Big Data Systems (WT 2019/20)

Prof. Dr. Tilmann Rabl

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 analyses 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, integration, modeling, and interpretation.

In this lecture, we will discuss big data systems, i.e., infrastructures that are used to handle all steps in typical big data processing pipelines.


Date: October 15, 2019
Language: English
Duration: 01:15:49
Date: October 24, 2019
Language: English
Duration: 01:12:54
Date: November 5, 2019
Language: English
Duration: 01:30:37
Date: November 14, 2019
Language: English
Duration: 01:27:59
Date: November 20, 2019
Language: English
Duration: 01:28:53
Date: November 28, 2019
Language: English
Duration: 01:21:21
Date: December 3, 2019
Language: English
Duration: 01:28:01
Date: December 12, 2019
Language: English
Duration: 01:30:15
Date: January 28, 2020
Language: English
Duration: 01:29:25
Date: January 30, 2020
Language: English
Duration: 01:18:55
Date: February 4, 2020
Language: German
Duration: 00:25:47