Answer To: Page 1 of 7 Big Data Basics INFS 5095 2019 Student's Assignment Guide (Internal and External/Online)...
Shikha answered on Jun 22 2021
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Student ID 16
Assignment 2 – Big Data Analytics
(McDonalds)
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Table of Contents
1. Executive Summary 3
2. Introduction 3
3. Organization Background 4
4. Business Priority 5
5. Big Data Approach 6
6. Information and Sources 7
7. Big Data Technologies 7
8. Big Data Visualization Examples 10
9. Big Data Adoption Challenges and Governance 12
10. Conclusion 13
11. References 14
1. Executive Summary
The immense repository of terabytes of information is created every day by using current information systems or advanced innovations like Internet of Things and cloud computing. Analyzing this huge data requires many endeavors at various dimensions in order to get meaningful data for better decision making process. Consequently, this big data analysis is a momentum area of innovative work. The main objective of this paper is to analyze the potential effect of big data challenges, open research issues, and various tools that are related with it. Thus, this paper will provide a better understanding to analyze big data at various stages. Moreover, it opens another skyline for the researchers to build up the solution, in view of the challenges as well as open research issues (Acharjya and Kauser, 2016). In this report, we will discuss about McDonalds organization and how the organization can use the approach of big data and convert it into meaningful information for better decision making.
2. Introduction
Big data analytics is characterized as tool or process which can be applied to large datasets in order to acquire meaningful insights, which helps the organization to improve the performance. These innovations help organizations to better comprehend their business sectors and influence the opportunities by accessing large amount of data (Ghasemaghaei and Hassanein, 2015). Organizations that gather information can use the data for generating new revenue schemes. Therefore, the organization should start with a business reason for analyzing their big data so as to decide how information will be gathered, organized or processed for the some chosen analytic form. The main opportunities that are connected into data analysis in numerous associations have created a significant enthusiasm for business insight, that help to create better understanding of the market and furthermore to make accurate decision at correct time (Alsghaier and Akour, 2017).
For the most part, large datasets in the organization are managed using Data warehouses. Some data mining methodologies are certainly not ready to deal with the large datasets effectively. The main objective of this paper is to discuss the effect of data mining methods and structures of big data which is considered as ideal methodology in accomplishing the correctness and timing in quick as well as reliable decision making (Acharjya and Kauser, 2016). In this report, we are discussing the case of McDonalds.
3. Organization Background
McDonald's is the large global food service retailer having 34.000 local restaurants that serve approximately 69 million individuals in 118 nations every day. The daily customer traffic is about 62 million clients and approximately 75 burgers are sold consistently. Their annual revenue is about $ 27 billion. With such large restaurant chain, their generation of data is so large that they need some analytic tool to use this data in meaningful way (Datafloq, 2019).
Adopting data driven culture is likewise imperative to enable McDonald's to comprehend the restaurant performance at every franchise that can be imparted to other franchises in the chain. The consistency of sustenance as well as customer's experience Since McDonald's uses an establishment plan of action, is significant over the establishment. The organization considers multiple data points for making the customer's experience better. For instance, in case of drive-through experience they not just evaluate the structure of the drive-through, yet they analyze the data which is provided to the customer and what's going on for clients holding up in line to order. In order to make customer's experience better, they analyze the data pattern fr predicting and modify the overall structure (Marr, 2019).
4. Business Priority
Currently, the data which is provided by local stores depended on average metrics. Hence, it became challenging while comparing the stores so that some action can be taken for making the results better. In this manner McDonald's uses an average to trend analytics that give significantly more understanding of data in case of local stores. The management integrated datasets and envisioned it to comprehend the reason as well as its effect while making differences. They joined multiple graphs based on the datasets in order to comprehend the correlation. These correlations were utilized for having better and significant actions, that results in saving money as well as time.
This information which is derived from the prescient analytics is utilized to make iterations crosswise over design, data as well as individuals practices. McDonald's at that point utilizes this data analytics in order to discover the trade-offs of the progressions made so as to find the better solution for plan, data and individuals. The big data solution like Microsoft Azure HDInsight can enable the organization to find fundamental data that may have remained covered up in your information—or even been lost for the restaurant. This data can help to evaluate the association's verifiable performance, find new opportunities, recognize operational efficiencies, enhance consumer loyalty, and even anticipate likely results for the coming future (Microsoft big data solutions, 2019).
Besides, McDonald's tracks and analyze this large measures of factors for improving its processes and improving the customer experience. The organization monitor in-store traffic, client co-operations, flow graphs to analyze flow through pattern of customer's orders, purpose of-sales data, video information and sensor information. Results that is derived from this information is utilized to develop iterations in the structure of the restaurant chains, generate menu variations, advance their training program and their supply chain network. Hence, according to data, all restaurant chains around the globe appear to be identical, but there is difference in each chain as they are streamlined utilizing such information for the local market. Likewise, McDonald's uses operational information to computerize and enhance the...