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Google Exam Professional Machine Learning Engineer Topic 6 Question 102 Discussion

Actual exam question for Google's Professional Machine Learning Engineer exam
Question #: 102
Topic #: 6
[All Professional Machine Learning Engineer Questions]

You are responsible for building a unified analytics environment across a variety of on-premises data marts. Your company is experiencing data quality and security challenges when integrating data across the servers, caused by the use of a wide range of disconnected tools and temporary solutions. You need a fully managed, cloud-native data integration service that will lower the total cost of work and reduce repetitive work. Some members on your team prefer a codeless interface for building Extract, Transform, Load (ETL) process. Which service should you use?

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Suggested Answer: D

Cloud Data Fusion is a fully managed, cloud-native data integration service that helps users efficiently build and manage ETL/ELT data pipelines. It provides a graphical interface to increase time efficiency and reduce complexity, and allows users to easily create and explore data pipelines using a code-free, point and click visual interface. Cloud Data Fusion also supports a broad range of data sources and formats, including on-premises data marts, and ensures data quality and security by using built-in transformation capabilities and Cloud Data Loss Prevention. Cloud Data Fusion lowers the total cost of ownership by handling performance, scalability, availability, security, and compliance needs automatically.Reference:

Cloud Data Fusion documentation

Cloud Data Fusion overview


Contribute your Thoughts:

Val
3 days ago
Haha, I bet the developers of Cloud Data Fusion had a field day coming up with that name. But it does sound like the perfect solution for our needs.
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Catalina
3 days ago
I was leaning towards B) Dataprep, but D) Cloud Data Fusion makes more sense given the requirement for a codeless interface for ETL processes.
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Selma
9 days ago
I agree with Dorothea, Cloud Data Fusion seems like the best option to lower costs and reduce repetitive work.
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Gail
11 days ago
I agree, D) Cloud Data Fusion is the way to go. It's designed to handle data quality and security challenges across multiple data sources.
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Dorothea
12 days ago
I prefer Cloud Data Fusion because it offers a codeless interface for ETL processes.
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Leota
30 days ago
D) Cloud Data Fusion seems like the best option to me. It's a fully managed, cloud-native data integration service that can help us lower costs and reduce repetitive work.
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Matilda
3 days ago
D) Cloud Data Fusion is definitely the way to go for a fully managed, cloud-native data integration service.
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Rima
3 days ago
D) Cloud Data Fusion is definitely worth considering for a fully managed, cloud-native data integration service.
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Stephen
6 days ago
A) Dataflow could be a good option for a codeless interface for building ETL processes.
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Cristen
10 days ago
B) Dataprep could also be a good choice for simplifying the data preparation process.
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Kristine
28 days ago
A) Dataflow sounds like a good option for a codeless interface for building ETL processes.
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Levi
1 months ago
I think we should use Dataflow for building a unified analytics environment.
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