Snowflake SnowPro Certification Practice Test

How does Snowflake compare to Apache Spark in terms of management?

1. Higher manual data management

2. No need to manage data files

3. Dependency on Java coding

4. Limited SQL support

The correct answer is: No need to manage data files

The assertion that Snowflake requires no need to manage data files is accurate and emphasizes one of its main advantages over Apache Spark. Snowflake operates as a fully managed cloud data warehouse, which abstracts the complexities of underlying infrastructure management and data file handling from the user. With Snowflake, users do not have to worry about the physical storage of data, file formats, or the optimization of raw data files, as these processes are automated by the Snowflake platform. This allows users to focus on querying and analyzing their data using SQL without being bogged down by file management tasks. In contrast, Apache Spark typically requires more hands-on management regarding data files, format handling, and optimization, which involves data engineers and developers to ensure the environment is properly set up for processing. The other options reflect aspects that are not characteristic of Snowflake’s management style. Higher manual data management would imply an increased burden on the user for managing datasets, which is not the case with Snowflake. Dependency on Java coding suggests a requirement for programming knowledge to manage and manipulate data, which is less relevant in Snowflake due to its SQL-based querying capabilities. Lastly, claiming limited SQL support is misleading, as Snowflake is designed to provide extensive support for SQL, making it more accessible for