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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Kompetenzen, die Sie erwerben
University of 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.
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Top-Bewertungen von DATA MANIPULATION AT SCALE: SYSTEMS AND ALGORITHMS
Its pretty decent. I liked the assignments. However there were some typos in the lecture slides and also the grader output is not very friendly.
Definitely need some background in R or Python and the lectures are a bit old. Seem to be from around 2013 when this first came out but most of the info is still relevant.
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.
A great way to start, and become familiar with the nature, requirements & analytics of today's data.
Über den Spezialisierung Skalierte Datenverarbeitung
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
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