Data Compression Practice Test

Read the passage. A media company publishes articles, photos, and videos and uses different compression methods depending on content. Compression reduces the number of bits needed by encoding patterns more efficiently, helping files download faster and cost less to store. Lossless compression preserves exact data and is favored for text, where accuracy matters, while lossy compression discards some information to achieve smaller files and is common for images and video. Huffman coding and LZW are lossless techniques often used for text or general data, while JPEG is a popular lossy format for still images. MPEG is widely used for video compression, often balancing quality against file size. Selecting the right method depends on whether perfect fidelity or smaller size is the priority.

Based on the text, how does Huffman coding differ from JPEG compression?

Read the passage. A cloud platform stores millions of customer documents and wants to reduce storage costs without changing any file contents. Data compression helps by representing repeated patterns more efficiently, lowering the number of bits needed to store data. Lossless compression is used when exact recovery matters, such as for text files, code, and spreadsheets, while lossy compression is common for media where small imperfections are acceptable. LZW is a lossless algorithm that builds a dictionary of repeated sequences and substitutes short codes, which can be effective when the same phrases or patterns appear many times. Huffman coding is also lossless, using shorter bit patterns for more frequent symbols. JPEG and MPEG, by contrast, are typically lossy and focus on shrinking images and video.

Which scenario best demonstrates the use of LZW compression?