AZ-305 - Design Data Storage Solutions (22% of the exam) - Section 2.3

Design data integration solutions using Azure Data Factory, Azure Synapse Analytics, and Azure Databricks.

Design ETL and ELT pipelines using Azure Data Factory, Azure Synapse Analytics, and Azure Databricks to move and transform data at scale. Distinguish when each service is the better fit for orchestration, large-scale analytics, or advanced data transformation workloads.

Azure Data FactoryAzure Synapse AnalyticsAzure DatabricksETL and ELT pipelinesdata movement and transformation

Practice question for this objective

Free sampleDesign Data Storage Solutionsmedium

A team needs a managed Azure service whose primary job is orchestrating data movement across 90-plus connectors with code-free copy and mapping data flows, but it must not double as an analytics workspace. Which service fits the description?

ASelect Azure Synapse Analytics as the orchestration platform.
BSelect Azure Databricks as the orchestration platform.
CSelect Microsoft Fabric Real-Time Intelligence as the platform.
DSelect Azure Data Factory as the orchestration platform. Correct

ADF is the orchestration-only service; Synapse and Databricks bundle additional analytics workspaces. Azure Data Factory is the cloud ETL and data integration service with 90-plus connectors, mapping data flows on serverless Spark, and code-free copy activities. Its decision-table role is data movement and orchestration without bundling SQL pools or Spark pools as a workspace.

Why A is wrong: Synapse embeds the same ADF engine but also provides SQL pools, Spark pools, and Data Explorer; the requirement is explicitly to avoid an analytics workspace.

Why B is wrong: Databricks is a lakehouse and ML platform with notebook-driven pipelines, not a code-free 90-plus-connector ETL orchestrator.

Why C is wrong: Fabric Real-Time Intelligence is for streaming and log analytics, not the documented 90-plus-connector ETL orchestrator described.

Why D is correct: Correct. Azure Data Factory is the cloud ETL and data integration service with 90-plus connectors, mapping data flows on serverless Spark, and code-free copy activities.

See more AZ-305 practice questions, answers explained.

Exam traps in Design Data Storage Solutions

Answers that look right on this material and are not. Each one is a distractor from a different question in the AZ-305 bank for this domain.

Select Azure Databricks SQL Warehouse for the workload.
Why it is wrong: Databricks SQL Warehouse uses Databricks SQL, not T-SQL, and lacks the documented T-SQL PREDICT function and dedicated SQL pool model described.
Built-in T-SQL PREDICT scoring of machine-learning models.
Why it is wrong: T-SQL PREDICT is a Synapse SQL feature for scoring models inside SQL; ADF does not expose a native PREDICT surface.
Provision an Azure Files share using the SMB protocol.
Why it is wrong: SMB supports Windows, Linux, and macOS but does not provide native NFS semantics; the workload explicitly requires NFS.

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