Introduction to data science

As described in 1  Introduction, data science lives at the intersection between statistics, computer science, and discipline knowledge. It is generally the process by which we gain insight from data. Many statistics topics (e.g., data wrangling, data visualization, modeling, statistical inference, and machine learning) are data science at heart. Many computer science topics (e.g., search algorithms, data storage, distributed computing, and machine learning) are data science at heart. But beyond statistics and computer science, data science is heavily dependent on the disciplinary connections to the quantitative problem solving. Additionally, putting data science in context and understanding the ethical implications of any analysis is vitally important to the entire data science process.