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What are all of the BigQuery operations that Google charges for?
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Question 350 - Professional Data Engineer discussion

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You are architecting a data transformation solution for BigQuery. Your developers are proficient with SOL and want to use the ELT development technique. In addition, your developers need an intuitive coding environment and the ability to manage SQL as code. You need to identify a solution for your developers to build these pipelines. What should you do?

A.
Use Cloud Composer to load data and run SQL pipelines by using the BigQuery job operators.
Answers
A.
Use Cloud Composer to load data and run SQL pipelines by using the BigQuery job operators.
B.
Use Dataflow jobs to read data from Pub/Sub, transform the data, and load the data to BigQuery.
Answers
B.
Use Dataflow jobs to read data from Pub/Sub, transform the data, and load the data to BigQuery.
C.
Use Dataform to build, manage, and schedule SQL pipelines.
Answers
C.
Use Dataform to build, manage, and schedule SQL pipelines.
D.
Use Data Fusion to build and execute ETL pipelines
Answers
D.
Use Data Fusion to build and execute ETL pipelines
Suggested answer: C

Explanation:

To architect a data transformation solution for BigQuery that aligns with the ELT development technique and provides an intuitive coding environment for SQL-proficient developers, Dataform is an optimal choice. Here's why:

ELT Development Technique:

ELT (Extract, Load, Transform) is a process where data is first extracted and loaded into a data warehouse, and then transformed using SQL queries. This is different from ETL, where data is transformed before being loaded into the data warehouse.

BigQuery supports ELT, allowing developers to write SQL transformations directly in the data warehouse.

Dataform:

Dataform is a development environment designed specifically for data transformations in BigQuery and other SQL-based warehouses.

It provides tools for managing SQL as code, including version control and collaborative development.

Dataform integrates well with existing development workflows and supports scheduling and managing SQL-based data pipelines.

Intuitive Coding Environment:

Dataform offers an intuitive and user-friendly interface for writing and managing SQL queries.

It includes features like SQLX, a SQL dialect that extends standard SQL with features for modularity and reusability, which simplifies the development of complex transformation logic.

Managing SQL as Code:

Dataform supports version control systems like Git, enabling developers to manage their SQL transformations as code.

This allows for better collaboration, code reviews, and version tracking.

Dataform Documentation

BigQuery Documentation

Managing ELT Pipelines with Dataform

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asked 18/09/2024
Francinilo Leitao Ferreira
34 questions
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