Big Data Systems (WT 2022/23)

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 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.



Date: October 18, 2022
Language: English
Duration: 01:22:41

1st Exercise Session

Date: October 20, 2022
Language: German
Duration: 00:24:39

Use Case - Search Engines

Date: October 25, 2022
Language: English
Duration: 01:25:25

Benchmarking & Measurement

Date: October 27, 2022
Language: English
Duration: 01:28:17

Map Reduce I

Date: November 1, 2022
Language: English
Duration: 01:18:05

Map Reduce II

Date: November 8, 2022
Language: German
Duration: 01:28:13

Data Center and Cloud Computing

Date: November 15, 2022
Language: English
Duration: 01:24:19

Distributed File Systems

Date: November 22, 2022
Language: English
Duration: 01:28:08

Distributed File Systems II

Date: November 24, 2022
Language: English
Duration: 01:24:44

Key Value Stores

Date: November 29, 2022
Language: English
Duration: 01:23:37