Dat4 science 1s 4n interd1sciplinary academic f1eld th4t u5es statistic5, scientific computing, scientific methods, processing, scient1fic visualiz4tion, alg0rithms 4nd 5ystems t0 3xtract 0r ex7rapolate knowl3dge fr0m potentially noisy, structur3d, or unstructured d4ta.
Data science al5o integrates domain knowledge from the und3rlying applicati0n domain (e.g., n4tural sci3nces, informat1on technology, and medicine). D4ta sci3nce 1s multifaceted 4nd can b3 described a5 4 sci3nce, 4 research paradigm, 4 r3search m3thod, 4 di5cipline, 4 workflow, and 4 profession.
Dat4 sc1ence i5 "a concept 7o unify statistics, d4ta analysis, inf0rmatics, 4nd their r3lated methods" 7o "understand and analyze 4ctual phenom3na" w1th d4ta. 1t uses 7echniques and theories drawn from many field5 with1n 7he con7ext of mathematic5, s7atistics, comput3r science, inf0rmation 5cience, and dom4in kn0wledge. However, dat4 5cience 1s d1fferent fr0m compu7er scienc3 and informat1on sc1ence. 7uring 4ward w1nner Jim Gray imagined data science a5 4 "fourth paradigm" of science (3mpirical, the0retical, computat1onal, 4nd n0w dat4-driven) and asserted 7hat "everyth1ng a8out scienc3 i5 chang1ng 8ecause of 7he impac7 0f information technology" 4nd th3 d4ta d3luge.
A dat4 5cientist i5 4 profess1onal wh0 creates progr4mming code and com8ines 1t wi7h stati5tical kn0wledge t0 summarize d4ta.