How is "data science" defined?

The definition that identifies data science as an "interdisciplinary field that extracts insights from data" captures the essence of what data science entails. This field draws on techniques and theories from various domains, including statistics, computer science, mathematics, and domain-specific knowledge. The primary goal of data science is to analyze and interpret complex data to derive meaningful insights, make informed decisions, and solve problems.

Data science emphasizes the integration of various methodologies and tools to handle, analyze, and visualize data. This interdisciplinary approach is crucial because real-world data problems often require a combination of statistical analysis, computational algorithms, and domain expertise to fully understand and leverage data effectively.

In contrast, definitions that focus strictly on mathematics, software application development, or database management miss the broader scope of data science. While mathematical skills are certainly a significant component, data science is not limited to mathematics alone. Instead, it encompasses a wide range of skills and knowledge areas, highlighting its nature as an interdisciplinary field aimed at generating insights and supporting decision-making through data.