Chevron Left
Вернуться к ETL and Data Pipelines with Shell, Airflow and Kafka

Отзывы учащихся о курсе ETL and Data Pipelines with Shell, Airflow and Kafka от партнера IBM

4.5
звезд
Оценки: 87
Рецензии: 25

О курсе

After taking this course, you will be able to describe two different approaches to converting raw data into analytics-ready data. One approach is the Extract, Transform, Load (ETL) process. The other contrasting approach is the Extract, Load, and Transform (ELT) process. ETL processes apply to data warehouses and data marts. ELT processes apply to data lakes, where the data is transformed on demand by the requesting/calling application. Both ETL and ELT extract data from source systems, move the data through the data pipeline, and store the data in destination systems. During this course, you will experience how ELT and ETL processing differ and identify use cases for both. You will identify methods and tools used for extracting the data, merging extracted data either logically or physically, and for importing data into data repositories. You will also define transformations to apply to source data to make the data credible, contextual, and accessible to data users. You will be able to outline some of the multiple methods for loading data into the destination system, verifying data quality, monitoring load failures, and the use of recovery mechanisms in case of failure. Finally, you will complete a shareable final project that enables you to demonstrate the skills you acquired in each module....

Лучшие рецензии

DS

13 июня 2022 г.

Excellent introduction to this topics. Labs contain all you need to know how to start using this type of technologies. Highly recommended.

MA

9 июня 2022 г.

Thanks to all the instructor's efforts, one of the best DATA engineering courses, contains hands-on Experience with essential data tools.

Фильтр по:

1–25 из 25 отзывов о курсе ETL and Data Pipelines with Shell, Airflow and Kafka

автор: Nataliya S

12 окт. 2021 г.

Thanks to IBM and Coursera for the great "ETL and Data Pipelines with Shell, Airflow and Kafka" course, that I passed with Grade Achieved: 100%. It's the third course, that I've passed, as a part of "IBM Data Engineering Specialization". I was so carried away by the course that I literally sat up until 2 am almost every day. In this course I could apply my knowledge of Python, Pandas, SQL, Bash commands to build ETL Batch and Stream pipelines.

автор: Evgeny D

29 сент. 2021 г.

I​t's one of the most challenging courses I've been enrolled!

автор: Dmitry K

17 сент. 2021 г.

Buggy practice. Not possible to complete without fixing airflow start script yourself. Nobody monitor or fixing issues here

автор: RLee

13 янв. 2022 г.

The final project to connect Airflow as a pipeline management tool to Kafka server is a very useful hands-on project. More details or explanations on the syntax of Python calling Kafka producer and consumer, which are in the files of toll_traffic_generator.py and streaming_data_reader.py, would be more valuable rather than just providing these two files to run on its own.

автор: Ilya K

13 янв. 2022 г.

Perfect environment to make experiments! Very easy and powerful in use.

автор: Natale F

15 дек. 2021 г.

Interesting course with enough labs.

автор: Hugo A O O

6 дек. 2021 г.

i really liked the labs

автор: Omar H

26 янв. 2022 г.

It's great introduction for airflow and kafka but still an introduction it is shallow doesn't offer much but at the end you will understand what you need to continue further in both technologies.

автор: Chris B

20 апр. 2022 г.

Course content is good but labs are riddled with bugs and in dire need of quality control. I encountered many time-consuming, frustrating technical issues that made completing this course a slog. Final assignment introduces some difficult linux manipulations that were not covered in the coures and are not really that relevant to the subject matter. Some questions on the final are unclear and could be better written. Would recommend the instructors or whomever created this course to eat their own cooking and go through this course and fix the various issues.

автор: David A S

14 июня 2022 г.

Excellent introduction to this topics. Labs contain all you need to know how to start using this type of technologies. Highly recommended.

автор: Mohamed A

10 июня 2022 г.

Thanks to all the instructor's efforts, one of the best DATA engineering courses, contains hands-on Experience with essential data tools.

автор: k b

24 апр. 2022 г.

Nice intro to ETL and Data Pipelines. Beginner level easy to follow hands on Airflow and Kafka.

автор: Rorisang S

14 мар. 2022 г.

Succinctly presented. Labs really hammered the point home :)

автор: Minh N T

12 апр. 2022 г.

Useful course for beginner Data engineer

автор: Chris W

3 апр. 2022 г.

A d​ecent overview of Airflow and Kafka. Worth it for the time invested. The labs were good, however the execution of the final assignment was poor -- you have to submit two dozen screen captures for a peer reviewed assignment. Taking screen caps of code is silly, why not just submit the code? Plus you are taking the caps before you even know if your code works. And you are relying on strangers to read and understand your code before you can get credit for the course. Fortunately, some kind soul found mine quickly and gave me 100%. My code did work -- I tested it thoroughly -- but you can't really tell from screen caps.

автор: Sina S S

7 мая 2022 г.

A good introductory course to airflow and kafka. Could have been broken up into at least two courses focusing on each of these platform, and going more in depth in each one. Also, the final assignment is a pain to complete especially due to some errors in instructions. But overall, It is a decent course.

автор: Markus Z

28 мар. 2022 г.

G​ood compact summary of the topics.

R​egarding the assignment: Good to have an environment for testing your code directly. Unfortunatly it was a bit unstable. Final assignment was a bit to much screenshots and lesser coding.

автор: Katarzyna G

26 мар. 2022 г.

I​t would be much better with real instructors and with no peer review that is not objecitve and no proper ansers clue

автор: David R

4 июня 2022 г.

Good introduction to Airflow and Kafka however only one airflow operator is explored

автор: Otto Z g

22 июня 2022 г.

It takes 1 hour to connect the lab and start the service.

автор: YANGYANG C

17 янв. 2022 г.

Love the labs, but do not like the robotic lectures.

автор: Mbaye B

14 мая 2022 г.

i​nteresting

автор: Krishnakumar K

12 апр. 2022 г.

good

автор: Yao G A

25 февр. 2022 г.

Cette note est du au fait du probleme de notation des examens. Le fait de laisser à l'appréciation des étudiants de juger de la bonne réponse basé sur uniquement que des indices... par exemple pour le Task 1.2 à 1.8 je crois avoir eu 2 presque partout maison ne m'en a donné que 1. Ce que je ne trouve pas vraiment juste

автор: Roberta B

3 апр. 2022 г.

Ok, Very good course, but during the exam the focus was a very difficult part made of commands of Linux Shell, expecially dealing with files that are not CSV. That was not the main focus of the course, actually.....