Searched over 200M research papers for "data science"
10 papers analyzed
These studies suggest that data science is an interdisciplinary field combining computer science, statistics, and other disciplines to analyze large-scale data sets, with significant impacts from big data and machine learning, and applications in various domains such as healthcare, business, climate change, and software engineering.
19 papers analyzed
Data science is an interdisciplinary field that focuses on extracting meaningful insights from data through various techniques and methodologies. It integrates principles from computer science, statistics, mathematics, and domain-specific knowledge to analyze and interpret complex datasets. This synthesis aims to provide a cohesive understanding of the current state of data science based on multiple research papers.
Interdisciplinary Nature and Curriculum:
Emergence and Evolution:
Role in Various Domains:
Methodological Challenges:
Core Concepts and Algorithms:
Data science is a rapidly evolving field that integrates multiple disciplines to analyze and interpret large and complex datasets. It has emerged due to technological advancements and plays a significant role in various domains, including web science, commerce, health, and environmental sciences. Despite its broad and interdisciplinary nature, data science faces methodological challenges that require a holistic approach for effective project management. Core concepts and unique algorithms further distinguish data science from related fields like machine learning and statistics.
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