What is ELT and why is advantageous with cloud data warehouses?

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Multiple Choice

What is ELT and why is advantageous with cloud data warehouses?

ELT means loading data in its raw form into the data warehouse and then performing transformations inside the warehouse using its processing power. In cloud data warehouses, storage and compute can scale independently, so you can ingest large volumes of raw data quickly without pre-processing. Once the data is inside the warehouse, you transform it with SQL or built-in processing, create curated tables or views, and reuse the raw data for future analyses. This approach is advantageous because it reduces data movement and pipeline complexity, preserves the original raw data for flexibility, and lets you leverage scalable, on-demand compute to run intensive transformations as needed. It also aligns well with handling semi-structured data and evolving analytics requirements. The other options describe pre-transforming data before loading, or avoiding warehouse compute, which misses the main benefit of ELT in a cloud environment.

ELT means loading data in its raw form into the data warehouse and then performing transformations inside the warehouse using its processing power. In cloud data warehouses, storage and compute can scale independently, so you can ingest large volumes of raw data quickly without pre-processing. Once the data is inside the warehouse, you transform it with SQL or built-in processing, create curated tables or views, and reuse the raw data for future analyses.

This approach is advantageous because it reduces data movement and pipeline complexity, preserves the original raw data for flexibility, and lets you leverage scalable, on-demand compute to run intensive transformations as needed. It also aligns well with handling semi-structured data and evolving analytics requirements. The other options describe pre-transforming data before loading, or avoiding warehouse compute, which misses the main benefit of ELT in a cloud environment.

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