Data compression

A process aimed at reducing the size of digital data by removing redundant information. This is accomplished by converting data into a more compact form, thereby reducing transmission time and data storage space. 

Basic principles of data compression Removing redundancy: 

Compression is based on eliminating repetitive fragments or frequently occurring values in the data. This may include replacing repetitive sequences with references or using shorter codes for frequently occurring data. 

Types of compression: 

There are two main types of compression, lossless compression and lossy compression. 

• Lossless compression allows full recovery of the original data, which is important for text files and programs. 
• Lossy compression is used for audio, video and images where some of the information can be discarded without significant degradation. 

Data compression in storage systems (storage) 

Data compression in storage is an important feature that helps to improve storage efficiency and performance. 

The main benefits of data compression in storage include: 

• Space savings:
  Reducing the amount of data stored allows less disk space to be used, which reduces hardware and support costs. 
• Increased throughput:
  Compressed data is transferred faster, improving overall system performance. 
• Automation:
  Modern storage systems often include automatic compression mechanisms that can detect and remove duplicate or redundant data without manual intervention. Overall, data compression in storage is a key tool for optimizing resource utilization and improving the efficiency of data storage and transmission.