Azure Data Scientists Associate Practice Exam

Why is it recommended to use MLTable when the schema of data changes frequently?

1. It enhances visualization of data.

2. It allows for schema changes in a single location.

3. It supports data processing in real-time.

4. It is better suited for historical data.

The correct answer is: It allows for schema changes in a single location.

Using MLTable when the schema of data changes frequently is beneficial because it allows for schema changes to be managed in a single location. This means that rather than having to update multiple files or code sections whenever there is a schema change, the modifications can be made in one place. This centralized approach simplifies the management of the schema, reduces the risk of errors, and makes it easier to maintain consistency across various data sources. When schema changes occur often, maintaining a singular source of truth for the schema helps ensure that all data processing and model training processes are aligned with the latest schema definitions. By using MLTable, data scientists and engineers can avoid the complications that arise from disparate data structures, which can lead to inefficiencies and challenges in data handling and analysis. In contrast, the other options do not directly address the main benefit of MLTable in situations with frequently changing schemas. For example, while visualization is important, it does not impact how schema changes are managed. Similarly, while real-time processing and handling historical data are relevant capabilities, they do not specifically relate to the core advantage of managing schema changes in a unified manner.