15 March 2017

Data Management: Data Compression (Definitions)

"any kind of data reduction method that preserves the application-specific information." (Teuvo Kohonen, "Self-Organizing Maps 3rd Ed.", 2001)

"The process of reducing the size of data by use of mathematical algorithms." (Tom Petrocelli, "Data Protection and Information Lifecycle Management", 2005)

"1.Algorithms or techniques that change data to a smaller physical size that contains the same information. 2.The process of changing data to be stored in a smaller physical or logical space." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"Encoding information in such a way that its representation consumes less space in memory" (Hasso Plattner, "A Course in In-Memory Data Management: The Inner Mechanics of In-Memory Databases 2nd Ed.", 2014)

"Compression is a data management technique that uses repeating patterns in data to reduce the storage needed to hold the data. A compression algorithm for databases should perform compression and decompression operations as fast as possible. This often entails a trade-off between the speed of compression/decompression and the size of the compressed data. Faster compression algorithms can lead to larger compressed data than other, slower algorithms." (Dan Sullivan, "NoSQL for Mere Mortals®", 2015)

"Reducing the amount of space needed to store a piece of data" (Nell Dale & John Lewis, "Computer Science Illuminated" 6th Ed., 2015)

"The process of reducing the size of a data file by encoding information using fewer bits than the original file." (Faithe Wempen, "Computing Fundamentals: Introduction to Computers", 2015)

"A method that reduces the amount of space needed for storing data. See also client compression and hardware compression." (CommVault, "Documentation 11.20", 2018)

"Any technique used to reduce the amount of storage required to store data." (IEEE 610.5-1990)

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IT Professional with more than 24 years experience in IT in the area of full life-cycle of Web/Desktop/Database Applications Development, Software Engineering, Consultancy, Data Management, Data Quality, Data Migrations, Reporting, ERP implementations & support, Team/Project/IT Management, etc.