IBM Data Science Practice Test

Data engineers play a critical role in managing and optimizing the flow of data within organizations. Their primary tasks generally involve designing, building, and maintaining systems that store and process data efficiently, as well as developing infrastructure for data generation and collection.

The task of handling unstructured data formats is indeed something that data engineers may encounter, but it would not primarily be their main focus or expertise. Instead, they typically work with structured and semi-structured data, designing systems that process and transform these data types.

Performing ETL (Extract, Transform, Load) tasks and accessing data via SQL are foundational duties for data engineers. ETL tasks involve extracting data from various sources, transforming it into a suitable format, and then loading it into a database or data warehouse. SQL is a crucial tool for data engineers to query and manipulate data stored within relational databases.

The phrase "None of the above" implies that all the tasks listed are activities associated with data engineers, which is a true statement. Therefore, the correct understanding is that while data engineers may sometimes work with unstructured data, it is not the primary aspect of their role compared to the other tasks mentioned. This highlights that while data engineers can handle a wide array of data formats, their key responsibilities are