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Voltar para Modernizing Data Lakes and Data Warehouses with Google Cloud

Comentários e feedback de alunos de Modernizing Data Lakes and Data Warehouses with Google Cloud da instituição Google Cloud

2,428 classificações
301 avaliações

Sobre o curso

The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course....

Melhores avaliações

14 de Fev de 2020

Good introduction and overview of the field of data engineering, data lakes and modern data warehouses and a hands-on walkthrough of all the technologies related to solving these problems on GCP.

16 de Abr de 2020

A better understanding of BigQuery starts here. A vital resource for consultants, data analysts, and product managers, and an important reference source for engineers and data scientists.

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201 — 225 de 307 Avaliações para o Modernizing Data Lakes and Data Warehouses with Google Cloud

por Muhammad Z H

13 de Jun de 2020


por Rogelio E R C

21 de Abr de 2020


por Rachmat H

31 de Ago de 2021


por Jean C F

14 de Jun de 2021


por Lyndon A

15 de Out de 2020


por Julian D O H

2 de Ago de 2020


por Saptarshi S

15 de Jun de 2020


por Antony C

6 de Mai de 2020


por J J

24 de Abr de 2020


por Giovanni D P

11 de Abr de 2020

ok ok

por Gerardo F V

23 de Nov de 2020



4 de Nov de 2020


por Sangwoo K

2 de Out de 2020


por Gadamsetti V V N

10 de Jul de 2020


por Ratan K

9 de Jul de 2020


por Richa G

3 de Mai de 2020


por Hilmi A A

25 de Jan de 2020


por Krystian O

3 de Set de 2020

Very condensed course. A lot of stuff to go through which is great but links to code, refereed documentation etc would be very helpful, especially when only mentioned in a video and not shown. At some points its possible to pause the video to note down where reference material can be found.

por Sean D

12 de Jul de 2021

Good course. To make Great: 1) get some Intern (or better AI) to correct text, punctuation, etc., displayed below recordings. 2) allow video to be on separate screen, from text (without having to download text files). It would be nice to view video/graphics, while following the text.

por Xavier A A

29 de Abr de 2020

Evan & Lak's lectures are very good, it went so seamless, but listening to Julie's lectures is hard work, she is rapid, I needed subtitles to comprehend the speech. Other opinions might be different, but; these are genuine ones from me, please note that there is no bias in my mind.

por Pola, R (

20 de Abr de 2021

Provides a broad over view of GCP tools to build data pipelines, tools to build data lake and data warehouse and reference architecture to use. It helped me understand the GCP platform better and provided hands-on exercises which are very helpful.

por Shadab B

10 de Ago de 2021

Excellent course for beginner as I was not aware of the Data Lake and Warehouse concepts.Apart from that the course really explained in an efficient manner the concepts of Nesting , Partioning and clustering for Big Data.

por Vishal P

7 de Mai de 2020

Really Interesting. If possible add one migration example from existing data warehouse for one small subject area to BigQuery . It would give more comparable insight on power, design approach on BigQuery

por Alphanso W

16 de Abr de 2020

Good course but perhaps to make things stick, we would have used one project and built upon it. I felt like I was being tossed all over the place in terms of subjects and topics.

por Walter H

14 de Jan de 2022

bit simple for experienced db users, but the 2nd week does a very useful deep dive into advanced GBQ features like how to properly handle nested fields.