The amount of data that can be generated and stored in academic and industrial projects and applications is increasing rapidly. Big data analytics technologies have established themselves as a solution for big data challenges to the scalability problems of traditional database systems. The vast amounts of new data that is collected, however, usually is not as easily analyzed as curated, structured data in a data warehouse is. Typically, these data are noisy, of varying format and velocity, and need to be analyzed with techniques from statistics and machine learning rather than pure SQL-like aggregations and drill-downs. Moreover, the results of the analyzes frequently are models that are used for decision making and prediction. The complete process of big data analysis is described as a pipeline, which includes data recording, cleaning, In this lecture, we will discuss big data systems, ie, infrastructures that are used to handle all steps in typical big data processing pipelines.
Charts
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Neueste Folgen
Feb 7, 2023
Recap and Exam Preparation
95 mins
Feb 2, 2023
From Prototypes to Products: The Gap Between Academic and Commercial Code
86 mins
Jan 31, 2023
Modern Hardware I
83 mins
Jan 24, 2023
Machine Learning Systems & Modern Hardware I
83 mins
Jan 19, 2023
Machine Learning Systems II
91 mins