Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales.
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- 5 stars57.23%
- 4 stars25.39%
- 3 stars9.07%
- 2 stars4.73%
- 1 star3.55%
DATA MANIPULATION AT SCALE: SYSTEMS AND ALGORITHMS의 최상위 리뷰
Comprehensive and clear explanation of theory and interlinks of the up-to-date tools, languages, tendencies. Kudos and thanks to Bill Howe.
Very good course, but lectures could be more tuned onto the home assignments. A lot of independent work for me at least. Teacher is very good.
The course is very coherent and comprehensive. It covers only important aspects of the fields. Also, the exercises are very well prepared.
- great and very useful overview of concepts important in big data that does not get bogged down in random details
- interesting and sufficiently challenging assignments
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