Data deduplication aims to eliminate duplicate copies of data, thereby reducing the overall storage requirements.

Hashing is a widely used data deduplication technique that involves creating a unique fingerprint for each data block. Duplicate blocks can be identified by comparing their hashes.

Data compression aims to reduce the size of data without compromising its integrity. This helps in optimizing storage space and improving data transfer efficiency.

PNG (Portable Network Graphics) is a lossless data compression technique that preserves the original quality of the image. It is commonly used for graphics and illustrations.

Data deduplication focuses on identifying and removing duplicate copies of data, while data compression aims to reduce the size of data by eliminating redundant information.

LZ77 is a widely used data compression algorithm that works by identifying and replacing repeated sequences of data with pointers to their previous occurrences.

Data deduplication can significantly reduce storage costs by eliminating duplicate copies of data, which is particularly beneficial in big data environments where data volumes are immense.

Data deduplication can introduce additional computational overhead during data processing due to the need to identify and eliminate duplicate data.

Data compression can significantly reduce storage requirements by reducing the size of data, which is crucial in big data environments where data volumes are massive.

Data compression can introduce additional computational overhead during data processing due to the need to compress and decompress data.

A hash function is a mathematical function that takes a data block as input and generates a unique fingerprint, or hash value, for that data block.

Arithmetic coding is a data compression technique that utilizes statistical methods to assign shorter codes to more frequently occurring symbols and longer codes to less frequently occurring symbols.

In data deduplication, a chunk is a small unit of data, typically a few kilobytes in size, that is processed and deduplicated individually.

Data compression can introduce additional overhead during data retrieval, as the compressed data needs to be decompressed before it can be accessed.

Lossless data compression techniques preserve the original data exactly, while lossy techniques introduce some distortion in order to achieve a higher compression ratio.