Which combination lists the four data ingestion methods for loading data into a Fabric data warehouse?

Which combination lists the four data ingestion methods for loading data into a Fabric data warehouse?

• A. Data pipelines, dataflows, cross-warehouse, and Data Wrangler.
• B. COPY (Transact-SQL) statement, data pipelines, dataflows, and cross-warehouse.
• C. COPY (Transact-SQL) statement, data pipelines, dataflows, and cross-platform ingestion.
• D. COPY (Transact-SQL) statement, data pipelines, dataflows, and cross-warehouse.

Answer: (B)

Ingesting data into a Fabric data warehouse happens through four primary channels: the COPY statement using Transact-SQL, data pipelines, dataflows, and cross-warehouse ingestion. The COPY (Transact-SQL) statement provides a SQL-based method to load data directly from files or external sources into tables, which is essential for bulk or automated loading. Data pipelines automate end-to-end movement and transformation of data into the warehouse, coordinating sources, processing, and loading. Dataflows offer a user-friendly, UI-driven way to prepare, shape, and load data into Fabric, often used for shaping data before it lands in the warehouse. Cross-warehouse ingestion enables pulling data from other warehouses into Fabric, supporting integration or migration scenarios. The other options mix tools or terms that aren’t recognized as ingestion methods in this context (for example, Data Wrangler is a data preparation tool rather than an ingestion channel, and cross-platform ingestion isn’t the standard Fabric term), so they don’t represent the complete set of ingestion methods.

Ingesting data into a Fabric data warehouse happens through four primary channels: the COPY statement using Transact-SQL, data pipelines, dataflows, and cross-warehouse ingestion. The COPY (Transact-SQL) statement provides a SQL-based method to load data directly from files or external sources into tables, which is essential for bulk or automated loading. Data pipelines automate end-to-end movement and transformation of data into the warehouse, coordinating sources, processing, and loading. Dataflows offer a user-friendly, UI-driven way to prepare, shape, and load data into Fabric, often used for shaping data before it lands in the warehouse. Cross-warehouse ingestion enables pulling data from other warehouses into Fabric, supporting integration or migration scenarios. The other options mix tools or terms that aren’t recognized as ingestion methods in this context (for example, Data Wrangler is a data preparation tool rather than an ingestion channel, and cross-platform ingestion isn’t the standard Fabric term), so they don’t represent the complete set of ingestion methods.