DP-900 Describe an analytics workload on Azure Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Use SQL Server Integration Services (SSIS) to transfer data over the internet.

  Why it's wrong here

  SSIS (SQL Server Integration Services) is an ETL tool that can extract data from on-premises SQL Server and load it into Azure SQL Database or Blob Storage via the internet. However, all data movement is constrained by the actual network bandwidth available, so a massive initial load would take days or weeks and is prone to timeouts/instability. SSIS offers no offline shipping mechanism or bandwidth optimization, making it a poor choice when limited bandwidth is the bottleneck.

• ✓

  Use Azure Data Box to physically ship the data.

  Why this is correct

  Azure Data Box is Microsoft's offline transfer appliance: Microsoft ships you a ruggedized storage device, you copy the on-premises SQL data to it locally, ship it back, and Microsoft uploads it directly into your Azure storage account. This completely bypasses internet bandwidth limitations because the only upload occurs from Microsoft's datacenter over its high-speed internal network. Data Box is built specifically for large datasets (typically tens of TB) where online transfer would be impractically slow, and it includes AES-256 encryption and secure tracking.

• ✗

  Establish a site-to-site VPN and use Azure Data Factory.

  Why it's wrong here

  A site-to-site VPN creates a secure encrypted IPsec tunnel between your on-premises network and Azure, but it does not increase the underlying WAN link's capacity. Azure Data Factory can orchestrate the copy pipeline, but the data still crosses the same limited-bandwidth internet circuit, so the overall transfer time remains bottlenecked by that same constraint. For a one-time, multi-terabyte bulk load, establishing a VPN alone doesn't solve the fundamental throughput problem—it only secures the data path.

• ✗

  Use Azure Data Factory with a self-hosted integration runtime over the internet.

  Why it's wrong here

  Azure Data Factory with a self-hosted integration runtime (SHIR) places the copy engine on your infrastructure, but the data still travels online from the SHIR to Azure over the public internet (or a configured ExpressRoute, which isn't mentioned here). This setup enables enterprise-hardened, monitored pipelines, yet it's still an online movement method—identical bandwidth limitation applies. The SHIR does not provide any physical media or offline fallback, so it's not designed for the initial bulk migration of very large datasets when bandwidth is restricted.