MIS609 Data Management and Analytics

Introduction

Amazon is known to be a huge enterprise that is Internet-based that has been known to be selling various things starting from books, movies, electronics, toys to houseware and many other various goods, either directly or as the specific middleman in between various other retailers and also the millions and millions of various customers. The company’s business of web services is known to be involving renting storage of data and also several resources of computing, that is so called “Cloud Computing” over internet (Haque, Saber & Shah, 2018). The online presence of the
company that is considerable is such that within the year 2012, 1% of all of the traffic of internet within North America has been found to be travelled in as well as out of the various data centres of the company.

This organization has been chosen because it has been found to be gaining a lot of benefit from several technologies like Machine Learning, AI and also Big Data (Nandal, Tanwar & Pruthi, 2020). The specified company is also found to be making hugely market leading e-book readers
of Kindle. Its promotion of various such devices has actually led towards a huge growth in the publishing of e-cook and turned this particular company into a great force that is disruptive within the market of publishing books. The company has been known to be utilizing several services of
transportation for delivering several packages. The company’s product lines which have been available at its specific website have been mainly involving several consumer electronics, groceries, items of personal care, media and many more.

 

Concept of data analysis

Big Data for the company
Amazon has been known to have thrived by the adoption of a model that can be considered “everything under one roof”. However, whenever faced with such kinds of greater range of various options, customers can be really very often feeling hugely overwhelmed. They become greatly rich
of data, with different kinds of options, but insight poor, with very much little concept regarding what will be the best decision of purchasing for them. For combatting this, Amazon has been found to be utilizing Big Data collected from various consumers while they will be browsing for building
as well as fine tuning its specific engine of recommendation. The more the company will be knowing about the consumer, the better it can be able to properly predict what one will be wanting to buy. Amazon has been known to be collecting data on various consumers while they will be utilizing the particular site. The company has been monitoring what the customers have been looking it, the shipping address and also the feedback as well.

 

Data Mining by Amazon
Possessing about millions of several customers throughout the whole world, the company Amazon has been found to be the greatest store online that has been providing several amazing services as well as products online. They have a marvelous database of customer and are utilizing this data for properly building very much stronger relationships with their different customers. By properly analyzing and also summarizing the information that are useful regarding the different customers, they can be designing their respective strategies about several promotions as well as
improvements of different products (Gruson et al., 2019). It has directly involved the particular data mining concept from the chain of supply to several operations of marketing.Customers are known to be wanting great personalization from all of the companies they have been actually purchasing the products mostly the companies that are online because of the incremented social media interventions.

Providing the information that has been targeted to that of the representative customer service dealing with any specific consumer is actually a huge opportunity required for being developed. If several employees will be possessing mostly appropriate tools for accessing the needed information whole properly dealing with the customer it will be really saving a huge amount of time and will also be leaving a good impression on that of the consumer (Haenlein et al., 2019). At the company Amazon, the representatives of the company have access towards completing the data of customers and can be properly analyzing the particular problem and properly discuss as getting call from the consumer. Customers will be really feeling very much comfortable as well as relaxed that they knew his specific problem. All of the various retailers who are smarter like the Amazon will be making effective utilization of the data collected through several sources that are effective and utilize the different kinds of results as well as outcomes even
more reasonably (Shrestha & Nasoz, 2019). Also, all of the various consumers have proper control over that of the information they will be wanting to share or not. This will be ultimately offering them a perfect sense of both control as well as ownership.

Data of the customers have actually become a great way of properly building much potential brands and also the loyalty of consumers through data mining which is very much effective. Each and every customer is known to be perfectly treated as individual and also offered the priority.                    They are feeling very much comfortable with the service communicating with them if they will be obtaining transparency as well as control (Dimitrieska, Stankovska & Efremova,2018). Marketers are known to be obtaining a lot of information with each and every click of thecustomers. The particular purchase history of the customers at Amazon has been found to be really helping them a lot for identifying various preferences of customer and also different kinds of choices. They can be then conducting the campaign of advertising as per the choice of thecustomer. The social data movement is really very much quicker that that of the data that aremanual and is automatically uploaded. The different patterns of behavior are properly studiedwithin the identification of several channels of marketing and also for making the different strategies of marketing accordingly.

 

Artificial Intelligence for better understanding queries of customer search

Being an earlier adopter of AI and automation, Amazon has been found to be always having a specific edge in utilizing the technology of AI for enhancing its efficiencies in business. Not only has it been utilizing this particular technology for enhancing the experience of the customers but
have also been greatly focused internally (Kepuska & Bohouta, 2018). From utilizing AI for predicting various customers willingly for buying a completely new product towards running a store that will be casher less, AI capabilities of Amazon are properly designed for offering several
recommendations that are customized to all of its various customers. One of the key areas where the company Amazon has been applying continuous AI is for better understanding their search queries of customer and what is the specific reason, they are actually looking for a particular product. For any specific e-commerce enterprise for making several recommendations to its consumers, it is not only very much important for them to actually know what is actually searched by the customers, but it is even greatly critical for properly understanding the reason behind any customer is searching for a particular kind of product. Properly understanding the specific context can really be helping the retailer for recommending some items that are complementary to all of its various consumers and the company Amazon is intent towards properly working out this particular puzzle by the application of AI to that of the problem. Amazon has been known to be utilizing AI as well as machine learning for predicting
the particular context from their various search queries of the customers (Rastogi, 2018). This particular system has been known to be directly aimed towards augmenting the particular quality of several results of search on the company’s platform, which indeed directly intended towards the
enhancement of the overall shopping experience of the Amazon.

Analysis

The top-notch status of Amazon within the world of e-commerce has been known to be making it a very much frequent for the specific retail fraud. Even though if no one will be hacking or rather accidentally releasing any data of consumer, the control of Amazon of the data will be releasing several risks of security (Roh, Heo & Whang, 2019). Companies like Amazon storing data within the cloud must definitely be assuming responsibility for their own individual security. They must be properly encrypting the data that is stored. The company has been known to be gathering much more that about 2000 points of data that are historical and also those which are based on the real time on each and every order and utilizes the algorithms of machine learning for searching several transactions with a likelihood that is elevated of being hugely fraudulent. This particular system will be helping a lot in directly stopping millions of dollars’ worth of the various transactions each and every year that are fraudulent (L’heureux et al., 2017). Because of the proactive approach of the company, and the algorithms of big data tweaked for meeting several requirements that are precise, the company can be very much properly scrutinizing several requests of return. Like for an example, if big data will be showing a person has returned greater percentage of various things unusually over some of the last few months, Amazon may be investigating further.
It has been observed that the company has been found to be losing some of its steam, with the company posting about 10% increment year after year (Wankhede, Wukkadada & Nadar, 2018). Amazon may be a leader in e-commerce that is undisputed, but some of the rivals which are formidable involving Walmart can be getting even more aggressive in their various efforts for siphoning the share of the market from the company. By the utilization of data mining for Amazon has been found to be gaining a lot of competitive advantage. Amazon is utilizing data mining for marketing of their different kinds of products in several aspects. Data of the customers has been known to have become a specific way of properly building some stronger brands as well as loyalty of customers by an effective data mining (Greene, Hoffmann & Stark, 2019). All of the various customers have been found to be really treated as individual and also provided a great priority.

 

Conclusion, findings and recommendations

Even though it has been observed that Amazon has been getting a lot of competitive advantage from various technologies like Machine Learning, AI and also Big Data, it has been found that Amazon has been facing some kinds of challenges with the big data which are quite similar to several challenges which have been faced by some other different companies like the security of data, controllership of data and also difficulty analyzing the different datasets which are diverse. Amazon has been known to be leading the space of cloud by a specific fair distance.

Its AWS subsidiary has been found to be properly controlling about 35% of the worldwide market of cloud infrastructure, and it is trying to hugely extend its lead by the help of AI. After facing a lot of rivalry from various companies, Amazon has been found to have properly recognized its flaw and is faster working on plugging the various holes. It has been expanding its team of various specialists of AI for helping a lot in the development of products that can be deployed on AWS and all of the various results have been greatly flowing in. It can be recommended that proper
encryption techniques must be definitely followed from preventing any sort of security issues. Properly Machine learning algorithms are to be utilized for searching any sort of fraudulent or suspicious elements. This will be helping a lot in gaining a lot of competitive advantage and also to cover up all sort of challenges which are faced by the company. This will also be helping a lot in gaining a lot of benefits from all of the different technologies used by the company.

 

 

References:

Gruson, D., Helleputte, T., Rousseau, P., & Gruson, D. (2019). Data science, artificial intelligence, and machine learning: opportunities for laboratory medicine and the value of positive regulation. Clinical biochemistry, 69, 1-7. Haenlein, M., Kaplan, A., Tan, C. W., & Zhang, P. (2019). Artificial intelligence (AI) and management analytics. Journal of Management Analytics, 6(4), 341-343. Roh, Y., Heo, G., & Whang, S. E. (2019). A survey on data collection for machine learning: a big data-ai integration perspective. IEEE Transactions on Knowledge and Data Engineering. Nandal, N., Tanwar, R., & Pruthi, J. (2020). Machine learning based aspect level sentiment analysis for Amazon products. Spatial Information Research, 28(5), 601-607. Dimitrieska, S., Stankovska, A., & Efremova, T. (2018). Artificial intelligence and marketing. Entrepreneurship, 6(2), 298-304.
L’heureux, A., Grolinger, K., Elyamany, H. F., & Capretz, M. A. (2017). Machine learning with big data: Challenges and approaches. Ieee Access, 5, 7776-7797. Shrestha, N., & Nasoz, F. (2019). Deep learning sentiment analysis of amazon. com reviews and ratings. arXiv preprint arXiv:1904.04096.
Kepuska, V., & Bohouta, G. (2018, January). Next-generation of virtual personal assistants (microsoft cortana, apple siri, amazon alexa and google home). In 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 99-103). IEEE.

Haque, T. U., Saber, N. N., & Shah, F. M. (2018, May). Sentiment analysis on large scale Amazon product reviews. In 2018 IEEE international conference on innovative research and development (ICIRD) (pp. 1-6). IEEE. Rastogi, R. (2018, June). Machine learning@ amazon. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (pp. 1337-1338). Wankhede, K., Wukkadada, B., & Nadar, V. (2018, July). Just walk-out technology and its challenges: A case of amazon go. In 2018 International Conference on Inventive Research
in Computing Applications (ICIRCA) (pp. 254-257). IEEE. Greene, D., Hoffmann, A. L., & Stark, L. (2019, January). Better, nicer, clearer, fairer: A critical assessment of the movement for ethical artificial intelligence and machine learning. In Proceedings of the 52nd Hawaii international conference on system sciences.