The key goals of foldering in data analytics are:

1. Organize files into subfolders: This helps in maintaining a clean and organized workspace. It allows for easy navigation and retrieval of files when needed.

2. Keep project-related files together: This is crucial in data analytics where multiple files may be used for a single project. Keeping them together under a single folder helps in better management and reduces the chances of misplacing or losing any important file.

3. Assign metadata about the folders: Metadata provides additional information about the files and folders. This can include details like the creation date, last modified date, author, etc. This can be useful in tracking the history and usage of the files.

Transferring files from one place to another is not a key goal of foldering in data analytics. While it can be a part of the process, it is not the primary purpose of creating and managing folders.

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The key goals of foldering in data analytics are:

1. Organize files into subfolders: This helps in maintaining a clean and organized workspace. It allows for easy navigation and retrieval of files when needed.

2. Keep project-related files together: This is crucial in data analytics where multiple files may be used for a single project. Keeping them together under a single folder helps in better management and reduces the chances of misplacing or losing any important file.

3. Assign metadata about the folders: Metadata provides additional information about the files and folders. This can include details like the creation date, last modified date, author, etc. This can be useful in tracking the history and usage of the files.

Transferring files from one place to another is not a key goal of foldering in data analytics. While it can be a part of the process, it is not the primary purpose of creating and managing folders.

Knowee AI · Accepted Answer

The key goals of foldering in data analytics are:

1. Organize files into subfolders: This helps in maintaining a clean and organized workspace. It allows for easy navigation and retrieval of files when needed.

2. Keep project-related files together: This is crucial in data analytics where multiple files may be used for a single project. Keeping them together under a single folder helps in better management and reduces the chances of misplacing or losing any important file.

3. Assign metadata about the folders: Metadata provides additional information about the files and folders. This can include details like the creation date, last modified date, author, etc. This can be useful in tracking the history and usage of the files.

Transferring files from one place to another is not a key goal of foldering in data analytics. While it can be a part of the process, it is not the primary purpose of creating and managing folders.

Question 2What are the key goals of foldering in data analytics? Select all that apply.1 pointTransfer files from one place to anotherOrganize files into subfoldersKeep project-related files togetherAssign metadata about the folders

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