Highlighting OLAP Cube's Role and Importance in Customer Management

This project investigates the role and significance of OLAP Cube in online customer management within the Australian retail industry, using Catch.com as a case study. The research aims to understand the concept of OLAP Cube, identify its roles in customer management, and determine its importance for online consumers. The project employs a positivism research philosophy, a deductive research approach, and a survey strategy for data collection. It will address research questions through primary and secondary data collection, including a questionnaire for primary data and literature review. The research will contribute to the economy, communities, society, and culture by providing insights into how businesses can improve customer management using OLAP Cube and enhance their performance. The study will use a cross-sectional time horizon and probability sampling, selecting 40 customers of Catch.com. The project will also discuss the potential contributions to the discipline and the broader economy, highlighting the benefits of OLAP Cube in data analysis and customer relationship management within the retail sector.

Research Higher Degree Students
1. Project title
Highlighting the role and importance of OLAP Cube in online customer management in the retail industry of Australia. A
study on Catch.com
2. Project summary
Aim of this project is “To understand the role and significance of OLAP Cube within online customer management within retail
industry of Australia.” Also, the case which has been taken into consideration is Catch.com. Primal significance of conducting
investigation on the chosen topic is that, it will help researcher to gain knowledge in relation with role and importance of OLAP
Cube for managing the customers within retail industry of Australia (Rajola, 2019). With the help of this, business-focused
multidimensional data and calculations can easily be performed in rightful ways by Catch.com. Also, detailed information in
relation with OLAP Cube, researcher may become able to gain ample number of opportunities in near future, which will help in
getting promoted within the organisation.
3. Project details
3.1. Introductory background
Over the years, many organisations are looking forward to improve customer management system, where OLAP Cube is
considered to be a crucial multi-dimensional array of data, which helps in performing online analytical processing that aid a
company in gaining insights to the business operations and aid in taking right decisions in correct time. Firm, which has been
taken into consideration is Catch.com where the operations that are performed by this company is related with bringing low
prices to everyday Aussies on the brands they know and doing business as online retailer from 2006. Basically, this organisation
was dealing with ample number of issues, where managing information of new and existing customers was considered to be the
crucial one. This impacted negatively on overall performance level of Catch.com because it affected decision making process of
the company. For better performance, this organisation is looking forward to improve online customer management system. In
present context, OLAP Cube is said to be a crucial customer management system, which would aid a company in improving
management of customer's information (Signori and et. al., 2019).
3.2. Research questions and brief evidence from literature
Research Gap: There are many investigations that are already performed by various investigators in relation with OLAP Cube in
past few years, where they have presented information in relation with benefits of this particular multi-dimensional array of data
and how they have have impacted on overall working of organisations. However, there are a few investigations only that has
given the information about what are the roles played by OLAP Cube and its importance, which only presented limited data in
relation with the same. This is why, topic i.e. highlighting the role and importance of OLAP Cube in online customer
management in the retail industry of Australia has been taken into consideration as this research project will present detailed
information in regards to role and significance of OLAP Cube to improve customer management system (DE MARCO, 2018).
Research Questions:
 What is the concept of OLAP Cube?
 What are the roles played by OLAP Cube in online customer management for Catch.com?
 What are said to be the importance that can be seen of OLAP Cube while managing online consumers?
3.3. Aims/objectives of the project
Aim: To understand the role and significance of OLAP Cube within online customer management within retail industry of
Australia. A study on Catch.com.
Research Objectives:
 To understand the concept of OLAP Cube.
 To identify the roles played by OLAP Cube in online customer management for Catch.com.
 To determine the importance that can be seen of OLAP Cube while managing online consumers.
Research question or problem to be addressed:
The research questions will be addressed considering both primary and secondary data collection tools, which will help in
gaining detailed information in relation with the chosen topic i.e. To understand the role and significance of OLAP Cube within

online customer management within retail industry of Australia (specific research will be conducted on Catch.com).
Research Methodology:
Research philosophy: Positivism and interpretivisim are the two crucial philosophies that are taken into consideration by
researcher while conducting most of the investigations. In present research, positivism research philosophy is specifically being
considered which will help in evaluating, collecting, and also using the quantitative data without taking additional time or even
the resources as well.
Research Approach: Over the years, investigators are using two different approaches and these are inductive and
deductive. In order to collect relevant data while performing quantitative investigation, deductive research approach is performed
(Dinh, 2018).
Research Strategy: Case study, experimental, survey, and mare said to be some of the crucial research strategies
that are undertaken by researchers according to the topic. Survey will be conducted in present research report, which will help
researcher in collecting primary data in relation with role and significance of OLAP Cube within online customer management
within retail industry of Australia.
Research choice: There are two major types of researches performed by investigators and these are quantitative and
qualitative. In present context, researcher has taken into consideration of quantitative research, because the chosen topic will be
delivering accurate data, which will help researcher to reach to a conclusion of pulling out favourable outcomes about what are
the major roles and importance of OLAP Cube to manage information in relation with customers in rightful ways.
Data Collection: Secondary and primary are said to be the two crucial research methods that are connected with most
of the investigators in order to performing investigations to collect data. Away with this, in present research questionnaire will be
used for gathering primary information, whereas, for gathering secondary information, books, magazines, articles etc. sources
will be used for literature review.
Time Horizon: Cross-sectional time horizon along with longitudinal time horizon are two different types of horizons are
considered by the investigators while conducting investigations. In present research project, researcher will be considering
cross-sectional time horizon will be applied because it is based on actual situation and also not takes maximum time in research
completion.
Sampling: It is the process which is used by researcher for selecting sample from the total population. Probability and
non-probability are two techniques of sample selection. In this project, probability sampling is essential because it helps in
selection of larger sample in less period. 40 customers of Catch.com will be selected in random basis under the probability
technique.
Research Ethics: There are various principles of research ethics including protection of confidentiality and anonymity
of research participants, avoid using descriptive practices, reduce the risk of harm to participants, obtain informed consent, etc
(Mahanti, 2019). These are main principles that must be use by researcher because it helps them in completion of research
project in ethical and systematic manner.
Significance/contribution to the discipline
Literature review is considered to be a crucial element, which helps researcher in enhancing knowledge about different aspects
of a particular topic. Considering this as a research method, researcher may effectively improve overall knowledge through
collecting data in rightful ways. In present context as well, if it is analysed then literature review will be helping research to gain
knowledge in relation with understand the role and significance of OLAP Cube within online customer management within
Catch.com, which is an organisation of retail industry of Australia.
3.4. Theoretical framework and methodology
Primal reason behind considering quantitative methodology in present research project will directly lead investigator to collect
outcomes in numbers, which stays much more relevant from any other research methodology like quantitative.
3.5. Contributions, revelations and future research
Considering this investigating topic, in near future researcher may effectively become able to improve his or her own knowledge
in relation with OLAP Cube. Through this, maximum benefits could be gained in short span and in rightful ways as well.
4. Please explain the potential contribution(s) your proposed research will make to the economy, communities
and society, the environment and/or culture, beyond the contribution to academic research. Where
possible, please explain how this impact might be realised
The topic i.e. highlighting the role and importance of OLAP Cube in online customer management in the retail industry of
Australia. A study on Catch.com, will be contributing on different areas and these are: economy, communities, society, culture

and so on (Ramos and et. al., 2019). Basically, some of the crucial aspects that can be seen considering this proposed research
project on economy is that, many other organisations may gain the knowledge of roles and responsibilities of OLAP Cube and
their impact on existing online customer management which has been adopted by them. Also, The principal advancement is a
basic result of Moore's law: figure and memory have become genuine items, and are presently both strangely modest and
effectively accessible by means of the cloud. Today, anybody with a working Mastercard can go to AWS or Google Cloud and
have a discretion’s incredible worker spun up for them in no time. This reality additionally applies to cloud-based information
distribution centres, organisations can store and investigate tremendous informational indexes with essentially zero fixed
expenses.
The subsequent advancement is that generally current, cloud-based information distribution centres have what is known as a
greatly equal preparing (MPP) engineering. The focal knowledge behind the advancement of MPP information bases is entirely
straightforward: rather than being restricted by the computational force and memory of a solitary PC, company can profoundly
help the exhibition of their question on the off chance that they spread that inquiry across hundreds if not a large number of
machines. These machines will at that point cycle their cut of the inquiry, and leave the outcomes behind the line for
accumulation into an end-product. The consequence of this work is that organisations may gain execution upgrades: Google's
BigQuery, for example, can play out a full regex coordinate on 314 million columns with no records, and return an outcome
inside 10 seconds.
One of the most important characteristics of OLAP systems is to facilitate the analysis of huge amounts of data. However,
querying and processing time can become day after day too significant. Thus, some works in the literature have carried out the
performance issue in data warehouse (DW) systems using partitioning solutions. Nevertheless, all of them have been focused
on the relational data warehouse and ignored the OLAP layer (Riker Jr, 2019).
In any case, one of the key difficulties of working with Big Data stages is that it is hard for clients to get to and control
information. Connecting existing BI devices onto the Big Data stage prompts a few presentation issues. Conventional BI devices
are intended to work with social information base administration frameworks (RDBMSs) and use SQL for questioning
information. At the point when associated straightforwardly to the Big Data stage, question execution debases essentially as
running intelligent SQL inquiries on enormous datasets is an incredibly tedious cycle.
Despite the fact that most customary BI apparatuses have experienced a few patterns of upgrades to improve their capacity to
manage Big Data, they are as yet incapable to convey bits of knowledge at a speed that coordinates the desires for the present
quick moving business conditions. Therefore,
5. Please clearly state the proposed research question and sub questions that your research thesis would
attempt to answer (max 250 words)
Research Questions:
What are roles and significance of OLAP Cube within online customer management within retail industry of Australia.
Objective: The objective of this question is to justify different roles and importance of OLAP Cube in one of its important sector
that is online customer management. The question specifically focuses on the retail industry in Australia. Therefore, the research
conducted will be based upon the Australian market and customers available for OLAP Cube.
What is the concept of OLAP Cube?
Sub Objective: The objective of this question is to justify basic nature or concept of OLAP Cube. This includes utilisation of
OLAP Cube along with the basic function of this system. It can also include importance of OLAP Cube for its customers. It is
necessary to identify concept of system in order to analyse it and conduct the research successfully (Bimonte, Ren and Koueya,
2020).
What are the roles played by OLAP Cube in online customer management for Catch.com?
Sub Objective: Major objective of including this question in research is to understand the particular functions and roles that
OLAP Cube is playing for Catch.com. There are a number of roles of the system as explained in the first question. This question
discusses about particular roles for Catch.com.
What are said to be the importance that can be seen of OLAP Cube while managing online consumers?
Sub Objective: With the help of this question the researcher can specify the importance of OLAP Cubes that are seen while the
system is effectively managing its online consumers. The major focus on this question is paid upon the online customers that are
effectively managed by the system OLAP Cubes.
6. Please summarise your understanding of the study and research requirements of a higher degree by
research

After performing the investigation on the chosen topic which is to understand the roles and significance of OLAP Cube within
online customer management within retail industry of Australia, it can easily be said that it may help organisations to take right
decision in relation with the same. Also, it is must for future researchers to conduct investigation on some of the other areas as
well, like network because there are some of the other countries as well, where network connectivity is not that much strong like
African countries and it is much needed for this particular multi-dimensional data process to work on different elements because
then only overall productivity in relation with the same may effectively be grabbed in much effective and in efficient ways (Riker
Jr, 2019). Including this, in order to perform higher degree it can be said that researchers may take into consideration of mixed
methodology (blend of both qualitative and quantitative method), this will help researchers in focusing on different aspects in
much effective and in efficient manner.
7. References/Bibliography
Rajola, F. (2019). Customer Relationship Management in the Financial Industry Organizational Processes and Technology
Innovation. Springer-Verlag.
Signori, P., Gozzo, I., sull’Impresa, P. S. D. S., Bisutti, V., & Segato, S. (2019). DIGITAL CORPORATE IDENTITY
CONGRUENCE ANALYSES: HIGHLIGHTING CRITICAL ISSUES AND UNTAPPED OPPORTUNITIES. A FOCUS ON
ITALIAN SMES OF THE DAIRY INDUSTRY. In The 7th International Research Symposium of the SGBED.
DE MARCO, A. L. B. E. R. T. O. (2018). EFFICIENT BUSINESS INTELLIGENCE AND ERP SYSTEMS WITHIN SMES.
Dinh, L. (2018). Semantic manipulation and business context in big data analytics (Doctoral dissertation, Federation University
Australia).
Mahanti, R. (2019). Data Quality: Dimensions, Measurement, Strategy, Management, and Governance. Quality Press.
Ramos, C. M. Q., Casado-Molina, A. M., & Ignácio-Peláez, J. (2019). An Innovative Management Perspective for Organizations
through a Reputation Intelligence Management Model. International Journal of Information Systems in the Service Sector
(IJISSS), 11(4), 1-20.
Riker Jr, R. W. (2019). End-User Computing Satisfaction and System Use on Business Intelligence End-User
Performance (Doctoral dissertation, Capella University).
Bimonte, S., Ren, L., & Koueya, N. (2020). A linear programming-based framework for handling missing data in multi-granular
data warehouses. Data & Knowledge Engineering, 101832.