Big Data Capabilities: Management Proposal for McDonald's (INFS 5095)

This report presents a management proposal for McDonald's to implement big data capabilities. It discusses the fundamental concepts of big data, McDonald's key business priorities, and how big data can address challenges like customer satisfaction and service speed. The proposal outlines ...Read More

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Big Data Basic

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Executive Summary
Big data refer as a data set that can be used to analyse a large amount of data and it is a
very popular technology that handles both structured and unstructured data. It is
defined as a collection of data which is very large in size and it has the potential to
maintain the complex data. In this report, a big data technology will be developed for
McDonald Company and fundamental concept of big data will be discussed. McDonald is
an American fast food company that provide food services to their customer but they
are not able to handle more complex and large data for which a new approach can be
adopted that is big data.

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Table of Contents
Executive Summary...............................................................................................................................1
Introduction...........................................................................................................................................3
About McDonald's.................................................................................................................................3
Key Business priority.............................................................................................................................4
Big data approach..................................................................................................................................5
Information and sources.......................................................................................................................6
Big data technologies............................................................................................................................7
High-level architecture....................................................................................................................10
Big data visualisation examples...........................................................................................................10
(Source: By author)..............................................................................................................................12
Big data adoption challenges and governance....................................................................................12
Hadoop is hard................................................................................................................................12
Scalability.....................................................................................................................................13
Lack of talent...............................................................................................................................13
Actionable insights.......................................................................................................................13
Conclusion...........................................................................................................................................13
References...........................................................................................................................................14

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Introduction
Big data is defined as a data set that maintains the structured, semi-structured and
unstructured data. This technique is characterized by 3Vs such as volume, variety and
velocity and it is a very popular technology to control and maintain a large amount of
data. The main objective of this report is to understand the fundamental concept of big
data and develop big data technology for McDonald’s organization. Today use of this
technology is growing very fast because most organizations use a large amount of data
but they are not able to control and handle. It has the ability to manage both traditional
and new data sets on an individual cloud platform (Alexandrov, et al., 2014). This report
is explaining the working principle of the bid data process and a high-level architecture
will be used for better understating about big data. It is observed that this technique has
the potential to improve the computer operations, very fast process and also increase
the efficiency of networks. In which relevant data is collected from various resources
such as mobile phones, applications, emails, database, and computer servers.
About McDonald's
It is an American company which is founded in the year 1940 by Richard and Maurice
McDonald. It is generally a fast food company that provide various kinds of foods to
their consumers such as burger, pizza, cold coffee and many more. In the year 1955, Ray
Kroc joined this organization as a franchise agent and proceeded to buy the chain from
the brothers of McDonald (Cardenas, Manadhata, and Rajan, 2013). The main
headquarter of this company is located in Oak Brook but now their shift into Chicago in
the year 2018. It is the world largest restaurant that is serving around 69 million
customers daily in 100 countries. This company is also called as hum burger which also
provides chicken products, breakfast items, French fries, and other desserts. In this
report, the researcher will produce a proposal to adopt the big data technology to
manage a large amount of data. McDonald communicates with numbers of users every
day due to which they are not able to handle and store their data. For which information
and communication technology developed an advanced process to avoid this kind of
issue which is called as big data. There are 37,241 restaurants of McDonald located in
the world and the operating income of this company is $9.55 billion in the year 2017
and according to a recent study it has almost 235,000 employees. In the United States it

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is observed that McDonald closed their 184 restaurants in the year 2015 and in the year
2017 they established new dishes like a cheeseburger and French fries. The data set is
one of the common problems for every company and it is analysed that most
organizations adopted the big data technique because it is a more effective approach to
control both unstructured and semi-structured data.
Key Business priority
There are many business priorities of McDonald Company, for example, customer
satisfaction, increasing their customers, expanding their business worldwide. With the
help of big data technology, this company can satisfy their customers by collecting their
area of interest and they can maintain their large amount of data. In last few years
McDonald is facing various kinds of issues such as quality related, the speed of service,
and lack of timing due to which they lost their numbers of customers between 2015 and
2017 (Cevher, Becker, and Schmidt, 2014). If they adopt big data technique then they
can analyse which types of fast foods like the modern generation people and they can
compare their data every year. In the year 2017, this company invested around $3
billion for installing new projects and technology like wireless networks, internet of
thing and many more. Still, they did not involve big data process in their business due to
which they cannot improve their customers. The speed of service is another business
priority of McDonald in which they developed mini robots and provide complete
information of their orders on a screen. All these priorities can be achieved by using big
data technology and they can easily find key factors that influence a user decides to
purchase any product. According to the recent studies the profit margins of McDonald
currently sit at around 10% which is occurred due to lack of customer satisfaction and
low service speed (Fisher, et al., 2014). It is observed that there are main two
organizations which are providing cloud-based services such as Amazon and Microsoft.
To perform big data technique the Microsoft Azure can be used that has potential to
evaluate the previous and recent performance of McDonald Company, also produce
latest opportunities to enhance the rate of customers, determine the overall efficiency,
and also increase the customer satisfaction.
Today, many organizations are using big data process to increase decision making by
existing BI solutions that analyse data produced through business activities and provide

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a report based on their analysis. Traditional BI solution is not more effective due to
which information and technology developed a new approach which is known as big
data. This method provides a platform to enhance the value of McDonald investment in
BI.
Big data approach
Big data analytics is defined as a complex process of evaluating a large number of data
sets that involve hidden patterns, market trends and unknown correlations. There are
many advantages of big data analytics for example effective marketing, provide better
user service, revenue opportunities, increased operational efficiency, and also increased
customer satisfaction. Due to these benefits, most of the organizations developed big
data approaches such as Amazon, Google and many more and McDonald can adopt this
modern technology to improve the customer satisfaction (Gandomi, and Haider, 2015).
To develop an effective big data projects for McDonald company decision makers
require involving main three techniques such as batch analytics, ad-hoc approach, and
real-time analytics. Most executives and decision makers focus on one of these
processes by which they can improve the efficiency of operation. Ad-hoc is an analytic
process that provides a relationship between a database and big data sets. For data
volume the relational database is megabyte but the size of data sets is between terabyte
and petabytes. Batch analytics is another approach which is a more effective medium of
evaluating a large amount of data and it provides an immediate action to an
organization. This type of process controls the stored data and improves the efficiency
of the information system (Herodotou, et al., 2014).
The real-time analytics is the analysis of data which is a very important step to produce
an effective big data approach. With the help of this technique, the manager can take
action very quickly and also reduced overall delay in operation. There are few steps also
involve during implementation of big data technology for McDonald company such as
gain executive-level sponsorship, augment rather than re-build, make value to the
consumer a priority, ran an agile shop and expend over time, connect users data to the
McDonald process, produce a repeatable method and action process, perform,
determine and learn new things, link data to the user’s life cycle and make a feedback

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process. With the help of all these steps and techniques, a big data process can be
developed for the McDonald Company (Sandeep, and Reema, 2017).
Information and sources
Big data is a very popular technique that has the potential to grow the business
operations and McDonald can increase their customers by using this advanced data
model. There are many information sources will be used for the generation of big data
processes such as social media, a recent investigation about big data, transactional data,
and other relevant information will be collected from online websites and journal
articles. Recently information and technology developed big data collection and analysis
techniques in SaaS platforms by which McDonald can easily analysis customer’s data
(Hu, et al., 2014). Contextual data is one of the most important processes to store a large
amount of data which involve numbers of variables. It is observed that big data analysis
has changed the way of retailer’s staff and this data can be utilized to guide staffs
choices. Google analytics will be used during the generation of big data because it has
the potential to store the demographic data or every customer (Simmhan, et al., 2013).
This information can help to McDonald Company for preparing marketing campaigns
and also identify which types of aspects get the most attention. In big data a heat map
technology will be used that provides a platform to find which section of every page on
the McDonald website produce the most mouse clicks.
There are main three categories of data such as structured data, unstructured data, and
semi-structured data. Structured data is defined as a data set which already exists in the
database and generally, it is used in programming and computer-related functions.
There are main two resources of structured data such as machines and humans and all
relevant data collected from sensors, emails, weblogs, and another financial web.
Human-generated data involve all data a user input into a computer, for example, his
name, bank details and other personal details. Unstructured data is the opposite of the
structured data in which around 80% of the data is stored in other peripheral devices.
In which data is collected from satellite images, and social media (Kambatla, et al.,
2014). The most of semi-structured data appear to be unstructured and in which 50%
data is stored in the database system. NoSQL is the best example of semi-structured that
contains only keywords which are used to process the document.

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Big data technologies
There are many big data technologies developed by information and technology in
which Apache Spark is best technology that can be used for McDonald Company. It is an
open source framework that provides a way to run large-scale data applications across
clustered computers (Singh, and Reddy, 2015). The main advantage of this technology is
that it can monitor both real-time and batch analytics approaches. Spark is a high-level
project of the Apache foundation and version 2.0 was produced in the year 2016 (Kwon,
Lee, and Shin, 2014). With the help of this technique, McDonald can enhance their
productivity and they can easily analysis the user’s data. Apache Spark process data
from various kinds of data repositories, for example, NoSQL, Hadoop distributed file
system and Apache Hive. It provides a comprehensive unified outline to control big data
processing with a number of datasets. It also allows programmers to make complex,
multistep data pipelines with the help of directed acyclic graphs and also support
memory data sharing across a directed acyclic graph. By using this technique McDonald
can analyse their data and they can easily identify which types of food required adults.
Processing of stream data is one major example of apache spark that processes the large
quantity of data at a time. There are other examples of this technology such as Pi
estimation, transformation system to generate a data set, and other data operations
(LaValle, et al., 2014). There are many other key technologies that enable big data
analytics for McDonald which are the following:
 Predictive analytics
 NoSQL databases
 Knowledge discovery tools
 Stream analytics
 In memory data fabric
 Distributed storage
 Data virtualization
 Data integration
 Data processing
 Data quality

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Figure: big data technologies
(Source: Najafabadi, et al., 2015)
Predictive analytics
It is one of the prime techniques to produce big data for McDonald that avoid the risks
and threats in decision making. The hardware and software solutions of predictive
analytics can be used to the devaluation of predictive scenarios with the help of
processing data. This type of process will help McDonald to solve the issue of analysis
datasets and understanding them.
NoSQL databases

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This technique stores data of customers as a relational database and it also help to
improve the overall efficiency of data management.
Knowledge discovery tools
These kinds of tools are used to mine big data which is stored on different sources and
by using this process McDonald can mine both structured and unstructured data. With
the help of search and knowledge tools, McDonald can use and isolate the relevant
information for their benefit.
Stream analytics
Sometimes McDonald needs to process data of customers and stored on numbers of
locations for which stream analytic approach can be used. It is a very common and
important step for filtering, analysis and aggregation of these kinds of data.
In-memory data fabric
It provides a way to distribute a large amount of user data into various sources such as
flash storage, dynamic RAM and other storage drives.
Distributed Storage
It is a process to counter the failures of big data resources and also maintain the quality
of data by which McDonald can expend their business. This type of technique can be
used to handle the replicated data or information.
Data virtualization
Data virtualization allows applications to retrieve data without developing practical
restrictions for example location of data, and data formats. It is one common technique
which is used in big data technologies.

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High-level architecture
Figure: a High-level architecture for big data technology
(Source: Rahm, 2016)
Big data visualisation examples
Example 1: Big Data technologies
Below visualisation is an example of technologies used for the generation of big data
process and all these tools will be used for McDonald Company. In which each technique
linked with big data and Apache spark is the best technology to analysis and maintain
user's data.

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Figure: Technologies used in big data
(Source: By author)
Example 2: Information sources to collect data
Below chart indicates the information about data collection methods and in which there
are main four key factors by which big data can collect data for McDonald Company
such as social media, contextual data, web blog, and transactional data.
Figure: Information sources
Information sources
Social Media
Contextual data
Web blog
Transactional data
Big
Data
NoSQL
databases
Apache Spark
Predictive
analytics
Data
virtualization
Stream
analytics
Distributed
Storage
Knowledge
discovery
tools