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Which technology is often used to process and analyze large-scale data sets in Data Science?
Answer & Solution
Correct Answer:
Option
A
Hadoop is a technology often used to process and analyze large-scale data sets in Data Science.
Hadoop is an open-source framework that allows for the distributed processing of large data sets across clusters of computers.
It is designed to scale up from a single server to thousands of machines, each offering local computation and storage.
Key components of Hadoop include: HDFS (Hadoop Distributed File System) for storage and MapReduce for processing.
Hadoop's architecture is highly scalable and fault-tolerant, making it a popular choice for big data processing.
Other technologies such as SQL and Python are also used in Data Science, but Hadoop is specifically designed for handling and analyzing large-scale data.
Hadoop is an open-source framework that allows for the distributed processing of large data sets across clusters of computers.
It is designed to scale up from a single server to thousands of machines, each offering local computation and storage.
Key components of Hadoop include: HDFS (Hadoop Distributed File System) for storage and MapReduce for processing.
Hadoop's architecture is highly scalable and fault-tolerant, making it a popular choice for big data processing.
Other technologies such as SQL and Python are also used in Data Science, but Hadoop is specifically designed for handling and analyzing large-scale data.
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