Drag and Drop Question Match the processes to the appropriate scenarios. To answer, drag the appropriate process from the column on the left to its scenario on the right. Each process may be used…

The correct answer is Extract, transform, and load (ETL) processing; Extract, load, and transform (ELT) processing; Data ingestion. ETL (Extract, Transform, and Load) processing is used when data must be transformed before loading into the destination, typically into a structured data warehouse where raw data is not stored. ELT (Extract, Load, and Transform) processing loads raw data into the destination…

Submitted by sofia.br· Mar 30, 2026Describe core data concepts and data processing workflows, including the differences between ETL, ELT, and data ingestion - typically aligned with Microsoft DP-900 (Azure Data Fundamentals) or similar foundational data certification objectives.

Question

Drag and Drop Question Match the processes to the appropriate scenarios. To answer, drag the appropriate process from the column on the left to its scenario on the right. Each process may be used once, more than once, or not at all. NOTE: Each correct match is worth one point. Answer:

Exhibit

Answer Area

Drag items

Data ingestionExtract, load, and transform (ELT) processingExtract, transform, and load (ETL) processing

Correct arrangement

Extract, transform, and load (ETL) processing
Extract, load, and transform (ELT) processing
Data ingestion

Explanation

ETL (Extract, Transform, and Load) processing is used when data must be transformed before loading into the destination, typically into a structured data warehouse where raw data is not stored. ELT (Extract, Load, and Transform) processing loads raw data into the destination system first (such as a data lake or cloud data warehouse), then transforms it using the destination's compute power. Data ingestion refers to the process of collecting and importing raw data from various sources into a storage system for immediate use or further processing, without implying a specific transformation order.

Topics

#Data Engineering#ETL vs ELT#Data Pipelines#Cloud Data Processing

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