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Description
This course covers the meaning of Big Data, the challenges posed by big volume, velocity, and variety of data, and the tools and techniques used in data science and complex analytics. The course discusses traditional solutions like ETL, the future of Hadoop, Spark, R, and Map-Reduce, as well as the importance of data integration at scale. The intended audience for this course is individuals interested in understanding the complexities of Big Data and learning about the various approaches and technologies used in handling large datasets.
Stanford Seminar - Big Data Is -At Least- Four Different Problems
Affiliate notice
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TypeOnline Courses
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ProviderYouTube
This course covers the meaning of Big Data, the challenges posed by big volume, velocity, and variety of data, and the tools and techniques used in data science and complex analytics. The course discusses traditional solutions like ETL, the future of Hadoop, Spark, R, and Map-Reduce, as well as the importance of data integration at scale. The intended audience for this course is individuals interested in understanding the complexities of Big Data and learning about the various approaches and technologies used in handling large datasets.
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