{"id":3359,"date":"2013-07-13T01:04:30","date_gmt":"2013-07-12T18:04:30","guid":{"rendered":"http:\/\/science-technology.vn\/?p=3359"},"modified":"2013-10-31T09:49:31","modified_gmt":"2013-10-31T02:49:31","slug":"xu-huong-du-lieu-lon","status":"publish","type":"post","link":"https:\/\/science-technology.vn\/?p=3359","title":{"rendered":"Xu h\u01b0\u1edbng Big Data"},"content":{"rendered":"

Trong nhi\u1ec1u n\u0103m, \u1ea4n \u0110\u1ed9 \u0111\u00e3 chi ph\u1ed1i th\u1ecb tr\u01b0\u1eddng l\u00e0m kho\u00e1n ngo\u00e0i c\u00f4ng ngh\u1ec7 th\u00f4ng tin (CNTT) nh\u01b0ng s\u1ef1 vi\u1ec7c c\u00f3 th\u1ec3 thay \u0111\u1ed5i n\u1eefa. Con s\u00f3ng ti\u1ebfp c\u1ee7a kho\u00e1n ngo\u00e0i CNTT kh\u00f4ng c\u00f2n l\u00e0 “vi\u1ebft m\u00e3 v\u00e0 ki\u1ec3m th\u1eed” hay “ph\u00e1t tri\u1ec3n \u1ee9ng d\u1ee5ng” m\u00e0 l\u00e0 ph\u00e2n t\u00edch D\u1eef li\u1ec7u l\u1edbn Big Data n\u01a1i c\u00e1c c\u00f4ng ti to\u00e0n c\u1ea7u s\u1eb5n l\u00f2ng chi v\u00e0i tri\u1ec7u cho t\u1edbi t\u1ec9 \u0111\u00f4 la m\u1ed7i n\u0103m cho c\u00e1c c\u00f4ng ti hay n\u01b0\u1edbc c\u00f3 th\u1ec3 cung c\u1ea5p c\u00f4ng nh\u00e2n c\u00f3 k\u0129 n\u0103ng trong l\u0129nh v\u1ef1c n\u00e0y. M\u1ed9t quan ch\u1ee9c \u0111i\u1ec1u h\u00e0nh \u1ea4n \u0110\u1ed9 than: \u201cQui t\u1eafc \u0111\u00e3 \u0111\u1ed5i r\u1ed3i, kh\u00f4ng c\u00f2n l\u00e0 chi ph\u00ed th\u1ea5p h\u01a1n m\u00e0 l\u00e0 k\u0129 n\u0103ng cao h\u01a1n v\u00e0 \u0111i\u1ec1u \u0111\u00f3 l\u00e0m cho ch\u00fang t\u00f4i b\u1ecb ng\u1ea1c nhi\u00ean. Ch\u00fang t\u00f4i s\u1ebd c\u1ea7n ph\u00e1t tri\u1ec3n nhi\u1ec1u ng\u01b0\u1eddi v\u1edbi k\u0129 n\u0103ng n\u00e0y m\u1ed9t c\u00e1ch nhanh ch\u00f3ng.\u201d\u00a0<\/span><\/p>\n

Big Data l\u00e0 v\u1ec1 thu th\u1eadp kh\u1ed1i l\u01b0\u1ee3ng th\u00f4ng tin bao la m\u00e0 m\u1ed9t c\u00f4ng ti c\u00f3 trong n\u1ed9i b\u1ed9, t\u1ed5 h\u1ee3p ch\u00fang v\u1edbi c\u00e1c ngu\u1ed3n b\u00ean ngo\u00e0i nh\u01b0 internet r\u1ed3i ph\u00e2n t\u00edch ch\u00fang \u0111\u1ec3 thu \u0111\u01b0\u1ee3c th\u00f4ng tin c\u00f3 gi\u00e1 tr\u1ecb nh\u01b0 xu h\u01b0\u1edbng v\u00e0 c\u01a1 h\u1ed9i. C\u00e1c c\u00f4ng ti to\u00e0n c\u1ea7u c\u1ea7n t\u1edbi Big Data \u0111\u1ec3 nh\u1eadn di\u1ec7n th\u1ecb tr\u01b0\u1eddng kinh doanh m\u1edbi v\u00e0 d\u00f9ng ph\u00e2n t\u00edch nh\u01b0 v\u1eady \u0111\u1ec3 gi\u00fap m\u1ed9t c\u00e1ch hi\u1ec7u qu\u1ea3 cho ng\u01b0\u1eddi qu\u1ea3n l\u00ed ra quy\u1ebft \u0111\u1ecbnh. Ch\u1eb3ng h\u1ea1n, ng\u01b0\u1eddi ph\u00e2n t\u00edch Big Data d\u00f9ng ph\u00e2n t\u00edch xu h\u01b0\u1edbng \u0111\u1ec3 hi\u1ec3u chi\u1ec1u h\u01b0\u1edbng th\u1ecb tr\u01b0\u1eddng, nhu c\u1ea7u c\u1ee7a kh\u00e1ch h\u00e0ng \u0111\u1ec3 ph\u00e1t tri\u1ec3n s\u1ea3n ph\u1ea9m m\u1edbi tr\u01b0\u1edbc khi ng\u01b0\u1eddi kh\u00e1c th\u1eadm ch\u00ed bi\u1ebft v\u1ec1 n\u00f3. N\u00f3 c\u0169ng ph\u00e2n t\u00edch xu h\u01b0\u1edbng c\u1ee7a c\u00f4ng nghi\u1ec7p v\u00e0 th\u1ecb tr\u01b0\u1eddng t\u01b0\u01a1ng lai \u0111\u1ec3 qu\u1ea3n l\u00ed to\u00e0n th\u1ec3 d\u00e2y chuy\u1ec1n cung c\u1ea5p, t\u1eeb v\u1eadt t\u01b0 th\u00f4 t\u1edbi ch\u1ebf t\u1ea1o, t\u1eeb c\u00e1c k\u00eanh ph\u00e2n ph\u1ed1i cho t\u1edbi \u0111\u1ea1i l\u00ed b\u00e1n l\u1ebb, \u0111\u1ec3 c\u1eaft gi\u1ea3m chi ph\u00ed v\u1eadn h\u00e0nh v\u00e0 l\u00e0m c\u1ef1c \u0111\u1ea1i l\u1ee3i nhu\u1eadn.<\/p>\n

Big Data c\u0169ng \u0111\u01b0\u1ee3c d\u00f9ng trong th\u1ecb tr\u01b0\u1eddng t\u00e0i ch\u00ednh \u0111\u1ec3 d\u1ef1 b\u00e1o xu h\u01b0\u1edbng th\u01b0\u01a1ng m\u1ea1i. Hi\u1ec7n th\u1eddi th\u1ecb tr\u01b0\u1eddng ch\u1ee9ng kho\u00e1n l\u00e0 linh \u0111\u1ed9ng do hi\u1ec7u \u1ee9ng c\u1ee7a cu\u1ed9c kh\u1ee7ng ho\u1ea3ng t\u00e0i ch\u00ednh cho n\u00ean h\u1ea7u h\u1ebft ng\u01b0\u1eddi l\u00e0m th\u01b0\u01a1ng m\u1ea1i \u0111\u1ec1u r\u1ea5t th\u1eadn tr\u1ecdng b\u1edfi v\u00ec kinh t\u1ebf M\u0129 v\u1eabn c\u00f2n \u0111ang ph\u1ee5c h\u1ed3i; Li\u00ean hi\u1ec7p ch\u00e2u \u00c2u \u0111ang trong kh\u1ee7ng ho\u1ea3ng; th\u1ecb tr\u01b0\u1eddng Trung Qu\u1ed1c ch\u1eadm h\u01a1n \u0111\u01b0\u1ee3c mong \u0111\u1ee3i; Trung \u0110\u00f4ng \u0111ang d\u01b0\u1edbi t\u00ecnh hu\u1ed1ng h\u1ed7n \u0111\u1ed9n v.v. Trong t\u00ecnh hu\u1ed1ng n\u00e0y, \u00edt ng\u01b0\u1eddi d\u00e1m l\u00e0m n\u01b0\u1edbc \u0111i t\u00e1o b\u1ea1o n\u00e0o. Nh\u01b0ng v\u1edbi vi\u1ec7c d\u00f9ng Big Data, m\u1ed9t s\u1ed1 c\u00f4ng ti th\u01b0\u01a1ng m\u1ea1i c\u00f3 kh\u1ea3 n\u0103ng nh\u1eadn di\u1ec7n nh\u1eefng xu h\u01b0\u1edbng n\u00e0o \u0111\u00f3 m\u1ed9t c\u00e1ch nhanh ch\u00f3ng v\u00e0 n\u1eafm l\u1ea5y c\u01a1 h\u1ed9i. Khi ph\u1ea7n l\u1edbn m\u1ecdi ng\u01b0\u1eddi \u0111ang m\u1ea5t ti\u1ec1n v\u00e0o th\u1ecb tr\u01b0\u1eddng ch\u1ee9ng kho\u00e1n, nh\u1eefng c\u00f4ng ti th\u01b0\u01a1ng m\u1ea1i n\u00e0y \u0111ang th\u1eafng l\u1edbn. N\u1ebfu b\u1ea1n nh\u00ecn v\u00e0o vi\u1ec7c l\u00e0m \u0111\u01b0\u1ee3c c\u1ea7n trong t\u1ea1p ch\u00ed Wall Street Journal, b\u1ea1n c\u00f3 th\u1ec3 th\u1ea5y m\u1ecdi c\u00f4ng ti th\u01b0\u01a1ng m\u1ea1i \u0111\u1ec1u \u0111ang thu\u00ea nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u v\u00e0 ng\u01b0\u1eddi ph\u00e2n t\u00edch d\u1eef li\u1ec7u v\u00e0 c\u1ea1nh tranh l\u00e0 d\u1eef d\u1ed9i.<\/p>\n

V\u00ec \u0111\u00e2y l\u00e0 l\u0129nh v\u1ef1c t\u01b0\u01a1ng \u0111\u1ed1i m\u1edbi, ch\u1ec9 c\u00f3 v\u00e0i \u0111\u1ea1i h\u1ecdc h\u00e0ng \u0111\u1ea7u m\u1edbi cung c\u1ea5p \u0111\u00e0o t\u1ea1o cho n\u00ean c\u00f3 thi\u1ebfu h\u1ee5t l\u1edbn v\u1ec1 c\u00f4ng nh\u00e2n Big Data v\u00e0 nhu c\u1ea7u \u0111ang t\u0103ng nhanh. Theo b\u00e1o c\u00e1o c\u00f4ng nghi\u1ec7p, m\u1ed9t m\u00ecnh M\u0129 s\u1ebd c\u1ea7n 250,000 nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u \u0111\u1ebfn n\u0103m 2015 v\u00e0 nhu c\u1ea7u to\u00e0n th\u1ebf gi\u1edbi c\u00f3 th\u1ec3 \u0111\u1ea9y con s\u1ed1 n\u00e0y l\u00ean t\u1edbi tri\u1ec7u. K\u0129 n\u0103ng Big Data l\u00e0 t\u1ed5 h\u1ee3p c\u1ee7a to\u00e1n h\u1ecdc, th\u1ed1ng k\u00ea, h\u1ecdc m\u00e1y, v\u00e0 khoa h\u1ecdc m\u00e1y t\u00ednh. C\u00e1c nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u l\u00e0m vi\u1ec7c tr\u00ean d\u1eef li\u1ec7u th\u1eddi gian th\u1ef1c \u0111\u01b0\u1ee3c thu th\u1eadp t\u1eeb nhi\u1ec1u ngu\u1ed3n \u0111\u1ec3 l\u00e0m ph\u00e2n t\u00edch d\u1ef1 b\u00e1o v\u1ec1 xu h\u01b0\u1edbng th\u1ecb tr\u01b0\u1eddng \u0111i\u1ec1u c\u00f3 th\u1ec3 gi\u00fap cho c\u1ea5p qu\u1ea3n l\u00ed \u0111\u1eb7t ra ph\u01b0\u01a1ng h\u01b0\u1edbng, ra quy\u1ebft \u0111\u1ecbnh v\u1ec1 th\u1ecb tr\u01b0\u1eddng t\u01b0\u01a1ng lai. Th\u00e1ng tr\u01b0\u1edbc, t\u1ea1p ch\u00ed \u201cHarvard Business Review\u201d \u0111\u00e3 g\u1ecdi Nh\u00e0 khoa h\u1ecdc D\u1eef li\u1ec7u l\u00e0 “Ngh\u1ec1 nghi\u1ec7p \u0111\u01b0\u1ee3c ham mu\u1ed1n nh\u1ea5t c\u1ee7a th\u1ebf k\u1ec9 21.” V\u00e0 c\u00e1c c\u00f4ng ti th\u01b0\u01a1ng m\u1ea1i ch\u1ee9ng kho\u00e1n Wall Street coi ph\u00e2n t\u00edch Big Data l\u00e0 t\u01b0\u01a1ng lai c\u1ee7a m\u1ecdi giao t\u00e1c kinh doanh t\u00e0i ch\u00ednh.<\/p>\n

Hi\u1ec7n th\u1eddi, Big Data \u0111ang n\u1ed5i l\u00ean nh\u01b0 th\u1ecb tr\u01b0\u1eddng sinh l\u1eddi nh\u1ea5t cho c\u00e1c c\u00f4ng ti l\u00e0m kho\u00e1n ngo\u00e0i CNTT v\u1edbi gi\u00e1 tr\u1ecb th\u1ecb tr\u01b0\u1eddng \u0111\u01b0\u1ee3c \u01b0\u1edbc l\u01b0\u1ee3ng qu\u00e3ng $1 t\u1ec9 \u0111\u00f4 la n\u0103m 2015. V\u00ec n\u00f3 l\u00e0 khu v\u1ef1c m\u1edbi m\u00e0 c\u00f3 \u00edt c\u1ea1nh tranh cho n\u00ean cu\u1ed9c \u0111ua n\u1eafm l\u1ea5y c\u01a1 h\u1ed9i n\u00e0y v\u00e0 th\u00e2u t\u00f3m th\u1ecb tr\u01b0\u1eddng n\u00e0y \u0111\u00e3 b\u1eaft \u0111\u1ea7u gi\u1eefa c\u00e1c c\u00f4ng ti tr\u00ean kh\u1eafp th\u1ebf gi\u1edbi. M\u1ed9t nh\u00e0 ph\u00e2n t\u00edch Wall Street n\u00f3i: \u201cS\u1ef1 ph\u00e1t tri\u1ec3n nhanh c\u1ee7a m\u1ea1ng x\u00e3 h\u1ed9i v\u00e0 m\u1ea1ng tr\u1ef1c tuy\u1ebfn kh\u00e1c \u0111\u00e3 cung c\u1ea5p nhi\u1ec1u d\u1eef li\u1ec7u th\u1ebf tr\u00ean Internet. \u0110i\u1ec1u ch\u00fang t\u00f4i c\u1ea7n l\u00e0 n\u1eafm l\u1ea5y nh\u1eefng d\u1eef li\u1ec7u c\u00f3 gi\u00e1 tr\u1ecb n\u00e0y, ph\u00e2n t\u00edch ch\u00fang v\u1ec1 xu h\u01b0\u1edbng \u0111\u1ec3 cho ch\u00fang t\u00f4i c\u00f3 th\u1ec3 ra quy\u1ebft \u0111\u1ecbnh th\u1ecb tr\u01b0\u1eddng m\u1ed9t c\u00e1ch nhanh ch\u00f3ng. Ch\u00fang t\u00f4i c\u1ea7n nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u \u0111\u1ec3 ti\u00eam th\u00eam h\u00e0o h\u1ee9ng v\u00e0o trong th\u1ecb tr\u01b0\u1eddng ch\u1ee9ng kho\u00e1n.\u201d<\/p>\n

Nhi\u1ec1u sinh vi\u00ean b\u1ecb l\u1eabn l\u1ed9n v\u00ec kh\u00e1c bi\u1ec7t gi\u1eefa Big Data v\u00e0 nh\u1eefng l\u0129nh v\u1ef1c \u0111\u00e3 \u0111\u01b0\u1ee3c thi\u1ebft l\u1eadp ch\u1eafc kh\u00e1c nh\u01b0 qu\u1ea3n tr\u1ecb c\u01a1 s\u1edf d\u1eef li\u1ec7u, qu\u1ea3n l\u00ed d\u1eef li\u1ec7u, khai ph\u00e1 d\u1eef li\u1ec7u v\u00e0 trinh s\u00e1t doanh nghi\u1ec7p. Kh\u00e1c bi\u1ec7t then ch\u1ed1t l\u00e0 c\u00e1c l\u0129nh v\u1ef1c kh\u00e1c \u0111ang thu th\u1eadp v\u00e0 qu\u1ea3n l\u00ed d\u1eef li\u1ec7u t\u1eeb c\u01a1 s\u1edf d\u1eef li\u1ec7u quan h\u1ec7 c\u1ee7a c\u00f4ng ti \u0111\u1ec3 ph\u00e2n t\u00edch v\u00e0 sinh ra b\u00e1o c\u00e1o. B\u00e1o c\u00e1o n\u00e0y b\u1ecb gi\u1edbi h\u1ea1n v\u00e0o d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c thu th\u1eadp v\u00e0 \u0111\u01b0\u1ee3c l\u01b0u gi\u1eef b\u00ean trong c\u01a1 s\u1edf d\u1eef li\u1ec7u c\u1ee7a c\u00f4ng ti v\u00e0 nh\u1eefng d\u1eef li\u1ec7u n\u00e0y \u0111\u1ec1u \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh r\u00f5 v\u00e0 c\u00f3 c\u1ea5u tr\u00fac.<\/p>\n

Nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u l\u1edbn thu th\u1eadp d\u1eef li\u1ec7u t\u1eeb c\u1ea3 c\u00e1c ngu\u1ed3n b\u00ean trong V\u00c0 b\u00ean ngo\u00e0i nh\u01b0 internet v.v. \u0110i\u1ec1u n\u00e0y l\u00e0 kh\u00f3 h\u01a1n b\u1edfi v\u00ec d\u1eef li\u1ec7u t\u1eeb c\u00e1c ngu\u1ed3n ngo\u00e0i ph\u1ea7n l\u1edbn l\u00e0 kh\u00f4ng \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh r\u00f5 v\u00e0 kh\u00f4ng c\u00f3 c\u1ea5u tr\u00fac r\u00f5. Ch\u1eb3ng h\u1ea1n, web \u0111\u1ea7y nh\u1eefng \u201c\u1ee9ng d\u1ee5ng \u0111\u01b0\u1ee3c d\u1eabn l\u00e1i b\u1edfi d\u1eef li\u1ec7u.\u201d G\u1ea7n nh\u01b0 b\u1ea5t k\u00ec \u1ee9ng d\u1ee5ng e-commerce n\u00e0o c\u0169ng l\u00e0 \u1ee9ng d\u1ee5ng \u0111\u01b0\u1ee3c d\u1eabn l\u00e1i b\u1edfi d\u1eef li\u1ec7u. C\u00e1c m\u1ea1ng x\u00e3 h\u1ed9i nh\u01b0 Facebook, Linkedln \u0111\u1ea7y nh\u1eefng d\u1eef li\u1ec7u x\u00e3 h\u1ed9i v\u00e0 c\u00e1 nh\u00e2n. C\u00f3 m\u1ecdi ki\u1ec3u d\u1eef li\u1ec7u \u0111\u1eb1ng sau t\u1eebng m\u1eb7t ti\u1ec1n web, v\u00e0 ph\u1ea7n m\u1ec1m gi\u1eefa k\u1ebft n\u1ed1i \u00a0c\u00e1c c\u01a1 s\u1edf d\u1eef li\u1ec7u kh\u00e1c v\u00e0 d\u1ecbch v\u1ee5 d\u1eef li\u1ec7u nh\u01b0 c\u00f4ng ti th\u1ebb t\u00edn d\u1ee5ng, ng\u00e2n h\u00e0ng v.v. \u0110\u00f3 l\u00e0 l\u00ed do t\u1ea1i sao kh\u1ed1i l\u01b0\u1ee3ng d\u1eef li\u1ec7u l\u00e0 r\u1ea5t l\u1edbn. V\u1ec1 trung b\u00ecnh, nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u ph\u1ea3i ph\u00e2n t\u00edch qu\u00e3ng 3.5 zettabytes m\u1ed9t n\u0103m (M\u1ed9t zettabyte l\u00e0 m\u1ed9t ngh\u00ecn t\u1ec9 gigabytes hay m\u1ed9t t\u1ec9 terabytes). V\u00c0 nh\u1eefng d\u1eef li\u1ec7u n\u00e0y l\u1ea1i thay \u0111\u1ed5i v\u00e0 t\u0103ng tr\u01b0\u1edfng m\u1ecdi gi\u00e2y hay ph\u00fat. \u0110\u00f3 l\u00e0 l\u00ed do t\u1ea1i sao n\u00f3 c\u1ea7n c\u00e1c k\u0129 n\u0103ng v\u00e0 thu\u1eadt to\u00e1n kh\u00e1c \u0111\u1ec3 th\u1ef1c hi\u1ec7n ph\u00e2n t\u00edch.<\/p>\n

Cho d\u00f9 n\u00f3 l\u00e0 l\u0129nh v\u1ef1c t\u01b0\u01a1ng \u0111\u1ed1i m\u1edbi, Big Data \u0111\u00e3 \u0111\u01b0\u1ee3c d\u00f9ng \u1edf M\u0129 n\u01a1i nh\u1eefng ph\u00e2n t\u00edch nh\u01b0 v\u1eady \u0111ang sinh ra c\u00e1c th\u0103m d\u00f2 \u00fd ki\u1ebfn c\u00f4ng ch\u00fang, d\u1ef1 b\u00e1o k\u1ebft qu\u1ea3 b\u1ea7u c\u1eed, d\u1ef1 b\u00e1o xu h\u01b0\u1edbng th\u1ecb tr\u01b0\u1eddng ch\u1ee9ng kho\u00e1n, ph\u00e2n t\u00edch giao t\u00e1c t\u00e0i ch\u00ednh to\u00e0n c\u1ea7u v\u00e0 ph\u00e1t tri\u1ec3n c\u00e1c chi\u1ebfn l\u01b0\u1ee3c cho ch\u00ednh ph\u1ee7 v\u00e0 c\u00e1c c\u00f4ng ti t\u01b0 nh\u00e2n. Ng\u00e0y nay m\u1ecdi c\u00f4ng ti \u0111\u1ec1u t\u00ecm c\u00e1c c\u00f4ng nh\u00e2n c\u00f3 nh\u1eefng k\u0129 n\u0103ng n\u00e0y \u0111\u1ec3 l\u00e0m vi\u1ec7c tr\u00ean c\u00e1c d\u1ef1 \u00e1n d\u1eef li\u1ec7u l\u1edbn c\u1ee7a h\u1ecd v\u00e0 h\u1ecd s\u1ebd n\u1eafm l\u1ea5y b\u1ea5t k\u00ec ng\u01b0\u1eddi t\u1ed1t nghi\u1ec7p n\u00e0o c\u00f3 hay kh\u00f4ng c\u00f3 kinh nghi\u1ec7m \u0111\u1ec3 \u0111\u00e0o t\u1ea1o h\u1ecd v\u1ec1 Big Data. M\u1ed9t nh\u00e0 ph\u00e2n t\u00edch c\u00f4ng nghi\u1ec7p n\u00f3i: “Kh\u00f4ng c\u00f3 v\u1ea5n \u0111\u1ec1 l\u00e0 c\u00e1c c\u00f4ng ti s\u1ebd c\u1ea7n k\u0129 n\u0103ng n\u00e0y \u0111\u1ec3 thu \u0111\u01b0\u1ee3c \u01b0u th\u1ebf c\u1ea1nh tranh trong th\u1ecb tr\u01b0\u1eddng c\u1ea1nh tranh cao n\u00e0y v\u00e0 ai c\u00f3 c\u00f4ng nh\u00e2n c\u00f3 ph\u1ea9m ch\u1ea5t nh\u1ea5t s\u1ebd th\u1eafng.\u201d<\/p>\n

V\u1ec1 c\u0103n b\u1ea3n c\u00f3 b\u1ed1n lo\u1ea1i vi\u1ec7c l\u00e0m trong khu v\u1ef1c Big Data:<\/p>\n

1)\u00a0\u00a0\u00a0\u00a0Nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u: Vi\u1ec7c l\u00e0m n\u00e0y th\u01b0\u1eddng y\u00eau c\u1ea7u b\u1eb1ng c\u1ea5p chuy\u00ean s\u00e2u (th\u1ea1c s\u0129 hay ti\u1ebfn s\u0129) trong khoa h\u1ecdc m\u00e1y t\u00ednh, k\u0129 ngh\u1ec7 ph\u1ea7n m\u1ec1m, th\u1ed1ng k\u00ea, tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o, v\u00e0 h\u1ecdc m\u00e1y. Nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u thi\u1ebft k\u1ebf c\u00e1c ch\u01b0\u01a1ng tr\u00ecnh \u0111\u1eb7c bi\u1ec7t v\u00e0 thu\u1eadt to\u00e1n \u0111\u1ec3 thu th\u1eadp v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u. Ng\u01b0\u1eddi \u0111\u00f3 ch\u1ecbu tr\u00e1ch nhi\u1ec7m \u0111\u1eb7t ra chi\u1ebfn l\u01b0\u1ee3c d\u1eef li\u1ec7u v\u00e0 th\u1ef1c hi\u1ec7n m\u1ecdi s\u1ea3n ph\u1ea9m d\u1eef li\u1ec7u cho c\u00f4ng ti. Nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u l\u00e0m vi\u1ec7c v\u1edbi kh\u1ed1i l\u01b0\u1ee3ng d\u1eef li\u1ec7u l\u1edbn \u0111\u01b0\u1ee3c thu th\u1eadp t\u1eeb c\u1ea3 b\u00ean trong v\u00e0 b\u00ean ngo\u00e0i c\u00f4ng ti \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh nh\u1eefng d\u1eef li\u1ec7u n\u00e0y c\u00f3 ngh\u0129a g\u00ec v\u00e0 ch\u00fang t\u00e1c \u0111\u1ed9ng th\u1ebf n\u00e0o l\u00ean c\u00f4ng ti.<\/p>\n

2)\u00a0\u00a0\u00a0\u00a0Ki\u1ebfn tr\u00fac s\u01b0 d\u1eef li\u1ec7u: Vi\u1ec7c l\u00e0m n\u00e0y y\u00eau c\u1ea7u b\u1eb1ng c\u1ea5p chuy\u00ean s\u00e2u (th\u1ea1c s\u0129 hay ti\u1ebfn s\u0129) trong khoa h\u1ecdc m\u00e1y t\u00ednh, k\u0129 ngh\u1ec7 ph\u1ea7n m\u1ec1m m\u00e0 chuy\u00ean m\u00f4n ho\u00e1 trong qu\u1ea3n l\u00ed d\u1eef li\u1ec7u hay tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o. Ki\u1ebfn tr\u00fac s\u01b0 d\u1eef li\u1ec7u l\u1eadp k\u1ebf ho\u1ea1ch, ki\u1ebfn tr\u00fac v\u00e0 t\u1ed5 ch\u1ee9c m\u1ecdi c\u00f4ng c\u1ee5 t\u00ecm, thu th\u1eadp v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u cho c\u00f4ng ti.<\/p>\n

3)\u00a0\u00a0\u00a0\u00a0Ng\u01b0\u1eddi ph\u00e2n t\u00edch d\u1eef li\u1ec7u: Vi\u1ec7c l\u00e0m n\u00e0y y\u00eau c\u1ea7u b\u1eb1ng c\u1eed nh\u00e2n trong khoa h\u1ecdc m\u00e1y t\u00ednh, k\u0129 ngh\u1ec7 ph\u1ea7n m\u1ec1m, hay qu\u1ea3n l\u00ed h\u1ec7 th\u00f4ng tin. Ng\u01b0\u1eddi ph\u00e2n t\u00edch d\u1eef li\u1ec7u d\u1ecbch c\u00e1c ph\u00e2n t\u00edch th\u00e0nh th\u00f4ng tin m\u00e0 ng\u01b0\u1eddi qu\u1ea3n l\u00ed c\u00f3 th\u1ec3 d\u00f9ng \u0111\u1ec3 ra quy\u1ebft \u0111\u1ecbnh. Ng\u01b0\u1eddi ph\u00e2n t\u00edch \u0111\u1eb7t ch\u00fang v\u00e0o c\u00e1c b\u00e1o c\u00e1o cho c\u1ea5p qu\u1ea3n l\u00ed v\u00e0 gi\u00fap h\u1ecd hi\u1ec3u xu h\u01b0\u1edbng hi\u1ec7n th\u1eddi.<\/p>\n

4)\u00a0\u00a0\u00a0\u00a0K\u0129 s\u01b0 d\u1eef li\u1ec7u: Vi\u1ec7c l\u00e0m n\u00e0y y\u00eau c\u1ea7u b\u1eb1ng c\u1eed nh\u00e2n trong khoa h\u1ecdc m\u00e1y t\u00ednh, k\u0129 ngh\u1ec7 ph\u1ea7n m\u1ec1m, hay qu\u1ea3n l\u00ed h\u1ec7 th\u00f4ng tin. K\u0129 s\u01b0 d\u1eef li\u1ec7u ph\u00e1t tri\u1ec3n v\u00e0 th\u1ef1c hi\u1ec7n c\u00e1c ch\u01b0\u01a1ng tr\u00ecnh ph\u1ea7n m\u1ec1m ph\u00e2n t\u00edch, thu th\u1eadp v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u cho c\u00f4ng ti.<\/p>\n

 <\/p>\n

—English version—<\/p>\n

 <\/p>\n

The Big Data Trend<\/p>\n

For many years, India dominated the Information Technology (IT) outsourcing market but thing could change too. The next big wave of IT outsourcing is no longer \u201cCode and Test\u201d or \u201cApplications Development\u201d but Big Data analysis where global companies are willing to spend several millions to billions of dollars each year to companies or countries that can provide skilled workers in this field. An Indian executive lamented: \u201cThe rule has changed, it is no longer lower cost but higher skills and it caught us by surprised. We will need to develop more people with this skill quickly.\u201d<\/p>\n

Big Data is about collecting a vast amount of information a company has internally, combining them with external sources such as internet then analyzing them to get valuable information such as trends and opportunities. Global companies need Big Data to identify new business market and using such analysis to effectively help managers to make decisions. For example, Big Data analysts use trend analytics to understand market direction, customers\u2019 needs to develop new products before others even know about it. It also analyzes industry\u2019s trends and future market to manage the entire supply chain, from raw materials to manufacturing, from distributing channels to retails, to cut operational costs and maximize profits.<\/p>\n

Big Data is also used in the financial market to predict trading trends. Currently the stock market is volatile due to the effect of the financial crisis so most traders are very cautious because the U.S economy is still recovering; the European Union is in a crisis; China market is slower than expected; the Middle East is under a chaotic situation etc. In this situation, few people would dare to make any bold move. But with the use of Big Data, some trading companies have been able to identify certain trends quickly and seize the opportunity. When most people are losing money on the stock market, these trading companies are winning big. If you look at the Wall Street Journal\u2019s job wanted, you may find all trading companies are hiring Data Scientists and Data analyst and the competition is fierce.<\/p>\n

Since this is a relatively new field, there are only few top universities provide trainings so there is a significant shortage of Big Data workers and the demand is growing fast. According to the industry report, the U.S alone will need 250,000 Data Scientist by 2015 and worldwide demand could push this number to millions. Big Data skills are a combination of mathematics, statistics, machine learning, and computer science. Data Scientists work on real-time data collected from multiple sources to do predictive analysis on the market trends which can help management set direction, make decision about the future market. Last month, the \u201cHarvard Business Review\u201d has termed Data Scientists to be the “Sexiest career of the 21st Century.” And Wall Street stock trading companies considered Big Data analysis to be the future of all financial business transactions.<\/p>\n

Currently, Big Data is emerging as the most lucrative market for IT outsourcing companies with market value estimated to be $1 billion dollars in 2015. Since it is a new area that has few competitions so the race to seize this opportunity and capture this market has begun among companies all over the world. A Wall Street analyst said: \u201cThe proliferation of social and other online network has provided so much data on the Internet. What we need is to capture these valuable data, analyze them for trends so we can make market decision quickly. We need Data Scientists to inject more exciting into the stock market.\u201d<\/p>\n

Many students are confused about the difference between Big Data and other well established fields such as database administration, data management, data mining and business intelligence. The key difference is the other fields are collecting and managing data from company\u2019s relational database to analyze and generate reports. The report is limited on the data collected and stored inside the company database and these data are well defined and structured.<\/p>\n

Big data scientists collect data from both internal AND external sources such as the internet etc. This is more difficult because data from external sources are mostly not well defined and structured. For example, the web is full of \u201cdata-driven apps.\u201d Almost any e-commerce application is a data-driven application. Social networks such as Facebook, Linkedln are full of social and personal data. There are all types of data behind each web front end, and middleware that connect other databases and data services such as credit card companies, banks etc. That is why the amount of data is very big. On the average, Data Scientists must analyze about 3.5 zettabytes a year (A zettabyte is a trillion gigabytes or a billion terabytes). AND these data are changing and growing every second or minute. That is why it needs different skills and algorithms to perform the analysis.<\/p>\n

Even it is a relatively new field, Big Data is already being used in the U.S. where such analysis are generating public opinion polls, forecast election results, predict stock market trends, analyze global financial transactions and develop strategies for governments and private companies. Today every company is looking for workers with these skills to work on their Big Data projects and they would grab any graduate with or without experience to train them on Big Data. An industry analyst said: “There is no question that companies will need this skill to gain a competitive advantage in this highly competitive market and who have the most qualified workers will win.\u201d<\/p>\n

Basically there are four job categories in the Big Data area:<\/p>\n

1)\u00a0\u00a0\u00a0\u00a0Data Scientist: This job usually requires advanced degrees (MS or PhD) in Computer Science, Software Engineering, Statistics, Artificial Intelligence, and Machine Learning. Data scientist design special programs and algorithms to collect and analyze data. He is responsible to set data strategy and implement all data products for the company. The Data scientist works with vast amount of data collected from both inside and outside the company to determine what these data means and how they impact the company.<\/p>\n

2)\u00a0\u00a0\u00a0\u00a0Data Architect: This job requires an advanced degree (MS or PhD) in Computer Science, Software Engineering that specialize in Data management or Artificial Intelligence. The Data Architect plans, architects and organize all data searching, collecting and analyzing tools for a company.<\/p>\n

3)\u00a0\u00a0\u00a0\u00a0Data Analyst: This job requires a Bachelor\u2019s degree in Computer Science, Software Engineer, or Information System Management. The data analyst translates analytics into information that managers can use to make decision. The analyst put them into reports for management and helps them understand the current trends.<\/p>\n

4)\u00a0\u00a0\u00a0\u00a0Data Engineer: This job requires a Bachelor\u2019s degree in Computer Science, Software Engineer, or Information System Management. The data engineer develops and implements analytic software programs that collect and analyze data for the company.<\/p>\n","protected":false},"excerpt":{"rendered":"

Trong nhi\u1ec1u n\u0103m, \u1ea4n \u0110\u1ed9 \u0111\u00e3 chi ph\u1ed1i th\u1ecb tr\u01b0\u1eddng l\u00e0m kho\u00e1n ngo\u00e0i c\u00f4ng ngh\u1ec7 th\u00f4ng tin (CNTT) nh\u01b0ng s\u1ef1 vi\u1ec7c c\u00f3 th\u1ec3 thay \u0111\u1ed5i … <\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,36,26],"tags":[],"class_list":["post-3359","post","type-post","status-publish","format-standard","hentry","category-quan-li-he-thong-tin","category-social-media-mobility-big-data-analytics-and-cloud-computing","category-xu-huong-cong-nghe"],"_links":{"self":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/3359","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3359"}],"version-history":[{"count":4,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/3359\/revisions"}],"predecessor-version":[{"id":3361,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/3359\/revisions\/3361"}],"wp:attachment":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3359"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3359"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3359"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}