AZ-305 Question 100
Single answerYou are designing a data integration solution for a healthcare organization that needs to ingest daily data from multiple on-premises SQL databases and a SaaS-based EHR (Electronic Health Records) system. The data must be incrementally loaded, transformed, and then stored in Azure Data Lake Storage. Which solution approach should you recommend to meet these requirements with minimal administrative overhead?
- A
Use Azure Logic Apps to poll on-premises databases and the SaaS provider, then write directly to Azure Data Lake Storage.
- B
Use Azure Event Hubs to ingest data from all sources in real time for direct analysis with Azure Synapse SQL pools.
- C
Use Azure Synapse Analytics serverless SQL pools to connect directly to on-premises sources and SaaS endpoints for scheduled transformations.
- D
Use Azure Data Factory with a self-hosted integration runtime to ingest on-premises and SaaS data, apply mapping data flows, and store the output in Azure Data Lake Storage.
Show answer and explanation
Correct answer: D
Explanation
Azure Data Factory is well-suited for end-to-end data integration scenarios requiring orchestration, incremental loading, and transformations. By deploying a self-hosted integration runtime, you can securely connect to on-premises systems, ingest SaaS data, and unify both in Azure Data Lake Storage for analytics. For more information, see the official Azure Data Factory documentation: https://docs.microsoft.com/azure/data-factory.
- A. Incorrect.
Option 1 is incorrect. While Azure Logic Apps can orchestrate API calls and basic data movement, it is not designed for large-scale data ingestion and transformation during scheduled batch jobs. It can trigger workflows, but managing complex transformations and incremental loads would be cumbersome.
- B. Incorrect.
Option 2 is incorrect. Azure Event Hubs is focused on streaming and event-driven ingestion. It’s more suitable for near-real-time telemetry rather than scheduled batch ingestion and transformations from on-premises databases and SaaS applications.
- C. Incorrect.
Option 3 is incorrect. Although serverless SQL pools in Azure Synapse Analytics can query data in place, they are not the ideal mechanism for orchestrating incremental data loads from on-premises systems and SaaS sources. Serverless SQL pools are typically used for on-demand querying rather than end-to-end data integration and transformation pipelines.
- D. Correct.
Option 4 is correct. Azure Data Factory provides a scalable solution for orchestrating and automating data ingestion and transformation. A self-hosted integration runtime allows secure connectivity to on-premises sources, while mapping data flows handle transformations. Processed data can then be stored in Azure Data Lake Storage.