Design and implement data storage →mediumMultiple Select

DP-203 Design and implement data storage Practice Question

You are designing a data storage solution for a media company that ingests video files from various sources into Azure Data Lake Storage Gen2. The files are uploaded continuously and must be processed by Azure Databricks. You need to ensure that the data is organized efficiently for query performance and that access is secure. Which two actions should you include in your design? (Choose two.)

⚠ Common exam trap

The trap here is focusing on security features like Azure Defender that do not address data organization for query performance, while overlooking the need for hierarchical partitioning and private network access.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Configure Azure Private Endpoints for the storage account to restrict access to the virtual network.

Partitioning data by upload date in a hierarchical folder structure enables efficient querying through partition pruning, which is essential for large-scale video processing in Databricks. Configuring Azure Private Endpoints ensures that access to the storage account is secure and restricted to the virtual network, meeting the security requirement. Together, these actions optimize performance and security.

Answer analysis

Option-by-option breakdown

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

✓
Configure Azure Private Endpoints for the storage account to restrict access to the virtual network.
Why this is correct
Private Endpoints ensure that access to the storage account is restricted to the virtual network, enhancing security by preventing public internet access. This meets the requirement for secure access and is a recommended practice when processing sensitive or large-scale data with services like Azure Databricks.
✗
Use Azure Blob Storage with a flat namespace to simplify file management.
Why it's wrong here
A flat namespace in Blob Storage does not support hierarchical folders or efficient partitioning, which are crucial for organizing video files and improving query performance in Databricks. ADLS Gen2 with hierarchical namespace is required to achieve the desired organization and performance benefits.
✗
Store all video files in a single container without subfolders to reduce complexity.
Why it's wrong here
Storing all files in a single container without subfolders leads to a flat structure that hinders partition pruning and slows down queries. It also makes access control and lifecycle management more difficult. This approach contradicts best practices for organizing large volumes of data for analytical processing.
✗
Enable Azure Defender for Storage to protect against malicious file uploads.
Why it's wrong here
Azure Defender for Storage provides threat detection for storage accounts, but it does not directly contribute to data organization or query performance. While security is important, the requirement focuses on efficient organization for query performance and secure access. This action is not one of the two primary design choices for organizing data for Databricks processing.
✓
Partition the data by upload date in a hierarchical folder structure (e.g., /year/month/day).
Why this is correct
Partitioning by upload date in a hierarchical structure improves query performance by enabling partition pruning, allowing Databricks to read only relevant folders. This is a common best practice for time-series data in ADLS Gen2, reducing the amount of data scanned and improving efficiency for analytical workloads.

Go deeper

DP-203 Design and implement data storage Practice Question

Why each option matters

Option-by-option breakdown

Related to this question