 21, the desktop of Tableau application
is showed. Tableau Desktop is a free program that install on a local computer
that allows to connect, modify and visualize data.

Figure 21: Tableau desktop

With Tableau Desktop, someone can connect to various data sources, and
integrate it (commonly called modeling) into a data model. This data model
allows someone to create visuals, as well as collections of visuals that someone
can share as reports, with other people within organization. Many users working
on business intelligence projects use the Tableau Desktop to create reports and
then use the Tableau application to share their reports with others.

After running the desktop, the home menu will get open. In Figure 22, the
connect section of Tableau application is showed. The connect section of
 34

Tableau software allows someone to create visuals by inserting data. The data
can be inserted using Connect section.

Figure 22: The Sources of importing the data

Connect section includes various options such as search for data, to a file, to a
server and many more. It includes different visualizations which can be used for
presenting the data in unique manner. It also enables user to filter the data used
for preparing report.

In Figure 22, the sources for importing data are mentioned. There are many
sources for inserting the data into Tableau software. There are many options
available in the connect section for importing the data such as search for data,
to a file and to a sever.
 35

Figure 23: The Process of inserting the data

In Figure 23, the process of inserting the data is showed. In connect section,
click on any options available for importing the data. The data can be imported
from number of sources like Excel, Text/CSV, JSON file, PDF file, Spatial file,
Statistical file and many more. Beside this, it is also possible to import data
through Tableau desktop using Microsoft SQL server, My SQL, Oracle, Amazon
Redshift and many more.

Note:

For example, with a view to import Excel data, the aggregate data is formatted
in table form for Tableau to identify the data and bifurcate it into particular
sections for providing visualizations. The data for analysis is imported by
selecting Microsoft Excel option in the to a file category under connect section.
After selecting the option of Excel, the window will appear for selecting the file
which is required to be imported for the purpose of analysis. From the window,
 36

select Tableau analysis file and click on open button in order to open it. The
Tableau analysis file is selected for inserting the data into Tableau application.

Figure 24: The transformation of importing data

Figure 24 indicates the empty white colour window which is going to be used for
creating charts. Once the data file which is to be used for the purpose of
analysis is selected, the window shown in the Figure 24 will appear where an
individual needs to drag the categories for creating charts.

Dashboard Creation

The next important thing is to help Tableau application in identifying fields which
are related to stock prices of selected BSE indices. Therefore, the data is
required to be categorized and divided into particular fields.
 37

The process of designing the dashboard

Figure 25: Tableau workspace desktop

The Figure 25 includes report view and there is a workspace in Tableau

Software. Moreover, the figure also indicates the essential parts to be
emphasized for performing analysis. The figure indicates that the Tableau
workspace consists of menus, a toolbar, the Data pane, cards and shelves and
sheets. Sheets can be worksheets, dashboards, or stories.

Workbook Name - The workbook contains sheets. Sheet can be a worksheet,

dashboard, or story.
 38

Cards & Shelves - Drag fields to cards and shelves in the workspace to add
data to view.

Toolbar - Use the toolbar to access commands and analytics and navigation
tools.

View - This is a canvas in the workspace where someone create visibility (also
called "viz").

Sidebar - In the worksheet, the sidebar area contains the Data window and the
Analytics window.

Status bar - Displays information about the current view.

Sheet Tabs - Tabs represent each sheet in workbook. This may include
worksheets, dashboards and stories.

There is Show Me tab on the right side of the window. Under the show me tab,
various types of charts are available like bar chart, pie chart, map chart,
treemap chart and many more. An individual can select any type of chart for
presenting the data.

The show me icon includes different types of charts which can represent the
data graphically in an interactive way.

There are fields situated in the left-hand side of the figure. Under the show me
section, choose any chart and click on that chart in order to create a chart and
then drag one category into the column field and drag another category into the
row field for running the connection between data and present it through a
chart. Different charts represent the data differently in respective charts that are
mentioned in the literature review like bar charts, maps, pie charts and many
more.
 39

4.2 Power BI

Power BI, Microsoft, is an organization of business analytics tools used to

analyse data and share information in the form of reports and dashboards. User
data can be inserted in a variety of ways - spreadsheets, text files, databases,
etc. Data sets are created by converting data provided by users. Data
conversion is determined by users. This step is used to remove errors and
unwanted data, correct formatting, and to prepare additional analysis of data by
sorting them into standard appropriate forms, and so on. Depending on the
report and the dashboard being created, filtering data to include only relevant
pieces makes one focus only on important data.

Once the database is ready, reports can be created from them by adding from
the multi-item selection option. The visual objects in the Power BI range from
the number one display to the gradient colour map. These mirrors help to
present data in a way that provides context and understanding. Filters can be
used in reports so that relevant data is directed to users who are interested in
data analysis. Such reports can be created manually or once the reports have
been published, report items or the entire report can be added to the
dashboard.

Power BI dashboards display 360 degree data viewing by enabling users to

keep their most important metrics in one place. They also allow users to
participate in filtering or query reports, and allow native language queries.
However it is limited to one page, thus only opening the relevant parts of the
data to make it easier for users to gain insight. It is also possible to regularly
update data and dashboard data, in real time, and make it available on all
devices such as PCs and smartphones. [15]

Most users working on business intelligence projects use the Power BI Desktop
to report, provide and analyse data and then use the Power BI app to share
 40

their reports with others. [16] The key features of the Power BI Desktop are as
follows:

● Connect to data
● Change data and build a data model
● Create visuals (charts or graphs) that provide visual data presentations
● Create visual reports, on one or more of the report pages
● Share reports with others via the Power BI service

Power BI is free to use app to visualize various types of data that analyze and
retrieve filed information, intelligently organizing chapters with a closely related
group table into one category. [17] It can create a complex and visually rich
reports, uses data from multiple sources and immediately shares it with others
through the Power BI service thinking. [18]

Figure 26: Power BI desktop

In Figure 26, the first page of the Power BI Desktop report is represented as
Home. It is the beginning of a visual tool. There are many features that Power
 41

BI offers to connect to other apps and tools. There are three ways to use Power
BI, such as:

● Power BI online
● Power desktop
● Power BI Cell Phone

4.3 Cognos

IBM Cognos is a business intelligence tool for web-based reporting and

analytics. This business software offers a variety of features to enable data
integration and to create detailed reports that are easy to use. Cognos also
offers the option to send reports in XML or PDF format and view reports in XML
format.

Features of IBM Cognos

The following are the key features of Cognos.

● Provides streaming statistics within the memory

● Provides real-time events, notifications, and notifications.
● Intuitive, attractive Web 2.0 interface
● Personal and progressive collaboration
● Drag and drop, free form integration, and search-assisted authorization
● External data operated by the wizard
● Automatic access to SAP BW queries
● Allows features such as status model creation, real-time monitoring, and
forecasting
● Users can edit existing data.
● Drill-Through Power.
● Integration of Possible Image Documents.
● It is an independent, reliable, and dependable platform.
 42

● Provides secure data as protected by firewall.

Components in Cognos

Below is a list of key features of the Cognos software.

Cognos connections

Cognos Connect is a web site that allows users to access Cognos 10 and
studios. Depending on the role someone have been assigned, someone may
use this section to locate, view, publish, manage, and edit company reports,
scoreboards, and agents. Administrator also uses Cognos Connection to
establish user roles and permissions and manage Cognos Connection content.

Cognos Business Insight

The offer of Cognos Business Insight allows users to create their own
dashboard and use anything. All content that the user is allowed to view will be
presented as an object. This can be used in your workplace to create a
completely personalized dashboard.

Cognos Query Studio

Cognos Query Studio helps business users find quick answers to

business-related questions. It helps organizations better understand the
product, customers and organizational needs. It also helps them to respond
faster and stay ahead of the competition.

Cognos Analysis Studio

 43

Cognos Analysis Studio helps businesses find and focus on business priorities.
It is also helpful to understand the latest trends, compare data, and evaluate
business performance with several analyzes.

Cognos Business Insight Advanced

Cognos Business Understanding Improved by a new module installed in

Cognos 10. Includes Cognos Questionnaire and Cognos Analysis Studio. It
provides a powerful environment for authorizing business people.

Cognos Report Studio

Using the Cognos reporting tool, someone can create complete pixel reports for
organization. Allows someone to create charts, maps, lists, or any other type of
report available using affiliate or multi-distribution data sources.

Cognos Event Studio

This tool allows someone to provide a specific event that sends a notification to
a stakeholder in an organization. Someone can create agents that empower
anyone at events and borders. Therefore, in the event that an event or limit is
reached by the agent who sends the notification.

Cognos Metric Studio

Cognos Metric Studio lets someone’s view and analyze an organization's

business metrics by creating a scorecard environment. It also helps someone to
initiate the process and monitor an organization to see how it responds as
changes are made to the process.

Types of Cognos
 44

Here are the key types of Cognos reporting tool.

Content Store

Set with data tables used by the Content Manager to store Cognos application
data.

Content Manager

Cognos Manager helps someone to manage storage and retrieve reported data,
configuration data, and published packages, from the content store database.

Cognos Content Database

The Cognos Content Database is a self-contained database server used to host

a content store database in demo’s locations where DBMS business is not
available.

4.4 Qlik view

Qlik (formerly known as QlikTech Inc. provides a business statistics platform.

SaaS Software Company was founded in 1993 in Lund, Sweden and is now
based in King of Prussia, Pennsylvania, United States. Qlik Sense and Qlik
Replicate, Both cloud-based software for business intelligence and data
integration.

QlikView is a business intelligence tool for data integration, chat statistics, and
converting raw data into a knowledge base. QlikView provides ad query
features and makes it easy to make decisions based on easily accessible
information. This software works on the integration model and can be accessed
in any way to search for answers.
 45

Here are the benefits / great benefits of using QlikView.

● It is very simple and intuitive to use the platform.

● Provides data visibility in a clear and professional way
● Quick response time without limit to the amount of data
● Allows to search for all data directly and indirectly
● QlikView provides support for dynamic applications, dashboards, and
analysis, etc.
● It facilitates the rapid integration of data from multiple sources into a
single application.
● It helps to identify styles and information to make new decisions.
● Allows someone to access, analyze, and retrieve data from mobile
devices.
● It provides a quick return on investment, due to the short start time.
● Rapid Development and Change Management.
● Self Service Business Intelligence for end users.

Key features of QlikView

Data Integration Model: QlikView works on in-memory integration model. So

someone doesn't need "IT professionals" If someone can write SQL select
Questions and understand data.

Platform: QlikView is a windows-only product, but is actually configured for 64

bit and many processors.

Costs effective: QlikView is a memory app, so it's an inexpensive way for

organization.

Economical: QlikView saves a lot of disk space as the amount of memory

depends on the amount of data someone wants for each program.
 46

QlikView Applications

● It helps to analyze revenue data based on various filters of a large

international organization.
● Allows someone to create a detailed watch report based on social media
feedback from customers around the world.
● The Qlikview tool lets someone make decisions based on predicting
cause and effect with drawings using its historical data.
● QlikView lets someone analyze existing items, activity orders, sales, and
staff usage - all focused on improving performance.
● Tools allow someone to analyze information about sales, production,
shipping, and product performance.
● Someone will be able to easily and quickly create reports and analysis at
the strategic, effective, and strategic level.
● Canon, Panasonic, Shell, FILA, ING LEASE are some of the well-known
companies that use Quickview in their businesses.

4.5 SAP Analytics

SAP Analytics Cloud, commonly referred to as SAC, is a tool for viewing cloud
data from SAP.

SAP Analytics Cloud combines the following functionality into one tool:

● Business Intelligence (BI);

● Predictability Analysis;
● Planning.

SAP provides a complete solution when it comes to business intelligence.

Available online in SaaS mode, SAC is becoming increasingly important in
 47

SAP's environmental system. Finally, it is intended to be a reliable BI tool for the

SAP Cloud suite.

SAP Analytics Cloud is a new tool in the SAP portfolio to meet the needs of
viewing data in the cloud. It is delivered as an all-in-one product, based on
SaaS. Includes requirements for data identification, budget planning, and
forecasting analytics.

Its main function is to create data reports.

This data can come from a variety of sources: real-time data taken from
business operations, budget status data or thousands of data lines formatted as
an MS Excel table.

The solution is accurate and easy to use. Allows the user to generate reports of
various complexities with complete independence.

SAC is part of a data analytics tool, similar to Microsoft's tool, Power BI.

The key features of SAC

● Business Intelligence
● Data Access
● SAP Analytics Cloud allows data to be available in two ways: Importing
Data and Direct reading from database / ERP.
● In the case of direct reading, real-time data is updated, only by
connecting to the SAP system (HANA, BW, BPC or another).

Data Modelling

This allows for data modification with additional features such as indexing,
formulas and converting values for acquired features.
 48

Data visualization

This feature allows someone to view and highlight data with graphs, tables or
other graphic objects.

Predictive Analysis

In order to highlight relevant metrics or predict future results, SAP has

introduced artificial intelligence. A few examples of use of these new features
include automated content creation with smart detection, powerful feature
identification, and uncompromising record acquisition, and much more.

Planning

The SAC planning process enables someone to consolidate financial and

operating statements with the same tool so that someone has a complete and
clear view of someone’s current situation.

Types of budget planning can be developed and modified from existing financial
statements. The machine learning tools provided and predictive tools can help
someone anticipate money in the future. Also available is the popular "What If"
mode of simulation.

What does the future hold for SAC?

SAP is focused on constantly improving SAC. Like a cloud tool, it is constantly

updated and visible, at no additional cost. SAP's future strategy for SAC can be
defined by the implementation of the solution: BI allocation and planning.

BI offer

The integration of the SAC data recognition component into other SAP Cloud
solutions furthers the synchronization of the reporting style and simplifies its use
 49

from one tool to another. Examples include SAP S / 4HANA Cloud Integrated
Analytics and a new cloud-based data storage tool, SAP Data Warehouse
Cloud.

In terms of SAP On-Premise solutions, SAP Business Objects remains the

preferred option, although hybrid solutions with On-Premise ERP and
cloud-based solutions are becoming increasingly available.

By planning

SAP strategy to prioritize cloud solutions for editing tools. The use of SAP
Analytics Cloud is recommended for scheduling without the need for legal
consolidation.

In addition, its collaborative planning tools provide an additional value for

updating forecasts in each company category and its integration with SAP S /
4HANA allows for easy data integration.

However, for customers using the On-Premise solution via SAP BPC, the
extension is possible with SAC. Even improved data usage is recommended.

In short, SAP develops SAP Analytics Cloud across all segments offered;
whether it reports on its new solutions or planning in conjunction with other tools
in its category. With SAP's focus on continuing to improve the tool, SAC has a
bright future ahead of it.

4.6 Excel

The most widely used Microsoft office program is Ms Excel. Excel is a

spreadsheet tool used to store and analyze numerical data.
 50

An Excel spreadsheet may be thought of as a collection of columns and rows

that together form a table. Rows and columns intersect in an area known as a
cell.

Normally, alphabetical letters are assigned to columns (A to Z and so on),

whereas numerals are assigned to rows (1 to 1,048,576). Each cell can only
hold a single piece of data, such as a number value, text, or formula.

Microsoft Excel is a spreadsheet tool used to capture and analyze numerical

and statistical data. Microsoft Excel has a variety of functions for performing
different tasks such as mathematical computation, graph tools, pivot tables,
micro programming, and so on. It is compatible with a variety of operating
systems, including Windows, Android, and others.

Microsoft Excel uses terms such as cell, workbook (which refers to an Excel
spreadsheet record), worksheet, workspace, formula bar, tool bar (which is
used to save, undo, redo, and so on), chart, data validation, and ribbon.

The default format for storing a Microsoft Excel workbook is.xlsx. The extension
for Excel workbooks (deprecated) is.xls. The extension for an Excel
macro-enabled workbook is .xlsm. The extension for an Excel binary workbook
is.xlsb. The extension for Excel templates is.xltx.
 51

5 Results and Analysis

This section gives an overview of data and visualisation of different indices

using Tableau.

5.1 Case Study Description

In this part of the thesis, two popular and widely used methods of BI platforms
are compared. The methods compared in the thesis include Microsoft Excel and
Tableau. Further, the thesis also compares their key parameters: Accessibility,
Usability and visibility, Differences in dashboard design, Features form
recognition and their strategies.

The comparison is based on a case study, and it tries to answer following

questions:
● What is the best tool for building visual dashboards?
● What are the major differences between Tableau and Microsoft Excel?

Microsoft Excel and Tableau are cloud-based suites of business analytics tools,
both below Office 365 Enterprise E5 version. Both of these programs are good
programs in their own way. It is therefore interesting to note the pros and cons
being used in studying case study.

This case study is aimed at presenting an assessment of return for selected

BSE Indices in India considering important decisions for companies, investors
and researchers.

The development and preparation of the visualization dashboard for research

scholars, investors and managers of the company regarding investment
decisions and having better understanding about return provided by selected
 52

BSE indices in preceding five years after demonetization in India. The

researcher is required to present the selected BSE indices stock prices data of
past five years i.e. from 2016 to 2021 in such an innovative way that it can be
easily and clearly understand by research scholars, managers, investors and
any individual. The researcher is also required to present the information
regarding how selected BSE indices are performing in terms of return
generation after the implementation of demonetization in India.

Research scholars, investors and managers of the well established companies

need well-processed data that match to their requirements and expectations.
Therefore, it is required to formulate creative ideas for presenting the raw data
and prepare a report based on data received from the website of Bombay Stock
Exchange concerning to international investors, researchers, companies that
already invested their money abroad. The data report should be informative and
understandable for a rapid analysis of the data, as international investors or
companies often do not understand the data of selected BSE Indices available
on BSE's website where the data is published by Bombay Stock Exchange of
India. These investors often invest based on the reports or documentation that
aims to help an individual to get better understanding about return given by
selected BSE indices in last five years after demonetization in India.

How to help these research scholars, investors and managers? To interpret the
data intelligently, a modern and sophisticated process to create an interactive
dashboard that explains the broad data in a simple and clear way to the end
viewer for analysis is used. The critical interest of the investors or researcher is
obvious to get an easily understandable stock prices data of selected BSE
indices which can be used in conducting further research or for making
predictions about future performance of selected BSE indices and which indices
will be going to perform better and results into higher returns for investors in
future in India. Apart from investors and researchers, the managers of
international companies will also have an interest in knowing about performance
 53

of selected BSE indices for making investment related decisions in India. Many
viewing tools can visualize big data, the most popular tool on the market
described in literature reviews and the types, purposes and methods of building
such visuals.

The dashboards should rapidly explain to end-user about the most important
indicators in general. For example, the stock prices of selected BSE indices, the
number of sectors performing well after the implementation of demonetization
and higher returns generated by selected indices among selected BSE indices
and other related information. The result of the analysis should provide pros and
cons to the investors, researchers and managers that whether it is good to
invest in India or whether Indian stock market is performing well after
demonetization or not. For example, if any foreign company or foreign investor
is planning to invest in India for business and for increasing their wealth then
they should make sure that it has potential growth opportunities and will be able
to generate good returns with lower risk.

This thesis will mostly focus on the comparison of Microsoft Excel and Tableau
dashboards which will analyse the data from authenticated database sources
and it will also give suggestions for further improvements in creating visual
dashboards. The result of dashboards will give visual differences and indicate
benefits of these used tools for the purpose of analysis.

5.2 Sources of Data

BSE Limited, also known as Bombay Stock Exchange (BSE), is an Indian stock
exchange located on Dalal Street in Mumbai (Bombay). Founded in 1875 by
Cotton Merchant Premchand Roychand, A Rajasthani Jain Businessman, it is
the oldest stock exchange in Asia, [6] and the tenth largest in the world. BSE is
the 9th largest stock exchange with a total market capitalization of more than
R255.003 trillion, as of October 2021.
 54

In 1986, BSE developed the S&P BSE SENSEX index, giving BSE a way to
measure the overall performance of a trade. In 2000, BSE used this index to
open the exit market, trading in future S&P BSE SENSEX contracts. The
development of the S&P BSE SENSEX options and the equity exit followed in
2001 and 2002 expanded the BSE trading platform.

BSE launched India INX on December 30, 2016. India INX is India's first
international exchange. BSE introduces an export contract for gold, silver. BSE
is the first in Asia and the Fastest Stock Exchange in the world with a speed of
6 seconds and is one of the leading trading groups in India.

BSE Indices

The stock market index statistically summarizes market movements in real time.
The stock market index is created by selecting the same types of stock in the
market or trading and then merging them together. Sensex, representing the
‘Stock Exchange Sensitive Index’, is a stock market indicator for the Bombay
Stock Exchange. Calculates movement on BSE.

Types of Stock Market Indices

There are various indicators of the stock market in India. Here are listed some
of the indices found in BSE.

Benchmark Index

The key metrics for viewing market movements as they reflect the performance
of the entire market. Comparative statistical rate which means showing the
amount earned by the central fund in the market compared to the amount that
should have been gained. eg: BSE Sensex, NSE Nifty (Nifty 50).

Broad Market Index

 55

They are indicators of stagnation, but they often strengthen many stocks in the
index. eg: BSE 100. BSE Sensex includes the movement of 30 financially
strong Indian companies listed on BSE. The BSE 100 does the same for over
100 large companies.

Market Capitalization Index

An indication of how companies' shares are measured in terms of total market

value (capitalization) of their remaining shares. eg: BSE Smallcap, BSE Midcap

Sector or industry-based index

Provide benchmarks and summaries of stock operations in specific industries

such as health care, energy, industrial goods, technology, etc. CNX IT, Nifty
FMCG Index.

BSE includes market capitalization index, broad market index, sector and
industry index, thematic index, strategy index, sustainability index, volatility
index and fixed income index.

In this thesis, the five sectoral indices were selected randomly for the purpose
of analysis. The selected five sectoral indices are S&P BSE Auto, S&P BSE
Bankex, S&P BSE Information Technology, S&P BSE Oil & Gas and S&P BSE
FMCG.

Introduction of Demonetization

Demonetization is the process of extracting money from a common use or

distribution. In other words, demonetization is the act of depriving a currency
unit of its status as a legal tender. It happens whenever there is a change in the
national currency. Current currencies are taken out of circulation and
discontinued which is often replaced with new notes or coins.
 56

On November 8, 2016, the Prime Minister of India Narendra Modi announced

the demonetization in an unscheduled live televised.

Speech to the nation at 20:15 IST., in a proclamation, Modi announced that the
distribution of all 2500 and 1000 banknotes of the Mahatma Gandhi series was
illegal from midnight on the same day, and announced the release of the new
500 and 2000 series to replace the old ones.

The purpose was to eradicate people's black money, as well as money from
terrorism. There is no doubt that ordinary people were greatly affected,
especially those who earn less money and who do not have wealth (lower
middle class family and poor family). Even their small financial assets do not
work and they face problems meeting their basic daily needs.

The category of employees who earn and save their income by 500/1000 notes,
were beaten because they had no money to buy in the market.

5.2.1 Data Based On Selected BSE Indices

BSE real-time information products are distributed directly by BSE vide lease
lines and indirectly by data vendors. Data products provide information on all
listed and traded instruments in Equity, Equity Derivatives, Currency
Derivatives, Commodity Derivatives and Credit Segment as well as S&P BSE
Real Time Indices.

Data Segments covered:

● S&P BSE Real Time Indices.

● BSE Real time Level 1 – Equity, Equity Derivatives & Debt.
● BSE Real time Level 2 – Equity & Equity Derivatives & Debt.
● BSE Real time Currency Derivatives.
 57

● BSE Real time Commodity Derivatives.

The stock prices of selected BSE indices for thesis namely S&P BSE Auto, S&P
BSE Bankex, S&P BSE Information Technology, S&P BSE Oil & Gas and S&P
BSE FMCG sector was collected from the website of BSE. The data was
collected for a period of past five years from 1st April, 2016 to 31st March,
2021. BSE provides historical stock prices on a daily, monthly and yearly basis.
However, in this thesis, the daily stock prices of all selected BSE indices have
been analysed for the purpose of return calculation. Apart from historical stock
prices data, the annual reports data of various companies are also available on
BSE's website. The website also provides information about various financial
ratios for companies listed on BSE stock exchange and it also provides
information about listed companies on stock exchange.

5.2.2 Description of Data

The data used for the analysis includes daily historical stock prices of selected
BSE indices for the monitored period of preceding five years such as from the
year of 2016 to 2021.

It includes:

Date : The dates are showed under this column. For example: 1/4/2016 to
31/3/2021.

Closing price: The closing prices for BSE oil and gas stocks are mentioned in
rupees. For example: 9047.79 Rs. As on 1st April, 2016.

Simple Moving Average using daily price: The simple moving average is
calculated for 3 days using daily stock prices of BSE oil and gas index, i.e.
9033.308 Rs.
 58

Simple Moving Average using monthly price: The simple moving average is
calculated for 3 months using monthly stock prices for deriving the average
return value for the year 2016.

After simple moving average, the return provided by selected BSE indices are
calculated for past five years using yearly prices of indices which are derived
using simple moving average method.

Sector: The name of the various sectors, e.g. "BSE Auto Index".

Year: The years are stated under the heading of year, i. e. 2015-16.

Closing price: The amount of stock price which is derived using simple moving
average method in the past five years is mentioned in rupees, e.g. 18001.75
rupees in the year 2015-16 and similarly the closing prices for remaining years
are mentioned in rupees under the head of closing price.

Return (Ri): The percentage of return given by BSE Auto Index in past five
years is stated, i.e. 18.03% return was given by BSE Auto Index. Similarly, the
return for remaining years is calculated. After calculation of return on yearly
basis, the mean is calculated using five years return values for identifying the
average return given by BSE Auto in preceding five years i.e. from 2016 to 2021
after the implementation of demonetization.

5.3 Data Analysis

In order to create a chart the most significant thing, the data, is analysed in the
entire dash board. In this case, it is the stock prices of selected BSE sectoral
indices for a particular year which is showed in Figure 27. The Figure 27
indicates the raw data which is analysed for the purpose of calculating return.
 59

Figure 27: The data used for creating the Tableau dashboard

The analysis is done by using stock prices of selected BSE indices. The stock
prices data is obtained from the BSE's website. After the data of stock prices
have been collected, it is analysed using Simple Moving Average Method for 3
days using daily stock prices for calculating the average monthly stock prices
given by particular index. Further, the monthly stock prices are used for
calculating yearly stock values using simple moving average method.
 60

Figure 28: Raw data of BSE Auto Index

In Figure 28, the raw data used for BSE Auto is stated. The figure also indicates
the calculation for deriving the yearly prices for BSE Auto index using Simple
Moving Average Method on a 3 days basis.
 61

Figure 29: Return calculation for BSE Auto Index

The Figure 29 indicates the return given by BSE Auto in last five years after the
implementation of demonetization. The return is calculated by using the
following formula:

Return = (Closing Price - Opening Price) / Opening Price * 100%

Firstly, the yearly returns are calculated and then average return given by BSE
Auto index in past five year is also calculated for comparative analysis of
selected BSE sectoral indices in order to know about which sector is performing
well by obtaining highest returns.
 62

Figure 30: Interactive visualization Heat Map Chart in Tableau.

In Tableau Heat Map chart is useful for comparing a number of dimensions

against a single measure (dimensions and measure are features provided by
Tableau). The following step is to be followed for creating an interactive chart to
know about the return given by selected BSE sectoral indices in each year.
Therefore, for creating Heat Maps chart in Tableau, first drag and drop the
return category into the column field and the year category into the row field. It
will then automatically create a bar chart.

After that, click on the Heat Map chart under the Show Me section which will
automatically convert the bar chart into Heat Map chart. In Figure 30, the right
sight of Auto- heat maps indicates the total amount of return in percentage
given (with square colour code) by BSE Auto Index in past five years and the
left sight of Auto- heat maps indicates the different years.
 63

Figure 31: Interactive visualization Text Tables Chart in Tableau.

After the Heat Map, text tables chart is created for representing the returns
obtained by BSE Auto Index in past five years after the implementation of
demonetization. For creating text tables chart, first drag and drop the return
category into the column field and the year category into the row field. It will
automatically create a bar chart.

Click on text table’s chart under the Show Me section which will automatically
convert the bar chart into text table’s chart. In Figure 31, the right sight of Auto-
text tables indicates the total amount of return in percentage given by BSE Auto
Index in the past five years and the left sight of Auto- text tables indicates the
different years.

The following step is to create an interactive vertical bars chart that provides
information about the percentage of return given by BSE Bankex in the past five
years after demonetization.
 64

Figure 32: Raw data of BSE Bankex Index

In Figure 32, the raw data used for BSE Bankex is shown. The figure also
indicates the calculation for deriving the yearly prices for BSE Bankex using
Simple Moving Average Method on a 3 days basis.

Figure 33: Return calculation for BSE Bankex Index

 65

The Figure 33 indicates the return given by BSE Bankex in last five years after
the implementation of demonetization.

Firstly, the yearly returns are calculated and then average return given by BSE
Bankex index in past five year is also calculated for comparative analysis of
selected BSE sectoral indices in order to know about which sector is performing
well with obtaining highest returns.

Figure 34: Interactive visualization vertical bar chart in Tableau

The next chart in the dashboard is the vertical bar chart. Let's try to develop a
chart that includes detailed information about the percentage of return given by
BSE Bankex in preceding five years.

In Figure 34, the vertical bar chart indicates the percentage of return given by
BSE Bankex in past five years from 2016 to 2021. In this type of chart, y-axis
indicates the total amount of return in percentage given by BSE Bank Index in
past five years and x-axis indicates the years.
 66

Here, the vertical bar chart represents the return given by BSE Bankex. In
2017-18, 27.20% return is obtained by BSE Bankex which is the highest as
compare to other years. However, in the year 2020-2021, the banking sector is
not performing well as it has negative return of -15.30%.

Figure 35: Highlight table chart in Tableau

The returns obtained by BSE Bankex are represented previously using vertical
bar chart. Here, the same data is presented using different chart type called
highlight table for presenting data in a better way of visualization. For creating a
highlight table chart select the chart from show me section and move the
categories in to row and column fields that are required to display in the
highlight tables chart. The figure of highlight table chart indicates the
percentage of return given by BSE Bankex from the year 2016 to 2021.
 67

Figure 36: Raw data of BSE FMCG Index

In Figure 36, the raw data used for BSE FMCG Index is shown. The figure also
indicates the calculation for deriving the yearly prices for BSE FMCG Index
using Simple Moving Average Method on a 3 days basis.
 68

Figure 37: Return calculation for BSE FMCG Index

The figure indicates the return given by BSE FMCG Index in last five years after
the implementation of demonetization. The yearly returns are calculated and
then average return given by BSE FMCG index in past five year is also
calculated.

Figure 38: Interactive visualization vertical bar chart in Tableau.

The next chart in the dashboard is the vertical bar chart. Let's try to develop a
chart that includes detailed information about the percentage of return provided
by BSE Fast Moving Consumer Goods in preceding five years.

In Figure 38, the vertical bars chart indicates the total percentage of return
achieved by BSE FMCG sector after demonetization.

The vertical bars chart shows the percentage of return given by BSE FMCG
Index in past five years. Each year is represented using different bars. The year
which has the highest return is highlighted with a longer bar and as the return
reduces the bar will be smaller or negative. For example, in the year 2017-18
BSE FMCG Index has obtained highest return of 21.14% which is indicated with
 69

a longer bar and the index has obtained return of 13.52% in the year 2018-19
which is lower as compare to year 2017-18. Therefore, it is indicated with
smaller as compare to highest return bar. The BSE FMCG Index has witnessed
lowest return in 2019-20 which is around -1.85% which is indicated with
negative bar in the vertical bars chart.

Figure 39: Interactive visualization circle view chart in Tableau.

The data of BSE FMCG Index is also represented using circle view chart. For
creating circle view chart, first drag and drop the year into column field and
return into row field. It will automatically create a bar chart.

Click on circle view chart under the Show me section which will automatically
convert the bar chart into circle view chart. In figure, the y-axis indicates the
total amount of return in percentage given by BSE FMCG Index in past five
years and x-axis indicates the number of years.

The following step is to create a circle views chart that provides information
about the percentage of return given by BSE Information Technology in past five
years after demonetization.
 70

Figure 40: Raw data of BSE IT Index

In Figure 40, the raw data used for BSE Information Technology Index is
mentioned. The figure also indicates the calculation for deriving the yearly
prices for BSE Information Technology Index using Simple Moving Average
Method on a 3 days basis.
 71

Figure 41: Return calculation for BSE IT Index

The Figure 41 indicates the return given by BSE Information Technology Index
in last five years after the implementation of demonetization.

Figure 42: Interactive visualization circle views chart in Tableau.

For creating a circle views chart select the chart from Show Me section and
move the categories into row and column fields that are required to display in
the circle views chart. The figure of circle views chart indicates the percentage
of return given by BSE IT from the year 2016 to 2021. X-axis indicates different
years and y-axis indicates return.
 72

Figure 43: Interactive visualization vertical bar chart in Tableau

The returns obtained by BSE IT Index are represented previously using circle
view chart. Here, the same data is presented using different chart type called
vertical bar chart for presenting data in a better way of visualization. For
creating a vertical bar chart select the chart from show me section and move
the categories in to row and column fields that are required to display in the
vertical bar chart. The figure of vertical bar chart indicates the percentage of
return given by BSE IT from the year 2016 to 2021. X-axis indicates different
years and y-axis indicates return.
 73

Figure 44: Raw data of BSE Oil & Gas Index

In Figure 44, the raw data used for BSE Oil & Gas Index is stated. The figure
also indicates the calculation for deriving the yearly prices for BSE Oil & Gas
index using Simple Moving Average Method on a 3 days basis.

Figure 45: Return calculation for BSE Oil & Gas Index
 74

The Figure 45 indicates the return given by BSE Oil & Gas in last five years
after the implementation of demonetization.

Figure 46: Interactive visualization vertical bar Chart in Tableau

The following step is to be followed for creating an interactive chart to know

about the return given by selected BSE sectoral indices in each year. Therefore,
for creating Vertical Bar chart in Tableau, first drag and drop the year category
into column field and return category into row field. It will automatically create a
bar chart.

After that, click on vertical bar chart under the Show me section which will
automatically convert the bar chart into vertical bar chart. In figure, the vertical
bar chart is displayed for BSE Oil & Gas Index. The vertical bar display with
different bars sizes depends on returns.
 75

Figure 47: Interactive visualization circle view chart in Tableau

After the Verticle bar chart, circle view chart is created for representing the
returns obtained by the BSE Oil & Gas Index in past five years after the
implementation of demonetization. For creating circleviews chart, first drag and
drop the year category into column field and return category into row field. It will
automatically create a bar chart.

Click on the circle views chart under the Show me section which will
automatically convert the bar chart into circle views chart. In figure, the y-axis
indicates the total amount of return in percentage given by the BSE Auto Index
in the past five years and x-axis indicates the years.
 76

Table 1: Different between Tableau and Microsoft Excel (Source:

https://www.simplilearn.com/)

S.R Parameters Microsoft Excel Tableau

.
No.

1. Definition It is a spreadsheet It is a visualization tool

application used to used for detailed analysis.
organize and format the
data.

2. Usage Suitable for storing data Perfect for the quick and
and statistical analysis. easy representation of
data.

3. Security The inbuilt security Several options to secure

features are weak as the data without scripting.
compared to the Tableau.

4. User Interface To unleash the full potential We can use Tableau with
of Excel, knowledge of no prior knowledge of
VBA and basic scripting is coding.
required.

5. Business Quick on-off reports. Best while working with

Purpose big data.

6. Integration Excel integrates with Tableau integrates with

around 60 applications. around 250 applications.
 77

6 Recommendations and Conclusions

The analysis of the thesis indicates that it is possible to convert raw data into
meaningful information based on the analysis of the case study. From the
analysis, it was observed that applications such as Tableau provided a good
result in terms of creation of a dashboard. Microsoft Excel has less distinct
benefits as compared to Tableau.

Microsoft Excel and Tableau applications are used for serving different
purposes. Not only Microsoft Excel but also Tableau are very affordable as
anyone can easily buy and install the respective applications.

While comparing Tableau with Microsoft Excel, it has been found that Tableau is
good when working with big data as compared to Microsoft Excel. Tableau
includes all the necessary things required for creating an effective dashboard
for securing business analytics as well as for creating reports and dashboards
which goods look in terms of visualization. Tableau is performing well in terms of
scalability in comparison to Microsoft Excel as it processes huge amounts of
information very quickly. The literature review and practical part describes the
major differences when using these the applications. As per the analysis,
Tableau is suitable for any user and it can create any unique dashboard as it
has many advantages and benefits compared to Microsoft Excel. Tableau is
used to present the data in such a way that it catches both viewer’s eyes as well
as their attention. While Microsoft Excel is suitable for creating smooth, basic
and straightforward visualizations without having much uniqueness in the report
or in the dashboard. Microsoft Excel is a spreadsheet application used to
organize and format the data.

Moreover, the most important thing is the end result of the analysis, because
well-designed, well-defined visualization helps in transforming raw data into
 78

useful information for easy understanding of the data. For example, instead of
describing the return values of the selected BSE sectoral indices to an
individual or managers of some company, it is better to explain data using
visualization tools which can present the information in a better way effectively
and effortlessly.

Data visualization is an efficient technique to convert the raw data into effective
graphic representations of any business or a project and it helps making
decisions related to future business actions. It also helps investors in getting
proper understanding about financial data for making effective investment
decision. The thesis analyzed current widely used visualization tools in the
market, validate differences and emphasized their benefits. It was necessary to
take two of the most popular applications of the market, design a dashboard
and create an interactive visualization using a particular data. The study used
the data of stock prices of selected BSE sectoral indices for a period of five
years which was collected from Bombay Stock Exchange’s annual report. The
study developed a dashboard for return values of selected BSE Sectoral indices
with the help of Tableau.

Tools such as Microsoft Excel and Tableau are inexpensive products today and
are affordable for startups and first-time users. Both of these tools are easy to
use and create dashboards because they analyze data quickly and include
analysis that automatically provides valuable and important aspects of data. It is
difficult to choose the best one because Microsoft Excel and Tableau have
different goals. One is a spreadsheet application that can create interactive
visuals, while another aims to design the effective visuals (like charts, tables,
graphs, maps, infographics, dashboards). Overall, the results showed that
Tableau is unique and provides seemingly relevant and professional looking
results that are very important to businesses and companies around the world
to present the significant data to investors and customers in an easily
understandable, effective and efficient manner.
 79

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