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노스웨스턴 대학원 지원 SOP(Analytics)에 대해 기술한 참고자료입니다.

저작시기 : 2021년 1월

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During my time as a procuremen
t associate in eTEC E&C, a South Korean EPC company that constructs civil buildings and industrial facilities, I was facing analytical challenges. I was almost completely dependent on the company's internal data, and it was very difficult to decide where and how to find relevant, accurate data from credible sources outside the company. Next, analyzing data and information that continuously changed or was affected by too many factors, such as the performance and output of machineries, was problematic because such information was hard to organize. Moreover, I needed a way to gather the necessary data automatically. To overcome my current analytical limitations, I became determined to learn analytics to attain more sophisticated quantitative and analytical techniques such as statistical analysis, data mining, optimization and algorithms.
What intrigues me most about
analytics is the concept of data discovery, namely, discovering insights and applying analytics to develop data based products, services, or features. I find the concept of data discovery especially fascinating because I realized during my work that there is no position at eTEC that performs both a supporting role and is directly involved with developing products. As a data scientist, I could take on both roles, allowing me to make greater contributions to the business by not only reducing costs, but also creating new lines of revenue through product development, which is the type of work that I hope to focus on during my career. To sum, while pursuing my degree in analytics, I would like to concentrate on learning methods to incorporate statistical, mathematical, and computer-based skills that would optimize the decision-making process and business operation efficiency, and lead to creative ideas to develop viable data based products. The greatest strength of Northwestern's MSIA program lies in its curriculum that incorporates computational disciplines with management skills and focuses on industrial experience. This will help me gain the knowledge I need to satisfy my career goal by integrating technical skills with management expertise. The practicum projects and internship opportunities with leading corporations will allow me to better understand the various approaches they take toward analytics and data science, what they hope to gain from them and how they expect them to be applied. In the end, I hope to be able to connect with companies that find my career goal in line with their vision for analytics.
With IoT (Internet of Things)
technology, I believe the future of analytics over the next five years is heading to the development of Smart Cities. The connection between devices within the city, networks, and people will enable us to monitor human and machine behavior in real-time, generating a consistent flow of Big Data for data scientists to analyze. The outcomes of the applications of analytics to the city, such as enhanced security and optimized energy use, will be so enormous that most of traditional cities will be transformed into Smart Cities. Hence, the field of analytics will flourish along with the development of IoT and Smart Cities.
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