Trends in Big Data Analytics

Summary

The case describes different systems that are used by organizations in their operations. Three main systems are presented in the case. The first is the transaction processing system also known as TPS. It is used to track all the transactions related to the operations of the company. Managers are able to use it whenever they need to gain any transaction information. The second system is the management information system. It is a system used mostly by middle-managers. By using it, they are able to gain a summary of the information given by TPS to predict future performance of the organization. The last system presented in the case is the decision-support system. It is used to deal with unexpected problems that can change on the fly. The case ends with an example of a ski resort that is utilizing many data gathering tools to use for future personalized marketing. The point of the case is to show that these systems are highly beneficial to the companies.

Support

This type of data collection is becoming very popular among large corporations. The amount of data is so large that it became known as “big data.” In the last ten years, it has become an industry of its own. Unfortunately, not all companies are able to gain full advantage of the data they gather because of the outdated hardware and software common in big corporations. This need has pushed many companies to create new software applications like the system mentioned in the section about the ski resort.

This advancement came because of the recent invention of the so-called “Cloud computing.” This idea means that a single computer does not have to process all the data when a request is made. Instead, this processing is distributed among many other computers connected to each other. This technique has made data analysis a much more powerful tool for corporations. This type of data analysis allows for a lesser accuracy constraint by analyzing a larger set of data than it would be possible by the older pre-cloud method. Big data is commonly used in sciences, healthcare, as well as business. In business, it is most beneficial in increasing efficiency of the business operations. This is similar to the purpose of the DSS (Kambatla, Kollias, Kumar, & Grama, 2014).

One of the companies that benefited the most from the use of these systems is Amazon.com. The online store has become one of the largest retailers on the market thanks to the advanced personalized marketing the company uses. By analyzing data from the customer’s previous purchases, the purchases of their family and other user information the company can provide best recommendations to the customer (Assunção, Calheiros, Bianchi, Netto, & Buyya, 2015).

Evaluation

The ski resort uses all three types of the systems. The transaction processing system is used to track all the purchases the client makes that are related to the resort through the connection of their credit card to the rewards card. The management information system data can be used to see which activities and plans are most popular at the resort and adjust them accordingly. The most important system for the resort is the decision-support system. It analyzes all the data gathered by the applications and other systems to create personalized marketing for as many customer groups as possible. By customizing their marketing, they are able to create more efficient marketing campaigns that aim at a specific audience.

Questions

The case describes these systems. Transaction processing system – is a system created with a purpose of answering questions about transactions and recording transaction activity. This system can give information about specific payments and the status of the inventory. It produces online and physical reports to help managers work with company transactions. This system improves the operation of the company by providing a quick answer to transaction questions. Management information system – is a system designed for middle management to show the current performance of the company.

By using this information, managers can predict the possible future performance of the organization. This system provides a summary of the data given by the transaction system. It improves the workflow of the company by providing feedback on its actions and letting the organization choose what to do next. Decision-support system – a system that helps solve problems that can change on the fly. Business analysts use these systems to analyze data gained from transaction processing systems, management information systems, and external sources. This system improves the company operations by analyzing possible outcomes of various decisions by using a large amount of data.

These systems support decision-making in different ways. TPS can provide the needed information when dealing with payroll. It can track all the money that already has been paid to the employee, as well as all the information related to those transactions. So when an employee asks for a raise, the manager can look at the number of hours worked and the pay received for them to make a decision on whether to raise it or not. MIS can be used to make decisions about the future actions of the company. For example, a new pricing strategy can be analyzed by using sales information from the MIS. A DDS can help to make many types of decisions. Most of them deal with gaining the most profit from operations. For example, to make a decision which delivery route to take to save money while keeping time.

The improvement of the guest experience is important for Vail Mountain resort for two reasons. The first is that the company gains the good word of mouth and reputation. A favorable reputation is extremely important in such a niche business as ski resorts. Vail Mountain Resort is not a part of a big chain of resorts so its management has to use every possible advantage it can. This is seen in their state of the art ten person ski lift, highly involved loyalty programs, and marketing strategies such as the involvement of an Olympic gold medalist in their racing program. These tactics allow the company to compete in this highly lucrative but also a highly competitive niche market.

The second is that the company gains a lot of personalized data that can be used to focus their marketing and make other information system related decisions. When the customers use their apps and online services, the company gains all the information it needs to target their specific demographic. This integration appears in almost every aspect of their resort experience, and it is cleverly weaved together with benefits and perks for the clients. The company utilizes almost every possible data gathering application. They collect data from the mobile app people use to compare their race times with other skiers.

They collect data through the RFID chips that people use for tickets and ski passes. They actively promote themselves and interact with their community on social media which lets them collect external data, and they collect transaction data through their reward cards tied to credit cards of the clients. These applications are cleverly designed to serve as a bonus activity for the client to create an appearance of equal benefit, although the company earns much more by gaining all this data. After collection, the data gets analyzed by their SAS Customer Intelligence software and put into the appropriate sections of the database. This allows the resort to target a much more specific demographic than before by creating personalized advertisements. They plan to expand this system in the future which could be very beneficial to the company.

References

Assunção, M., Calheiros, R., Bianchi, S., Netto, M., & Buyya, R. (2015). Big Data computing and clouds: Trends and future directions. Journal of Parallel and Distributed Computing, 80(1), 3-15.

Kambatla, K., Kollias, G., Kumar, V., & Grama, A. (2014). Trends in big data analytics. Journal of Parallel and Distributed Computing, 74(7), 2561-2573.

Cite this paper

Select a referencing style

Reference

AssignZen. (2023, May 12). Trends in Big Data Analytics. https://assignzen.com/trends-in-big-data-analytics/

Work Cited

"Trends in Big Data Analytics." AssignZen, 12 May 2023, assignzen.com/trends-in-big-data-analytics/.

1. AssignZen. "Trends in Big Data Analytics." May 12, 2023. https://assignzen.com/trends-in-big-data-analytics/.


Bibliography


AssignZen. "Trends in Big Data Analytics." May 12, 2023. https://assignzen.com/trends-in-big-data-analytics/.

References

AssignZen. 2023. "Trends in Big Data Analytics." May 12, 2023. https://assignzen.com/trends-in-big-data-analytics/.

References

AssignZen. (2023) 'Trends in Big Data Analytics'. 12 May.

Click to copy

This report on Trends in Big Data Analytics was written and submitted by your fellow student. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly.

Removal Request

If you are the original creator of this paper and no longer wish to have it published on Asignzen, request the removal.