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However, I was facing analytical challenges. To list a few, I was almost completely dependent on the companys 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 standardize. Moreover, I needed a way to gather the necessary data automatically because mining data manually is time consuming and inefficient. I was thus curious about the way my suppliers and subcontractors handled these problems and explored their efforts. I found a potential solution while I was examining a gas turbine for my power plant project at one of my suppliers, General Electric (GE). After speaking to its data scientist, I learned about the application of data collection and analytics to the turbine. The sensors were installed to collect real-time data, which enabled the data scientist to remotely monitor the equipments performance from a centralized data center and improve its efficiency by applying analytical solution to optimize the turbines system. Based on this encounter with the companys smart features, I began exploring the potency of analytics. The connection between data and machine and the utilization of valuable information derived using analytical data was an innovation that could help me revolutionize my analytical methods. Once I realized that analytics is the key to overcoming my current analytical limitations, I became determined to learn more about statistics, mathematics, and computer science to attain more sophisticated quantitative and analytical techniques such as statistical analysis, machine learning, optimization and algorithms. It is for these academic goals that I now aspire to pursue a graduate degree in Information Systems and Management with a Business Intelligence and Data Analytics concentration.
What intrigues me most about this field is the concept of data discovery, namely, discovering insights and applying analytics to develop data based products, services, or features. These skills enable data scientists to not only support businesses by assisting with management-level decisions that help the business run efficiently, but also by offering new products or features that enhance the users experience, and generate new channels for profits. LinkedInsPeople You May Know feature, which provides users with a list of people it thinks the user is likely to know, is an example of data product I aspire to develop. 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; instead, each of these tasks is strictly divided between engineers who designed structures and personnel like myself who supported their endeavors by implementing cost control measures and streamlining material procurement. With analytics, 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. Therefore, while pursuing my degree in MISM BIDA, I would like to concentrate on learning and researching methods to incorporate statistical, mathematical, managerial 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.
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