Comprehensive Microsoft Azure Data Engineer Certification (DP-203) Practice Test 2025 – Your All-in-One Guide to Exam Success!

Azure Data Lake Storage is designed to efficiently handle both structured and unstructured data, making it a versatile solution for various data scenarios. It leverages a hierarchical namespace that supports large-scale analytics and data processing workloads.

Structured data, such as tables in relational databases, can be stored in a straightforward format, while unstructured data, like images, videos, and text documents, can be ingested and stored in its native format without the need for a predefined schema. This flexibility allows organizations to store vast amounts of diverse data types, facilitating analytics, machine learning, and big data processing.

In contrast, the other options focus on a limited type of data. Some suggest the handling of only structured or only unstructured data, which does not reflect the capabilities of Azure Data Lake Storage. Additionally, stating that it handles exclusively binary data would overlook its support for various other formats and data types beyond just binary.