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Prepare and test your skills
Prepare and test your skills
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An organization is designing a data pipeline to process marketing analytics data collected from external advertising platforms. The analytics team wants to load the raw data directly into the cloud data warehouse first without pre-processing it in transit, and then use SQL scripts and Dataform to clean, model, and aggregate the data inside the warehouse.
Which data integration pattern and Google Cloud service strategy should the team implement?
The ELT (Extract, Load, Transform) pattern is a modern data integration strategy where raw data is extracted from source systems, loaded directly into the target data warehouse in its original format, and then transformed in place using the warehouse's built-in compute engine and SQL-based tooling such as Dataform or Data Manipulation Language (DML).
Unlike traditional ETL pipelines that require heavy transformation logic to execute before storage, ELT shifts the transformation step to BigQuery, which is purpose-built for high-performance SQL analytics and transformation modeling.
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