Big Data Systems (WT 2023/24)

Prof. Dr. Tilmann Rabl, Nils Straßenburg

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, integration, modeling, and interpretation.

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



Date: October 17, 2023
Language: English
Duration: 01:21:17

1st Exercise Session

Date: October 18, 2023
Language: English
Duration: 00:37:32

Use Case - Search Engines

Date: October 24, 2023
Language: English
Duration: 01:29:27

Benchmarking & Measurement

Date: October 25, 2023
Language: English
Duration: 01:21:44

Map Reuce 1

Date: November 7, 2023
Language: German
Duration: 01:25:28

Map Reduce Architecture

Date: November 8, 2023
Language: English
Duration: 01:32:04

Map Reduce III

Date: November 14, 2023
Language: English
Duration: 01:26:08

Data Center and Cloud Computing

Date: November 21, 2023
Language: English
Duration: 01:24:41

Data Center and Cloud Computing (2)

Date: November 22, 2023
Language: English
Duration: 01:27:12

Distributed File Systems (No Audio)

Date: November 28, 2023
Language: English
Duration: 01:25:35
Due to technical issues, please watch last year's lecture: