A seminar entitled Data Science: Opportunities and Challenges was presented by PhD candidate Shirin Noekhah on Thursday, Oct 3rd. She introduced Data Science as a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data, and also that it uncovers the findings from data. It’s about surfacing hidden insight that can help enable companies to make smarter business decisions. Data science uses the most powerful hardware, the most powerful programming systems, and the most efficient algorithms to solve problems.
She added that Data Science unifies the statistics, data analysis, machine learning, and their related methods to understand and analyze actual phenomena with data in different domains of study such as social media, health, finance, etc. It employs techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, and information science.
She explained that recently, data science has been added to this paradigm as a fourth component in the form of the data-driven concept. In many cases, earlier approaches and solutions are now simply rebranded as “data science” to be more attractive, which can cause the term to become beyond usefulness. While many university programs now offer a data science degree, there exists no consensus on a definition of suitable curriculum contents.
The opportunities and challenges were listed by her by discussing that data mining and big data are two hot topics of data science domain. However, many data-science and big-data projects fail to deliver useful results, often as a result of poor management and utilization of resources. Therefore, having professional data scientists can improve the performance of developed systems in the domain of data science.