Skip to content
Module 1 Fall 22 episode artwork

EPISODE · Sep 2, 2022 · 15 MIN

Module 1 Fall 22

from EDSE 622 Clarifying Lecture · host Christine Barthold

Listen to this podcast for important information and opportunities!

Episode metadata supplied by the publisher feed · Published Sep 2, 2022

Embed this episode

Ready to play

Module 1 Fall 22

0:00 15:21

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

Abnormal Psychology Lectures Dana C. Leighton These lectures were given to support my Introduction to Abnormal Psychology course at Portland Community College in Portland, Oregon, USA. They are "enhanced" podcasts, which includes my lecture slides, so be sure to open the "artwork & video viewer" in iTunes! Ringvorlesung - Practical Data Engineering (WT 2019/20) - tele-TASK Prof. Dr. Tilmann Rabl The Lecture Series on Practical Data Engineering will feature presentations by distinguished speakers from industry and academia on the topic of data engineering. We will cover topics on the application of data engineering in industrial setups as well as system level advancements in data engineering research. Hardware-Conscious Data Processing (ST 2023) - tele-TASK Prof. Dr. Tilmann Rabl Hardware development continuously advances, with different technologies improving at different pace. While the amount of transistors in a CPU package are growing, the single core performance is stagnating due to physical limitations. These trends require changes in data processing to keep database management systems efficient. In this lecture, we will take a look at current computer architectures and accelerator technologies and how they can be used for efficient data processing. We will cover CPU and memory architecture; the storage hierarchy; modern memory technolgoies, such as NVM and NVMe; fast interconnects, such as Infiniband, RDMA, and NVLink; and accelerators, such as GPUs and FPGAs. The course has a significant practical part, where the students learn to implement data structures and algorithms tailored to hardware concious data processing. Big Data Systems (WT 2024/25) - tele-TASK Martin Boissier 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 st

Frequently Asked Questions

How long is this episode of EDSE 622 Clarifying Lecture?

This episode is 15 minutes long.

When was this EDSE 622 Clarifying Lecture episode published?

This episode was published on September 2, 2022.

Can I download this EDSE 622 Clarifying Lecture episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!