Which statement about data science is correct?

Which statement about data science is correct?

• A. Data science automates all data processing and eliminates the need for human involvement.
• B. Data science is a field within mathematics that uses new mathematical concepts to analyze data.
• C. Data science is traditional computer programming that is applied to larger amounts of data.
• D. Data science is a new field that arose from the need to link big data and technology to provide useful information.

Answer: (D)

Data science is an interdisciplinary field that emerged to turn vast, complex data into meaningful, actionable information by combining statistics, computing, and domain knowledge. The correct statement reflects this broader view: it highlights linking big data and technology to provide useful information, recognizing that data science goes beyond pure math or simple programming and involves human guidance in problem framing, model choice, and interpretation. In practice, data science integrates statistics, machine learning, data engineering, and data visualization to extract insights from data at scale and support decision making. The other descriptions are too narrow: automation alone doesn’t capture the human-in-the-loop, math-focused views miss the computing and practical application, and treating it as just traditional programming ignores the analytical and interdisciplinary nature.

Data science is an interdisciplinary field that emerged to turn vast, complex data into meaningful, actionable information by combining statistics, computing, and domain knowledge. The correct statement reflects this broader view: it highlights linking big data and technology to provide useful information, recognizing that data science goes beyond pure math or simple programming and involves human guidance in problem framing, model choice, and interpretation. In practice, data science integrates statistics, machine learning, data engineering, and data visualization to extract insights from data at scale and support decision making. The other descriptions are too narrow: automation alone doesn’t capture the human-in-the-loop, math-focused views miss the computing and practical application, and treating it as just traditional programming ignores the analytical and interdisciplinary nature.