Importance of a Postgraduate Degree in the Computer Science Field (Data Science)
More than 17 years ago, when I was starting my undergraduate studies in Mexico, I would never have imagined the revolution of the digital age. The digital age brought with it a massive explosion of data coupled with new technologies and products developed with Artificial Intelligence and Big Data. As a data analyst, who sporadically had to do predictive analytics during my first job in a bank, I still remember how tedious it was to model certain phenomena using obsolete processes… Until a few years ago, companies primarily used statistical data for analysis, although in a more “handmade” way. With the advent of computing and the help of computers, cloud storage, and analytics tools, the decision-making process has been greatly improved and simplified. From the massive generation of data and the change in human behavior when living with technology, different needs appeared in the industry, such as taking advantage of the data that they themselves generated to obtain benefits from it
During my experience across different industries such as banks, airlines and startups, I notice that in some industry sectors, data science is still an untapped treasure trove, especially since there is a small number of competent personnel in this area. Since modern technology has allowed the creation and storage of large amounts of information, the volume of data has exploded, however, much of it is still sitting in databases, basically untouched, despite the great transformative benefits they represent. That is why data science is important, because from the treatment of this data it can generate information that can be used to make better decisions and create more innovative products or services, in addition to allowing autonomous learning models to “educate” themselves, instead of relying on Big Data only as was previously done.
The impact of data science is tremendous; from its most usual application, data science is present in our daily lives, both in the personal and professional fields. From business to the health industry, science to our everyday lives, marketing to research, in fact, for everything, data is required to thrust the movement forward. Computer science and information technology have taken over our lives, and it is advancing with each passing day with such velocity and variety that the operational techniques used a few years back have now become obsolete. Since it can evaluate a massive and complex volume of data, its use is distributed in different segments of the industry, which need it to find insights that contribute to the resolution of problems, in addition to being the fuel for innumerable business and social models, thus revolutionizing the way we perceive data.
The use of Data can have very positive purposes, for example, when it is used to make government decisions transparent, or when it becomes a source of analysis to produce public policies, as two of the most popular cases… For example, research has found that: “the social sciences, historically rich in theories and contextual knowledge, are well positioned to guide development and translation of data products into meaningful decisions and practices” (Erosheva et al., 2022).
Mobile phones, sensors, and the digitization of everyday activities create vast amounts of data that can be exploited, understood, and valued to gain new insights about our world and transform nearly every area of our lives. The same algorithms and techniques that companies can use to increase their profits can be used by organizations, companies or individuals who have the purpose of improving the world. However, most social change organizations do not have the budget or staff to take full advantage of this data revolution. That is why it is important that companies start dedicating themselves to contributing to the creation of scalable solutions to help decision makers to do it but, powered by data.
My expectations after the completion of MsC Data Science are clear: I want to learn the most modern and optimal techniques to model and manipulate data, computationally and mathematically supported, for problem solving and for the benefit of society. At the same time, this will help me to boost my professional career and will provide me with tools to implement digital transformation and apply the “data-driven” culture.
I am sure that the interaction between professors and classmates will enrich my knowledge, experiences and broaden my vision of the different problems faced by data professionals.
References:
Erosheva, E. A., Minhas, S., Xu, G., & Xu, R. (2022). Editorial: Data Science Meets Social Sciences. Journal of Data Science, 20(3): 277-278. DOI: https://doi.org/10.6339/22-JDS203EDI