OM DENNE PODCAST 🔗
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.
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.
Opdateringsfrekvens:
every 5 days
Gennemsnitlig lydlængde:
84 minutes
Videopodcast
Engelsk
USA
20 episoder
siden 14. oktober 2025
episodic
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SIDSTE EPISODER 🔗
Ansvarsfraskrivelse: Podcasten og kunstværket, der er indlejret på denne side, er fra Prof. Dr. Tilmann Rabl, som tilhører dens ejer og ikke er tilknyttet eller godkendt af Listen Notes, Inc.
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