Scaling Up to Address Data Science Challenges

Statistics and data science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields, such as statistics, machine learning, computer science, and applied mathematics, can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing.

This article explores various challenges in data science and highlights statistical approaches that can facilitate analysis of large-scale data, including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithms and procedures for efficient processing.

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