Data science for smoothly utilizing large amounts of data.

Keywords: Data Science, Exploratory Data Analysis, Database, Machine Learning, Artificial Intelligence

The advancement of computer performance, the increase in storage capacity, and the explosive growth of information circulating on the internet have significantly changed our living environment. In research and development settings, it is becoming increasingly important to utilize not only the knowledge and experience accumulated by individuals and research labs but also the vast amounts of data measured by experimental equipment and the ever-growing literature and databases. However, even when trying to utilize available data, there are cases where data is not organized or only printed data is available, making it difficult to start data analysis easily. Additionally, even after the data is prepared, making progress toward conclusions requires decision-making based on certain skills and experience regarding what to derive from the data, which analysis methods to use, and how to evaluate the results. The collective term for the technologies that address these challenges is data science, and currently, we are engaged in research on exploratory data analysis methods to facilitate understanding of data, as well as in the development of engineers and researchers equipped with specialized knowledge and the qualities of data scientists.

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