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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Habilidades que obtendrás
Universidad de Washington
Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world.
- 5 stars57,25 %
- 4 stars25,46 %
- 3 stars9,10 %
- 2 stars4,61 %
- 1 star3,56 %
Principales reseñas sobre DATA MANIPULATION AT SCALE: SYSTEMS AND ALGORITHMS
Comprehensive and clear explanation of theory and interlinks of the up-to-date tools, languages, tendencies. Kudos and thanks to Bill Howe.
It's pretty tough in assignments especially when there are mistakes in the given description, but I do learn the basic concepts of relational algorithm and MapReduce from them.
The course is very coherent and comprehensive. It covers only important aspects of the fields. Also, the exercises are very well prepared.
This is a quite wonderful course for large-scale data science. I believe I will have learned a lot via completing the courses.
Acerca de Programa especializado: ciencia de los datos a escala
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
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