Big Data and Decision Making

This assignment delves into the role of big data in modern decision-making processes. It examines how large datasets are leveraged to gain insights and make informed choices across diverse sectors like healthcare, finance, and supply chain management. The analysis covers theoretical concepts, practical applications, and ethical considerations associated with big data-driven decisions.

Running head: DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
Developing a Big Data Strategy for Commonwealth Bank
Name of the student:
Name of the university:
Author Note

1DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
Executive summary
The big data analytics is helping various organizations to harness their data and utilize that for
identifying the latest scopes. The big data has turned into a huge deal for the Commonwealth Bank
that has been changing the way how the customers could pay and quickly the business gets paid. The
report has analyzed the organizational analysis, big data strategy and multi-dimensional analysis.
Moreover, the case of NoSQL for big data analytics and lastly the role of social media in the process
of decision making are also considered here.

2DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
Table of Contents
1. Introduction:......................................................................................................................................2
2. Organizational Analysis.....................................................................................................................3
2.1. Nature of the business:................................................................................................................3
2.2. SWOT analysis:..........................................................................................................................3
2.3. Stakeholder analysis:..................................................................................................................4
2.4. Business pressure analysis:.........................................................................................................5
2.5. The need for developing big data strategies:..............................................................................6
3. A Big Data Strategy...........................................................................................................................6
3.1. State the big data strategy that the organization wants to adopt:................................................6
3.2. Initiatives that Commonwealth bank needs to take:...................................................................7
3.3. Outcomes of every initiative and critical success factors:..........................................................7
3.4. Specific tasks for each initiative.................................................................................................7
3.5. Sources of big data for supporting such tasks:...........................................................................7
4. The Use of Big Data Technology for Supporting the Big Data Strategy:.........................................8
5. Multi-Dimensional Data Analysis for Decision Support.................................................................10
5.1. Define data analytics and multi-dimensional data analysis and discussing their importance. .10
5.2. Use of data analytics and multi-dimensional data analysis to support decision making in
organizations:...................................................................................................................................10
5.3. Types of data analytics could be used under the proposed big data strategy to support the
decision making...............................................................................................................................11

3DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
6. NoSQL for Big Data Analytics:......................................................................................................11
7. Different NoSQL Databases and Their uses:...................................................................................12
8. Role of Social media in decision making process:..........................................................................12
9. Big Data Value creation in organizations:.......................................................................................13
10. Conclusion:....................................................................................................................................13
11. Recommendations:.......................................................................................................................14
12. References:....................................................................................................................................17

4DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
1. Introduction:
The big data analytics has been helping the companies to harness their data and utilize that
for identifying the latest scopes. In turn this has been leading to smart business approaches, higher
profits, happier customers and efficient operations (Provost and Fawcett 2013). Its presence has left
impact on cost reduction, faster and better decision making and latest services and products.
There has been no definite technology encompassing the big data analytics. There has been
various advanced analytics applied to the big data. However various kinds of technology have been
working together for helping to retrieve the best value from the data. The biggest players lying here
are the data mining, data management, text mining, predictive analytics and in-memory analytics.
The big data has been a big deal for the Commonwealth Bank that has been changing the
way how the customers could pay and quickly the business get paid. Daily settle and the other
merchant solutions and the mean funds have been quickly credited to the clients account regarding
invaluable insights and real results.
The report aims to analyze the new decision making techniques under the light of big data.
The fundamental objective is to undergo through a theoretical analysis providing a clear
understanding.
The study has included the organizational analysis, big data strategy and multi-dimensional
analysis. It has considered the case of NoSQL for big data analytics and lastly the role of social
media in the process of decision making.

5DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
2. Organizational Analysis
2.1. Nature of the business:
The Commonwealth Bank has been delivering various economic services. This includes
business, retail and institutional banking, superannuation, insurance, funds management, broking and
investment services (Provost and Fawcett 2014).
2.2. SWOT analysis:
SWOT Analysis
Strength Weakness
The bank posses a strong revenue and
rising profit
The bank has witnessed the loan
impairment.
Opportunities Threats
Implementation of the technology at the
core banking activities could help to
increase the quality of services.
The bank could face risks because of
changes in foreign exchange rates.

6DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
Promoters Defenders
Latents Apathetics
Interest of stakeholders
Influence of stakeholders
2.3. Stakeholder analysis:
Figure 1: “Stakeholder Analysis at Commonwealth Bank”
(Source: Www1.worldbank.org, 2017)

7DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
Globalization
Government regulations
Customer demand
Collaboration of partner
New vendors
New models of business
Decisions
Predictions
Analyses
The integrated computerized decision support
Business
Intelligence
Business
Environmental
factors
The response of
Commonwealth
Bank
Decision and support
Pressures
Opportunities
2.4. Business pressure analysis:
Figure 2: “The business pressure analysis at Commonwealth Bank”
(Source: Markets.theaustralian.com.au, 2017)

8DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
2.5. The need for developing big data strategies:
Since the customer relationships have been disrupted by the technological upheaval at the
sector, the big data strategies have turned out to be one of the largest strategic focuses for the
Commonwealth Bank at Australia.
3. A Big Data Strategy
3.1. State the big data strategy that the organization wants to adopt:
Holistic:
For setting the basis for the long term success, the companies require the big-picture viewing
that identifies the various distinct elements of the effective system.
Focusing on business:
The strategic planning regarding the big-data must be led by business.
Flexibility:
The strategies should account for the creation of the incremental value and the overall
evolutionary process.
Scalability and structure:
The primary step has come forward by the adaptable and powerful ecosystem linking the
discovery and the data platforms. This has been regarding the long-term scalability and connects to
the crucial external sources (McLeod et al. 2017).

9DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK

10DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
3.2. Initiatives that Commonwealth bank needs to take:
Commonwealth should think how to accelerate the innovation and predict the trends of the
seasonal demand. They must find out the most effective supply chain partners and uncover the
unnecessary costs of overhead.
3.3. Outcomes of every initiative and critical success factors:
Whether Commonwealth Bank performs the personalization of the promotional offers or the
loyalty programs for various client segments, the big data could deliver the insights for helping to do
that quickly and with more sustainably.
3.4. Specific tasks for each initiative
In order to keep the proper strategy in place, a unified and strong architecture to make that
accessible could be used (Raghupathi and Raghupathi 2014). For creating the best value from the
investments of big data investments, daunting and addressing the question regarding what to do with
these data must be done.
3.5. Sources of big data for supporting such tasks:
The NoSQL or Columnar data sources include the InfoBright, Cassandra or MongoDB are
the instances of the latest kinds of map reducing repository and the data aggregator.

11DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
4. The Use of Big Data Technology for Supporting the Big Data Strategy:
Big data
technologies
Characteristics Discussion Implementation
Hadoop It stores data and
run applications on
the clusters of the
commodity
hardware
It has huge data storage
for any type of data with
outstanding power of
processing.
As the security projects like
Rhino, Sentri and others
achieves stability, the
implementation of Hadoop
expands.
Cloud solutions It provides perfect
scalable resolution
to manage large
volume of
information.
As the Internet of Things
has been spreading in the
market place, the
generation of data is on
rise. There have been
various advantages of
Hadoop on the cloud in
order to sustain various
big data technologies.
This could be implemented
either by taking the server
and put that on anyone
else’s data centre or by
having a service provider
managing the devices.
Self-Service Big
Data
applications
This simplifies the
data preparation,
data cleaning and
the tasks of data
exploration.
The tools such as the
Hadoop and Tableau is
been rising in popularity
in the last few decades
(Demirkan and Delen
Regarding implementation,
it must be kept in mind that
the bank has to evolve
beyond the spreadsheets and
IT. They should nor settle

12DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
2013). This highly
reduces the efforts of
end-users.
for what they already had
and generate a core
community of data.
Revolutionizing
of traditional
database
This has been
consisting of the
structured data
For managing and
processing the data, the
NO-SQL databases are
the best choice since the
previous few years.
The NO-SQL data bases
like the Cassandra and
MongoDB would be getting
more implemented by the
vendors (Nguyen and Cao
2015).

13DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
5. Multi-Dimensional Data Analysis for Decision Support
5.1. Define data analytics and multi-dimensional data analysis and discussing their importance
Definition Importance
The data analytics or DA has been the
method to examine the datasets.
This helps in drawing the conclusions regarding the
data that remains rising with the aid to specialized
software and system.
The multidimensional analysis if the
process of data analysis in the field of
econometrics and statistics.
It helps in grouping data into two sections, the data
measurements and data dimensions (Janssen, van der
Voort and Wahyudi 2017).
5.2. Use of data analytics and multi-dimensional data analysis to support decision making in
organizations:
The data analytics has been created on the strong grasp of the probability and statistics. These
skills have been utilized to support the decision making. Moreover the big data scales that up
(Sagiroglu and Sinanc 2013).
Through the adoption of the multidimensional technology of data analysis to the statistics
helps in analyzing the basic data of the banking industry. Thus the analyses of the results are yield
for the decision making.

14DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
5.3. Types of data analytics could be used under the proposed big data strategy to support the
decision making
Types of data analytics Discussion
Prescriptive This reveals the type of actions to be taken.
These results in recommendations and rule for
the following steps.
Predictive This analyzes the suitable situations that could
take place. Here the deliverables are generally
of the predictive forecast.
Diagnostic This look at the previous performance for
determining what have occurred and why. The
outcome of the analysis has been the analytic
dashboard (Bailey 2016)
Descriptive There the occurrence has been based on the
incoming data. For mining the analytics the
real time dashboard is used.
6. NoSQL for Big Data Analytics:
With the emergence of the different NoSQL software platforms, the IT business executives
and managers are involved in the technology possess more choices on the database deployments.
The NoSQL databases have been supporting the dynamic design of schema. This has been delivering
the potential for the rise in customization, scalability and flexibility compared to the relational
software. The NoSQL databases have been disrupting the software monopoly (Pedrycz and Chen

15DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
2015). They have dented the dominance of the relational databases. However this has not been likely
to be fully broken holding that the SQL technologies have on the users. The NoSQL databases have
been scaling upward for the cloud computing.
7. Different NoSQL Databases and Their uses:
Types Uses Examples
Key-Value Store It posses the Big Hash Table
of keys and values
Amazon S3, Riak
Graph-based It uses the edges and the nodes
for representing and storing
data
Neo4J
Column-based Store Every storage block has the
data from only one single
column (Gandomi and Haider
2015).
HBase, Cassandra
Document-based Stor
e
This stores the documents that
are made up of the tagged
elements.
CouchDB
8. Role of Social media in decision making process:
As it comes to the preparation of the decision making process, there have been various
factors how the buyers could use the social platforms that are to be considered. This includes, what

16DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
sites are visited, why are they be used and when the process of decision making are have been
viewed by them. The source of social influence and the activities of social platform have notably
influenced them (Liebowitz 2014). The consumers could use the online sources for obtaining the
product information vital for the purchase decisions. This has been love of the hyping social media,
but inability in realizing what requires to be done to adopt the social media at Commonwealth Bank.
They could perform anything that is under their power for creating the mentions of their brand and
they could make sure that there have been positive mentions.
9. Big Data Value creation in organizations:
Before the Commonwealth Bank joins that rush for spending the more over big data, it has
been salutary in considering what has been really worked and which capabilities of management is
needed by the bank. This is done to retrieve the value from the big data. The central finding has been
that this has neither been the data itself nor the distinct data scientists (Power 2014). Moreover, the
value creation takes place by the process of data management. Here the managers have been capable
for contextualize, experiment, democratize and execute the data insights in a periodic manner.
10. Conclusion:
Though the commonwealth Bank has undertaken every effort for ensuring that the data has
been error free, nevertheless no surety has been given to the completeness and accuracy. Any
estimates or opinions expressed herein have been those of the bank on the data of preparation.
Moreover, this has been on the subject to change without any notice. Despite this no such estimates
or opinions constitute investment, legal or any other advice. Commonwealth Bank must find the
independent investment, legal or the proper advice from the suitably qualified or the regulated and
authorized advisor. This is before making any investment, legal or the other decisions. This has been

17DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
meant for the purposes of information only. Further this has not been intended as any
recommendation or offer to sell, buy or otherwise deal in the privacy or securities. The big data tools
have currently existed for allowing the multiple channels for understanding. The procedures and
polices manuals could remain. Now, the bank could use the tools of data measurement for easily
tracking how frequently they have been accessed. They could generate and store the user-generated
content like short instructions videos, blog posts, social media or job aids and then track the access.
Through learning of the big data to study personalization the Commonwealth Bank have been not
only expanding the amount of learning scopes but also could deepen the impact of the learning. They
no longer require to be constrained by the lack of data that forces learning on their audience in the
way they could not prefer. Various modalities of the similar data have been no longer meaning the
training department has been inconsistent or unfocused. Through the leveraging the data according
to the preference of the learner, the Commonwealth Bank have been consistently changing the
learning landscape. This is optimized for every person for allowing them to discover, explore and be
rewarded for the discoveries. This has been the latest method to imagine how the big data could help
designing the best robust solutions of learning.
11. Recommendations:
The recommendations are described below:
1. Customer-centric outcomes:
The Commonwealth Bank has been focusing their strategies of big data on the efforts that
could deliver the most effective value of business. This indicates that beginning the strategy of
analytics with the customer analytics for providing the clients with better services. This in turn must
leas in better retention of customer. The outcome is that the Commonwealth Bank would require

18DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
understanding their clients as the individuals. They require investing the advanced analytics and new
technologies for doing this.
2. Enterprise-wide big data blueprint:
The blueprint of their big data strategy must cover the entire vision. The strategy and the
necessities should not be on the departmental basis. This must be on the enterprise basis. It might
lead to the creating of the enterprise-wide common understanding regarding how the bank expects to
utilize the usage of big data, hardware and tools required for making the blueprint in actuality. With
this the bank must be able to recognize the primary challenges of the business to get overcome with
the business process necessities defining how the big data could be used.
3. Start with existing data:
For achieving the short-term outcomes as the implementation of big data begins and collects
steam. The enterprises require becoming realistic regarding what they could achieve at first. For the
people who have imposed the successful strategy that is delivering the business value already, the
simplest space to collect insights has been from the information that has been in the bank already.
4. Business priorities and skills investments:
As the marketplace gets matured, the businesses have been forced to opt between the rise
number of the analytics tools and having to deal with complicated shortage of the analytics tools at
Australia. The success of the big data has hinging to find the way across that.
5. Measurable outcomes:
For developing the viable strategy of big data and assuring that there would be the ongoing
investment and interest from the decision makers. The enterprises require assuring that case

19DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
regarding the current investment has been on the basis of the quantifiable outcomes of business. This
means that the business leaders of Commonwealth Bank must be capable for seeing the benefits.
Commonwealth could do this through assuring that there has been the active sponsorship and
involvement from the business leaders. This must take place as the original strategy gets developed
and the initial implementation occurs. Moreover the vital importance here has been the current
cooperation between the IT departments and business. This must assure that the business value of the
investments in analytics of big data has been understood properly.

20DEVELOPING A BIG DATA STRATEGY FOR COMMONWEALTH BANK
12. References:
Bailey, M., 2016. 12 Will Big Data Diminish the Role of Humans in Decision Making?. Big Data Is
Not a Monolith, p.163.
Demirkan, H. and Delen, D., 2013. Leveraging the capabilities of service-oriented decision support
systems: Putting analytics and big data in cloud. Decision Support Systems, 55(1), pp.412-421.
Gandomi, A. and Haider, M., 2015. Beyond the hype: Big data concepts, methods, and
analytics. International Journal of Information Management, 35(2), pp.137-144.
Jagadish, H.V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J.M., Ramakrishnan, R. and
Shahabi, C., 2014. Big data and its technical challenges. Communications of the ACM, 57(7), pp.86-
94.
Janssen, M., van der Voort, H. and Wahyudi, A., 2017. Factors influencing big data decision-making
quality. Journal of Business Research, 70, pp.338-345.
Kaisler, S., Armour, F., Espinosa, J.A. and Money, W., 2013, January. Big data: Issues and
challenges moving forward. In System Sciences (HICSS), 2013 46th Hawaii International
Conference on (pp. 995-1004). IEEE.
Liebowitz, J. ed., 2014. Bursting the big data bubble: The case for intuition-based decision making.
CRC Press.
Markets.theaustralian.com.au. (2017). The Australian - CBA Profile. [online] Available at:
http://markets.theaustralian.com.au/shares/CBA/commonwealth-bank-of-australia [Accessed 3 Sep.
2017].