What is Data Science?

Data Science combines tools from mathematics, statistics, computer science, and engineering, to effectively extract knowledge from data, facilitate data-driven decision making, and build systems that adapt and learn from data to solve complex industrial and scientific challenges. Data science emerged as a key paradigm in fields ranging from pharma and life sciences where it is used to better understand the fundamentals of life and disease, over medical imaging where it ushered in a new era of super-fast, high-resolution algorithms, to computational social science, digital humanities, political science and policy making. It solves challenging problems with almost unreasonable effectiveness. It generates and informs questions across all layers of our society, influencing legal frameworks, public debates, and changing the way we work, think, communicate, and relax. The data science pipeline begins with exploratory analysis of datasets and builds towards effective communication, data visualization, and representation of new knowledge which can inform decisions and lead to technological breakthroughs. Due to its sweeping importance over the last two decades this fascinating field is often referred to as the fourth pillar of scientific methods, alongside theory, research, and computational science.