Business Intelligence and Data Analytics for Target Australia

This report investigates the adoption of business intelligence (BI) and data mining (DM) strategies within the context of Target Australia's women's clothing business unit. The research aims to analyze proposed solutions for BI adoption, identify business needs, and recommend optimal BI and DM techniques. The report employs a mixed research design, incorporating literature review, survey through questionnaires, and statistical data analysis to explore the relationship between BI and DM. It examines the business needs for BI, identifies Sisense as a leading BI technique, and explores various DM techniques such as tracking patterns, classification, and association. The report recommends strategies for DM and links them to the project's BI adoption, with a focus on Power BI reports and audit information. The findings highlight the favorable relationship between BI and DM, providing valuable insights and recommendations for enhancing operational efficiency and decision-making within Target Australia.

Running head: DATA ANALYTICS AND BUSINESS INTELLIGENCE
Data analytics and business intelligence

DATA ANALYTICS AND BUSINESS INTELLIGENCE 2
Abstract
The main aim of this report is to analyze the proposed solution in the adoption of business
intelligence and develops the strategies in the context of women clothing of Target Australia.
The research question for this assignment is “what is the proposed solution in business adoption
of business intelligence”. This research question would be responded via literature review and
survey through a questionnaire. In this research, a mixed research design is used for completing
the investigation. Along with this, statistical data analysis will be used for performing the
research. Interpretivism and inductive approach are used due to the subjective nature of the
research issue. In addition, both primary and secondary data collection is implemented in this
investigation. The results demonstrated that there is a favourable relationship between business
intelligence and data mining of Target Australia-women clothing business unit.

DATA ANALYTICS AND BUSINESS INTELLIGENCE 3
Table of Contents
Abstract.......................................................................................................................................................2
Introduction.................................................................................................................................................5
Aim and objectives..................................................................................................................................5
Literature review.........................................................................................................................................6
The business need for Business intelligence in the context of Target Australia-women clothing............6
Best BI technique to introduce the project in the context of Target Australia-women clothing...............6
Relationship between Data Mining (DM) and BI in the context of Target Australia-women clothing....7
Different DM techniques in the context of Target Australia-women clothing.........................................8
Best DM strategy for their project and link with the project’s BI adoption in the context of Target
Australia-women clothing.......................................................................................................................9
Methodology.............................................................................................................................................10
Research philosophy and approach........................................................................................................10
Research design.....................................................................................................................................10
Data collection method..........................................................................................................................10
Research strategy...................................................................................................................................10
Sampling...............................................................................................................................................11
Experiment and/or methods followed........................................................................................................11
Data analysis method.............................................................................................................................11
Ethical consideration.............................................................................................................................11
Survey through questionnaire....................................................................................................................11
Results.......................................................................................................................................................14
Discussion.................................................................................................................................................24
Conclusion and recommendation for further research...............................................................................25
References.................................................................................................................................................26
Table 1: Gender.........................................................................................................................................15
Table 2: Age group....................................................................................................................................15
Table 3: Experience in Target Australia-women clothing.........................................................................16
Table 4: Business intelligence encompasses analysis of data with the intention for uncovering the trend,
insights as well as, patterns........................................................................................................................17
Table 5: Sisense technique is competent for significantly simplify difficult data analysis, and creates
accessible big data insights within Target Australia-women clothing.......................................................18

DATA ANALYTICS AND BUSINESS INTELLIGENCE 4
Table 6: Discovering new data source can lead to addressing the causes for the financial shortcoming of
Target Australia-women clothing..............................................................................................................19
Table 7: Tracking patterns is one of the basic tools of data mining that helps to address the patterns in sets
of data within Target Australia-women clothing.......................................................................................21
Table 8: Classification is complex data mining tool that forces business for gathering the several attributes
together into the discernable categories of Target Australia-women clothing...........................................22
Table 9: Target Australia-women clothing uses power BI report in audit information for categorizing the
users..........................................................................................................................................................23
Chart 1: Gender.........................................................................................................................................15
Chart 2: Age group....................................................................................................................................15
Chart 3: Experience in Target Australia-women clothing..........................................................................16
Chart 4: Business intelligence encompasses analysis of data with the intention for uncovering the trend,
insights as well as, patterns........................................................................................................................18
Chart 5: Sisense technique is competent for significantly simplify difficult data analysis, and creates
accessible big data insights within Target Australia-women clothing.......................................................19
Chart 6: Discovering new data source can lead to addressing the causes for a financial shortcoming of
Target Australia-women clothing..............................................................................................................20
Chart 7: Tracking patterns is one of basic tool of data mining that helps to address the patterns in sets of
data within Target Australia-women clothing............................................................................................21
Chart 8: Classification is complex data mining tool that forces business for gathering the several attributes
together into the discernable categories of Target Australia-women clothing...........................................22
Chart 9: Target Australia-women clothing uses power BI report in audit information for categorizing the
users..........................................................................................................................................................23

DATA ANALYTICS AND BUSINESS INTELLIGENCE 5
Introduction
The research topic is “To analyze the proposed solution in the adoption of business intelligence
and develops the strategies in the context of women clothing of Target Australia”. The researcher
will investigate the small business unit of Target Australia i.e. women clothing in order to
develop an understanding of the adoption of business intelligence (Target Australia, 2019).
Target Australia has different needs for the adoption of BI such as customer relationship
management, and inventory management. The adoption of business intelligence would be
beneficial for improving operational efficiency and increase business productivity (Chaudhuri,
Dayal, and Narasayya, 2011).
Online shopping is an incredible boom in current times and Business intelligence plays a vital
role in its growth. BI facilitates personalization experience by recording all practices of a user.
BI technique like Power BI creates the trend of customers in terms of bar graphs, other
geographical structure, and pie chart. This graphical illustration creates it easier for eCommerce
admin to assess the information as well as act accordingly to gain sales (Yeoh, and Koronios,
2010).
Aim and objectives
The main aim of this report is to analyze the proposed solution in the adoption of business
intelligence (BI) and develops the strategies in the context of women clothing of Target
Australia. The given below objectives is used to complete the main aim of the project:
RO1: To identify the business need for business intelligence: In the context of Target Australia-
women clothing
RO2: To discover the best BI tool for introducing the project: In the context of Target Australia-
women clothing

DATA ANALYTICS AND BUSINESS INTELLIGENCE 6
RO3: To explore the relationship between Data Mining (DM) to BI: In the context of Target
Australia-women clothing
RO4: To recommend the DM strategy for their project and its link to BI adoption: In the context
of Target Australia-women clothing
Literature review
The business need for Business intelligence in the context of Target Australia-women
clothing
According to Duan and Da Xu (2012), business intelligence encompasses analysis of data with
the intention for uncovering the trend, insights as well as, patterns. In current times, the online
business of Target Australia-women clothing is highly on trend. There are different things that
move with high speed of light as well as, staying on trend indicates developing reports as close to
synchronized as possible.
In contrast to this, Kolkas El-Bakry and Saleh (2014) stated that business intelligence enables
Target Australia-women clothing for optimizing the prices of items at right time as per upcoming
trends as well as, what consumers have purchased earlier. Assessing and measuring information
is essential for Target Australia-women clothing in terms of enhancing market positioning. With
the added rivalry of Target Australia-women clothing such as The Iconic, Myer, Glassons and
Rebel retailers should apply prompt data-driven ways for making the best decision.
Best BI technique to introduce the project in the context of Target Australia-women
clothing
As per the view of AL-Shubiri (2012), Sisense is a significant leader in BI market as well as, it is
the winner of best BI software award for 2016 from Finances Online due to renowned business
software review channel. This technique is competent to significantly simplify difficult data

DATA ANALYTICS AND BUSINESS INTELLIGENCE 7
analysis and creates accessible big data insights for Target Australia-women clothing. The
competitive edge related to Sisense is primarily its capability to collect information through
several sources without expensive preparations. These sources could be Google Analytics,
AdWords, and Salesforce.
In contrast to this, Prakash and Sarma (2011) stated that icCube is an end to end BI platform of
SaaS that is proficient to be entrenched in the application within Target Australia-women
clothing. Furthermore, its deployment on premises in clouds as well as makes utilization of one
of their managed facilities. There is a need for less time period to market for requesting the
custom features in Target Australia-women clothing. It combines the faultless application due to
on-the-fly-authentication as well as, authorization. The competency for connecting and
integrating the custom data sources, web-based dashboard builder, direct access to R and Java as
well as, competency to graphically design widgets through scratch within Target Australia-
women clothing.
Relationship between Data Mining (DM) and BI in the context of Target Australia-women
clothing
As per the opinion of Sherman (2015), data mining is related to the procedure of going through
large data set in order to address the feasible as well as, pertinent data. But, Target Australia-
women clothing should access to a smaller and more particular set of information. Target
Australia-women clothing implement data mining in the context of business intelligence and to
address the particular information that can support their corporation for making better
management as well as leadership decisions.
On the other side, Rajamani and Sheela (2018) evaluated that data mining is the procedure of
addressing solutions to concerns that Target Australia-women clothing did not understand what a

DATA ANALYTICS AND BUSINESS INTELLIGENCE 8
customer is looking for earlier. For instance, discovering new data source can lead to addressing
the causes for financial shortcoming as well as, underperforming workforces of Target Australia-
women clothing. Quantifiable data shows the information that cannot be understandable from
standard scrutiny.
Different DM techniques in the context of Target Australia-women clothing
As per the view of Jurek et al. (2014), data mining can be highly significant so long because it
focuses on one or more tool. Tracking patterns is one of basic tool of data mining that helps to
address the patterns in sets of data within Target Australia-women clothing. It is recognition of
some deviation in obtaining the data at regular intervals and flow or ebb of a specific variable
across time. For instance, Target Australia-women clothing can identify the sales of some
products that seem to spike just before the holidays as well as notice that warmer weather leads
to a high amount of individual towards its websites.
In contrast to this, Mach and Abdel-Badeeh (2010) stated that classification is complex data
mining tool that forces business for gathering the several attributes together into the discernable
categories of Target Australia-women clothing. It helps to draw a valid conclusion and
implements some more functions. For instance, when Target Australia-women clothing is
evaluating the information on the financial background of individual customers, and purchase
histories, the company may be competent for classifying them as low, medium or high credit
risks. Target Australia-women clothing can then use these classifications for learning more about
those consumers.
On the other side, Ghazanfari Jafari and Rouhani (2011) stated that association is linked with the
tracking patters. However, it is more complex to dependently relate the variables. In such a case,
Target Australia-women clothing will focus on particular attributes and events that are highly

DATA ANALYTICS AND BUSINESS INTELLIGENCE 9
connected with other attributes and events. For instance, Target Australia-women clothing may
notice that when a customer purchases a particular item, then they often purchase a second
associated item. It is commonly what is used to populate like “people also bought” sections
related to online stores.
Best DM strategy for their project and link with the project’s BI adoption in the context of
Target Australia-women clothing
As per the view of Loshin (2012), audit logs do not offer data for separating the type of user
hence, Power BI report using audit information that could be easily improved for categorizing
the users as per the known profiles. Cycles of prototyping can be considered through spikes in
adoption. Different usage structure could be a signal for adopting issues. For instance, the usage
structure of Target Australia-women clothing can emerge while superuser transforms the model,
and reports constantly. It can confound the customers, who may have shared certain initial
enthusiasm, but are no longer assure what to predict next time they right to use the report.
In contrast to this, Khan and Quadri (2014) stated that audit logs do not dictate the technique in
order to track the adoption and tracking usage. But as a company plan for deployment, Target
Australia-women clothing can likely have an assumption regarding how it intends the power
users, super users as well as consumers in order to leverage power reporting of business
intelligence. By explicitly demonstrating the expected usage structure, business intelligence
within Target Australia-women clothing can corroborate implementation as well as proactively
make corrective measures while log data shows the user behavior that cannot conform to
predictions.
Methodology
Research philosophy and approach

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Research scholar has exercised interpretivism research philosophy as it delivers favourable result
with inductive research approach. It is also selected to gather the real phenomenon regarding
research issues. Along with this, the inductive research approach is considered by developing the
theory about the research issues (Tajani, et. al., 2016).
Research design
In this dissertation, both types of research design qualitative and quantitative have used by the
researcher. In Qualitative research, theoretical information related to research concern is
collected by using a literature review method. On the other hand, in quantitative research design,
numerical data is accumulated by practicing survey through questionnaire method (Fitriana,
Eriyatno, and Djatna, 2011).
Data collection method
Investigator has practiced both primary and secondary data gathering techniques for this research
study. Primary data is fresh and new data which is gathered by using a survey through
questionnaire. Whereas, secondary data is attained by several existing sources which are articles,
journals, books, online and offline sources (He, et. al., 2015).
Research strategy
In this research, survey through the questionnaire is used for gathering the primary information.
For conducting the questionnaire, the researcher has taken prior consent to the manager. Along
with this, in designing the questionnaire, the researcher has used a close-ended questionnaire
structure and Likert scale method for creating the interest of employees towards the survey (Lee,
2017). Online Google form is used for conducting the survey through questionnaire.
Sampling

DATA ANALYTICS AND BUSINESS INTELLIGENCE 11
In this investigation, research scholar has practiced a probability sampling method and under
this, random sampling technique has executed to select the research participants randomly. It
assists the researcher to eliminate the biases from the research and also provides a similar
opportunity to each respondent for sharing their beliefs and opinion regarding proposed solution
in the adoption of business intelligence and develops the strategies in the context of women
clothing of Target Australia. 50 employees of Target Australia women clothing company has
selected by the investigator to conduct this research (Shen, et. al., 2015).
Experiment and/or methods followed
Data analysis method
In this research, the statistical data analysis method is used for analyzing the gathered data
regarding the research issue. Along with this, MS-excel software is used for analyzing the
information and represents the data through a different pie chart, bar graph as well as column
diagram. It is beneficial for gathering comprehensive information regarding research issues
(Trieu, 2017).
Ethical consideration
In this investigation, the researcher keeps the confidentiality of participants and do not disclose it
during and after the research. Moreover, the researcher will take prior consent with the manager
to conduct the survey through a questionnaire on their employees. This researcher is beneficial
for ethically conduct the research (Ittmann, 2015).
Survey through questionnaire
Demographic-based questions
Q1: Please specify your gender
Male

DATA ANALYTICS AND BUSINESS INTELLIGENCE 12
Female
Q2: Please mention your age group
20-24 years
25-28 years
29-32 years
32 or above years
Q3: Please specify your experience in Target Australia-women clothing
Less than 1 year
1-3 year
4-6 years year
More than 6 years
Objectives based questions
RO1: To identify the business need for business intelligence: In the context of Target
Australia-women clothing
Q4: Do you agree that business intelligence encompasses analysis of data with the intention
for uncovering the trend, insights as well as, patterns?
Strongly agree
Agree
Neutral
Disagree
Strongly disagree
RO2: To discover the best BI tool for introducing the project: In the context of Target
Australia-women clothing