Assess your understanding of methods and best practices for handling large data sets on mobile devices, including storage optimization, file formats, performance, and data integrity techniques. This quiz helps users recognize effective strategies for mobile storage management in real-world scenarios.
When managing a large collection of images on a mobile device, which storage option is generally most space-efficient?
Explanation: External storage with compressed files saves significant space when handling large numbers of images, as compression reduces file size and external storage prevents excessive memory use. Storing uncompressed images in memory is inefficient and consumes too much RAM. Database storage without compression is better for structure, not space-saving. Saving images as plain text is impractical and inefficient in both file size and performance.
What technique helps improve performance when repeatedly accessing large data sets, such as a sorted contact list, on mobile devices?
Explanation: Indexing allows fast lookup and retrieval by creating references for data, significantly enhancing performance for sorted or searchable lists. Storing data randomly makes retrieval slow and inefficient. Using only primary keys without indexes doesn't optimize search for non-key fields. Ignoring the data structure prevents implementing improvements like indexing or efficient searching.
Which method is commonly used to verify the integrity of large files moved between mobile storage and cloud backup?
Explanation: Checksums provide a way to detect if a file has changed or become corrupted during transfer by generating a unique value for the file content. Disabling error-checking removes protection against corruption. Reducing file names only affects file identification. Compressing files alone does not verify or guarantee integrity.
Which of the following file formats is best for quickly reading large tabular datasets on a mobile device?
Explanation: CSV (Comma-Separated Values) files efficiently represent tables and are easy to parse in mobile environments, making them ideal for tabular datasets. Image and audio formats are not suitable for tables; they store visual or sound data, respectively. PDFs can include tables but are not optimized for quick programmatic reading.
What approach effectively reduces the storage space required for high-resolution videos on a mobile device?
Explanation: Video compression encodes video data to save space without substantially sacrificing quality, making it ideal for large video files. Changing file extensions has no effect on file size. Duplicating files increases storage use. Increasing playback speed changes the viewing experience but does not reduce storage requirements.
What is a good practice to prevent data loss when handling large data sets on mobile devices?
Explanation: Regular backups protect data against accidental loss, corruption, or device failure, helping ensure recovery for large datasets. Deleting files frequently can result in unwanted data loss. Temporary storage is erased often and doesn't guarantee long-term safety. Storing unnecessary redundant data wastes space without providing structured protection.
Why is it important to load large data sets in small chunks rather than all at once in a mobile app?
Explanation: Loading data in small chunks prevents excessive memory consumption, sustaining app performance and device stability, especially with limited mobile memory. Slowing down performance is not a goal. Making files unreadable or increasing battery use are incorrect and undesirable outcomes.
Which challenge is commonly faced when synchronizing large data sets across mobile devices?
Explanation: Large data synchronization can be slow and resource-intensive if network bandwidth is limited, making transfers longer and sometimes unreliable. Mobile devices do not have unlimited battery supply; this is unrealistic. Instant data transfer is usually not possible with large files. Data conflicts may occur during sync processes, so the last distractor is incorrect.
Which database type is commonly used for storing large but simple data tables on a mobile device?
Explanation: Relational databases efficiently store and manage structured data in tables with relationships, making them suitable for large, simple data sets on mobile devices. Flat image files and audio databases do not store tables. Video player cache is used for streaming, not structured data storage.
Which method helps keep large sensitive data sets secure when stored locally on a mobile device?
Explanation: Encryption converts data into a secure format, protecting it even if the device is lost or stolen. Disabling device lock or sharing files unencrypted exposes data to unauthorized access. Renaming files does not provide any real security; it only hides file names without protecting content.