Data is the core of all decision-making in modern society. The essence of the ability to handle data is not simply technical skills, but data literacy to properly read, interpret, and use data. This means going beyond considering data as mere numbers or information, and the ability to identify hidden patterns in data and apply them to solve problems.
Statistics are made up of well-cleaned data, but most of the data that engineers encounter is provided in an unorganized state. This presentation discusses the power of data visualization to discover hidden patterns, the process of verifying whether the discovered patterns are actually meaningful, and the principles for deriving reliable predictions. It also presents a forecast of how AI and machine learning are utilizing data in the engineering field and how data literacy will evolve in the future.
