BIG DATA AND NEW DECISION-MAKING

TECHNIQUES/MODELS/APPROACHES

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Executive Summary

Big Data is required in an organisation to get access of large volume of data. In the present study,

Dominos, operating in Australia is taken into consideration. The study highlights business

strategies that are taken by Dominos for Big Data use case. A proper analysis is done based on

the business objectives, initiatives as well as tasks of the developed business strategy.

Furthermore, the study deals with different technology stack that can be used by the present

organization. Data Analytics as well as MDM is shown for supporting DS and BI. In addition to

this, the study sheds light in supporting NoSQL database in the Big Data Analytics, besides

showing different NoSQL databases that are used in Big Data. Social media role is highlighted

that helps in making decision-making and process of data value creation is discussed broadly.

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Table of Contents

Introduction......................................................................................................................................4

1. Discussion of business strategies for a Big data with use case reference to Dominos, Australia

.........................................................................................................................................................4

2. Analysis of business initiatives, objectives and tasks with developed Business strategy...........6

3.     Identification of required Technology Stack...........................................................................6

4.     Data Analytics and MDM for supporting DS and BI............................................................7

5.     Support of NoSQL Databases in Big Data Analytics..............................................................7

6.     Use of Different NoSQL Databases........................................................................................8

7.     Role of   social media in decision making.............................................................................10

8.     Discussion on the process of Big Value Data creation..........................................................10

Conclusion.....................................................................................................................................11

Reference list.................................................................................................................................12

Appendix 1: Use case....................................................................................................................15

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Introduction

Big Data can be defined as a large set of data that are analyzed computationally in order to reveal

patterns, associations and trends. Big Data aids an organization to know more about the

competitors, besides helping the company to adapt effective business strategy. Big Data

possesses extreme volume, variety and velocity of a large amount of data. Big Data is not the

only concern of this study but at the same time, it is supposed to analyze effective business

strategies with case reference to Dominos, Australia and how the company is using Big Data.

This current study will throw light on the influence of big data for providing better quality of

food, market analyses and making decision for running the business efficiently.

1. Discussion of business strategies for a Big data with use case reference to Dominos,

Australia

Dominos is now the world's largest pizza delivery chain having more than 10,000 outlets. Each

year, Dominos delivers more than millions of pizzas. This hugely successful business has been

possible only by the strategic management of the organization (Wang et al. 2016, p 750).

However, the company is boosting up their management system and business strategies by

applying smarter technologies. Big Data are the data that has huge volume which cannot be

easily captured or analyzed by any common software. The data are generated from various

sourcesand are structured as well as non-structured. Use case shows that the company is having

issues regarding unstructured data. The reasons are the company has the presence of Omni-

channel while driving sales, a large base of customers and had many touch-points to serve

customers. The company also expanded their order and delivery process by telephone orders,

online orders etc (Chen and Zhang 2014, p. 321).

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Figure 1: Dominos multiple channel

(Source: De Mauro, Greco and Grimaldi, 2015, p. 101)

In order to resolve these issues, the company takes help of software named LOB, for replacing its

age-old use of APM tool to enhance operational intelligence. This software helps the company to

segment six different applications. These are interactive mapping, real feedback, the updated

process for payment and supporting promotional activities. LOB software is used by present

organization, Dominos for business transaction. Interactive mapping helps the company to

calculate a total number of orders from all over Australia and count customer satisfaction (Bello-

Orgaz, Jung and Camacho, 2016, p. 52). Feedback from employees helps to judge employee

satisfaction. Dashboards help to keep track of set targets on monthly basis. Secured online

payment helps the company to increase trust among employees. When a customer is using

Dominos' service, LOB immediately records discounts that to be given, calculates the time of

responding and mode of order- online or in-store. These are data is forwarded and LOB indexer

relocates relevant data regarding customer response, purchasing time, number of sales etc in no

time (De Mauro, Greco and Grimaldi, 2015, p. 101). Promotion supports tracks how effectively

promotional discounts are influencing customer choice. Performance reviewing helps to improve

sales activities and service quality.

Information system:

Big Data policies have helped Dominos to determine effective business strategies. Information

system plays an important role in the market study and proper market study determines the future

scopes of the business (Cascetta et al.2015, p. 30). Collection of information is also a part of

strategic management. Point of sales system and data enrichment has added up to 85,000 of both

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structured and unstructured data sources in the company's information system. This is another

example of their successful business initiative.

New stores and products:

In order to reach more number of customers, the organization has the plan to open a number of

stores with more variety of .food items. That is why they have used the strategy for segmentation

and targeting (Wamba et al. 2015, p. 241). This segmentation is mainly based on demographic

and geographic factors. Big Data policies are effective to understand the taste of the customers of

both Australia and other countries. Therefore, the company produces their food items according

to the taste of the customers.

2. Analysis of business initiatives, objectives and tasks with developed Business strategy

In order to progress in a business, the organization needs to take proper business initiatives by

confirming specific goals and objectives. Domino's has pushed its brand through new and

developing technologies consistently.

Multi-channel approach:

The organization has used the multi-channel approach to interface their customers for capturing a

huge amount of data (Xu, Frankwick and Ramirez, 2016, p. 1564). Sensors such as RFID, Smart

Devices and IOT and so on are used as sensors and machine to machine such as Chatbots are

used by the mentioned company. It helps in generating data anywhere and at anytime. Moreover,

the present company uses Big Data to enhance the food sector and make on-time delivery and

making of foods. The data received from Big Data can be semi-structured, nano-structured and

structured. For instance it is obtained as Csv files, Audio, Video, xml, json, Document and so on.

Target customer:

The management of Domino's has identified their target customer in Australia so that they can

provide quality service and modify their productivity. In this sector, they have set their target on

the unified customer because it is easier to know the buying pattern of the customers residing in

a household rather than each customer (Hashem et al. 2015, p. 111).

Digital platform:

Digitalization is the biggest business initiative of the Domino's and they have utilized almost all

the digital platforms to advertise their brand including social media, such as Twitter, Facebook,

Instagram, LinkdIn and so on. The company has now the infrastructure to deliver 55 to 60

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percent of their order via online in various parts of Australia (Pedrycz and Chen, 2015).

3.     Identification of required Technology Stack

As stated by Wamba et al. (2017), technology stack stands as the list of technology that is used

for running a building single application. Dominos might use Hadoop sas technology in order to

store bulk amount data regarding processing power by using computing nodes and specially

information from social media platform. Using these nodes help to restrict hardware failure and

store data automatically without processing (Wang et al. 2018). By implementing Hadoop,

Dominos is expected to large scale data, for example, 250 GB in just a single machine by using

statistical languages, like R, Python etc. Moreover, each machine has 32 cores. This makes the

procedure more efficient in map-reducing work (Gandomi and Haider, 2015). Though the

technology has some drawbacks, for example, MapReduce programming is not the ultimate

solution to every problem because it relies on file-intensiveness. Another issue is that as map-

reducing requires advanced knowledge on analytic computing; it requires skilled employees and

becomes difficult for entry-level programmers (Sivarajah et al. 2017). However, as the process is

low cost and could be enlarged as much as required to add more data by increasing nodes, it

becomes less administrative.

4.     Data Analytics and MDM for supporting DS and BI

Introducing MDM in the enterprise has a positive effect on database and business intelligence

(Wamba et al. 2017). Example of MDM is DevOps. It stands for the architecture of the classic

data. If the organization does not possess the system of MDM and data analytics, then the

manager of the Dominos finds the data fractured in stores of multiple data. Therefore, in order to

create an integrated dimensional data within the BI system, the data user of Dominos can easily

make use of the tool of data integration for integrating master disparate data in the system of

multiple operations for building dimensions. Therefore, it can be said that BI stands as the place

for integrating and consolidating master data.

5.     Support of NoSQL Databases in Big Data Analytics

As commented by Wamba et al. (2017), NoSQL stands as the database technology that is driven

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by Web, Big Users, Cloud Computing as well as Big Data. The NoSQL is basically made for

overcoming the drawbacks that are faced by different organizations by the use of RDBMS

(Relational Database management System). Some examples of the companies using RDBMS are

Amazon, Google, Facebook and so on. In the present case, Australian Food Company, Dominos

can make use of NoSQL database as it stands alternative to database SQL. Wamba et al. (2015)

noted that NoSQL database does not make use of any table schemas. SQL requires table schemas

and are not structured. Dominos can focus only on NoSQL as it scales horizontally as well as

avoiding join operation of data. The present mentioned database is highly structured that

generally consist of the relational database.

NoSQL is used by Dominos for Big Data Analytics are Cassandra or Couchbase, HBase, instead

of the traditional RDBS. Sivarajah et al. (2017) commented that Big Data requires a flexible

model of data that requires a structured database. Dominos gets the benefit of messaging

infrastructure by using NoSQL database. In addition to this, NoSQL database within Big Data

can be used for gathering, storing, monitoring as well as logging data by the data user. Dominos

can use the present data for processing various data as well as monitoring the entire operation of

the organization. The NoSQL database is beneficial in exploding the volumes of data, a variety

of data as well as the increasing velocity of data. Furthermore, NoSQL database should be using

for the analytics of the Big Data as it helps in scaling horizontally with extra nodes addition

(servers of commodity database) to resource pool for easily distributing the load of Big Data.

Figure 2: Domino’s Big Data

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(Source: Sivarajah et al. 2017)

6.     Use of Different NoSQL Databases

Database NoSQL aids in making the database solution more reliable and easily available.

Different types of the mentioned database are as follows:

Key-Value Store

According to Bello-Orgaz, Jung and Camacho (2016), table of a big hash of values as well as the

table are contained in the present type of NoSQL. A different example that can be used in the

present case is Amazon S3, Riak and so on. In this type of storage, like Riak, it is important for

the person to properly decide what he or she wants to store. In the present case, Dominos,

operating in Australia can use the present key as it can be auto-generated and synthetic and the

value stands as the large object, such as BLOB, JSON, Sting and so on. Cascetta et al. (2015)

noted that in the present type of NoSQL, the hash table has the unique key as well as the pointer

for the particular data item. In addition to this, identical keys are found in the different buckets.

The present organization, Domino's, Australia can make use of the Key-value store as it would

help to improve the performance of the food company due to its cache mechanism, which

accompanies mappings. In order to read the value of the present NoSQL, it is important for the

mentioned company to know the bucket as well as the key as the actual key stands as the hash.

Business strategy can be enhanced by using the present type as it aids Dominos to identify data

sources, deal with each type of data, forecast trend and analyze the collected data.

Store of Document-based

According to Cheng et al. (2018), the document-based type of NoSQL aims at storing documents

that are made of different tagged elements. CouchDB stands as the example in the present case.

The data stands as the collection of the pair of key values. The mentioned company can use the

Document-based type of NoSQL to store the collected document which would represent names

of the specific food products of the stores. Moreover, the present type of NoSQL can aid the

company to embed the attribute metadata that is associated with the stored content. The data

sources include social media, demography, GPS, IOT, local events, traffic details, LOB and so

on (De Mauro, Greco and Grimaldi, 2015). The coding that can be used by Dominos operating in

Australia in the present case is JSON, XML as well as BSON.

Store of Column-based

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As opined by Eichorn (2018), in the store of Column-based NoSQL, documents are stored in the

cells, arranging the data in columns, instead of rows. It is easy to read as well as write the big

data in a column, rather than in rows. The present organization can use the mentioned type of

NoSQL as it would help the company to easily search any data, which are stored earlier. The

columnar database has the capability to store data in all cells making the search faster. The data

model in the present type includes column family, key, keyspace and column. BigTable of

Google, Cassandra and so on stands as the example which is found to be inspired from the

BigTable.   

Graph-based

Rigid form of the SQL, column, and table representation are not found in the Graph-based type

of NoSQL (Huda et al. 2018). In the present type, flexible representation of graphs is used for

addressing the scalability concerns. The graph structure makes use of nodes, edges as well as

properties that aims at providing adjacency of index-free. In the current type of NoSQL, data are

found to be transferred from the one model to another.

Use-case of Big Data

According to Lee et al. (2015), the use of big data is done by making use of graph database. The

current organization, Dominos in Australia can make use of Infinite Graph and InfoGrid as it

would be beneficial for the present company to represent complex information as well as

hyperlinked information. Therefore, Graph-based NoSQL stands most appropriate for the present

company to capture and generate huge data. The data can be then capitalized by Dominos for

improving the marketing efficiency.

7.     Role of   social media in decision making

Social Media plays a great role in aiding an organization to enhance their organizational

productivity by drawing the attention of a large number of customers at a time (Matthias et al.

2017). In the present case, Dominos is consistently pushing its brand on the developing tech,

which makes the company accept an order of Pizzas on smartwatches, TVs and so on. Facebook

is also used by the Australian customers to order Pizza of Dominos. Sun, Sun and Strang (2018)

noted that social media is making the food companies quick-service traditional restaurant to get

involved in digital e-commerce. Australian foodies get aware of the new products, such as Chocó

pizza, burst pizza and many more, which are being launched by Dominos, watching the ads on

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social media pages. Dominos also use social media for localizing the existing products. Vassakis,

Petrakis, and Kopanakis (2018) stated that organizations use social media for advertisement

purpose, besides improving the communication channel. The feedback on the social media aids

the mentioned company to understand the customer’s habits and needs. Dominos offers are

provided on social media for attracting new Australian customers, besides encouraging the

existing ones. Social media, therefore, provides the chance for the customers of Dominos to

easily get hold of the delicious and mouth-watering Pizzas of Dominos by scrolling the pages of

Facebook, Twitter and so on. Therefore, internet increases the sales of the present organization,

besides providing a quality experience to the customers. Moreover, social media aids the present

company to analyze its competitors in the Australian competitive market.

Figure 3: Dominos competitors

(Source: Chen and Zhang, 2014)

8.     Discussion on the process of Big Value Data creation

Establishing a proper link between enterprise and Potential Big Data

As opined by Wamba et al. (2015), the mentioned process helps in driving the effort of the Big

Data on targeting the existing processes as well as procedures. In addition to this, it helps in

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providing the recommendation in improving the decision quality of the data user. This would

help in improving the precision of making the internal decision. The mentioned process would

even help in improving the experience of the Domino's customers, besides reducing the IT

support cost for business intelligence (BI) warehouse environment. The creation of the Big Data

can aid Dominos, operating in Australia look at the monetization opportunities.

Assess interplay of technologies of Big Data

Once the link is established between the enterprise business and Big Data, it is important for the

organization to navigate the BI or DW traditional technologies (Chen and Zhang). Dominos, the

current organization can break the technology ‘Big Data' into four different buckets. The buckets

include a layer of source data, Extract or ETL, Load Layer and Transform. In addition to this, the

other layers are visualization layer and analytics layer. The technologies requires for creation of

Big Data are forecasting, machine learning, analyzing, transforming, storing, cleansing as well as

generating reports (Wamba et al. 2017).

Recognising that model of execution is different for Big Data

Execution Model stands as the major factor behind the successful creation of the Big Data. The

mentioned model requires proper planning and consideration (Sivarajah et al. 2017). In the

present case, Big Data needs the proper combination of the expertise in the business domain,

modeling strategic skills and strong analytics. It is important to note that the mentioned skills are

generally absent in present organization and it only focuses on the function of centralized

planning. In order to bring success to the creativity of Big Data, the mentioned company needs to

include both unstructured as well as structured data under the environment of centralized DW or

BI. Proper creation of the journey of Big Data would, therefore, benefit Dominos to shape the

experience of the customers, launch new food items, and increase spending for developing the

culture of the organization and so on.

Conclusion  

It can be inferred from the above discussion that the technology of Big Data provides Dominos,

operating in Australia to get access to large volume of data. It would help the company to increae

sales as well as customer’s experience. The importance of NoSQL has highlighted in the study

that it is highly structured and is best suited for storing Big Data. Different types of NoSQL

database is mentioned such as Key-value store, Document-based, column-based and so on.

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Social media role is mentioned that aids the manager of Dominos in decision-making. In addition

to this, the process of the creation of successful Big Data is provided vividly in the current study.

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Appendix 1: Use case

Source: dominos (2018)

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