Master of Science in Business Analytics - Admission/Application Essay Example

Master of Science in Business Analytics The Problem Supplying business decision-makers with the right data is one of the biggest challenges faced by contemporary organizations. During product development and market research, businesses rely on big data to make important decisions. For example, consumer electronics goods companies rely on performance data collected over time to decide whether to launch products, shelve them, or enhance them to meet market demand. companies do not provide their decision makers with accurate and relevant information at the right time so that critical business decisions are made in a timely and effective manner (Baesens 17).

As a matter of fact, businesses are finding that it is easier to generate data than to use it.Why I am Interested in this ProblemBusinesses aspire to use data analytics to avoid being immersed in the enormous amount of information they produce through different processes. Many business organizations do not have sound strategies for making effective use of the tons of business and customer data they generate on a daily basis. In addition, critical data should be distinguished from noise, such as inconsequential feedback provided by clients on social media (Krishnan and Rogers 19).

I believe that the problem presented in this paper is one that is covered in graduate courses in business, such as an MSc in Business Analytics. I also believe that the course would empower me help businesses solve this problem. The Importance of this Problem from a Business Point of ViewCEOs and other senior managers require the right information to be delivered to them in the right format so that they understand situations and take the necessary measures to remedy them. Businesses that have mastered the science of collecting, sorting, and supplying accurate and timely data are more successful than those that are handicapped in this area (Baesens 18).

Potential Solutions for this Problem Businesses need to undertake upscaling in order to improve their data analytics capabilities. In this context, upscaling implies improving all the vital aspects of data analytics that would boost the capacity to collect, process and deliver information. Employees should be adequate, competent, intelligent, and dynamic (Krishnan and Rogers 26). Benefits and Drawbacks of the Suggested SolutionsIf implemented correctly, the proposed solutions would inspire high levels of effectiveness and efficiency in data collection and use.

It would also provide vital competitive advantage for businesses that apply them correctly (Baesens 27). The first drawback of this suggested remedy is that it is expensive and would suit large businesses more than small or medium sized ones. The second drawback is that it is difficult to determine the right degree of upscaling that should be carried out. Works CitedBaesens, Bart. Analytics in a Big Data World: The Essential Guide to Data Science and Its Applications. New York: Wiley, 2012. Print.

Krishnan, Krish & ‎ Rogers. Shawn P. Social Data Analytics: Collaboration for the Enterprise. Waltham, MA: Newnes, 2014. Print.