{"id":4187,"date":"2014-04-06T09:12:57","date_gmt":"2014-04-06T02:12:57","guid":{"rendered":"http:\/\/science-technology.vn\/?p=4187"},"modified":"2014-04-06T09:12:57","modified_gmt":"2014-04-06T02:12:57","slug":"nhu-cau-ve-big-data","status":"publish","type":"post","link":"https:\/\/science-technology.vn\/?p=4187","title":{"rendered":"Nhu c\u1ea7u v\u1ec1 Big data"},"content":{"rendered":"

Trong s\u00e1u th\u00e1ng qua, nhi\u1ec1u c\u00f4ng ti t\u1edbi CMU \u0111\u1ec3 t\u00ecm ng\u01b0\u1eddi t\u1ed1t nghi\u1ec7p Big data v\u00ec thi\u1ebfu h\u1ee5t k\u0129 n\u0103ng n\u00e0y \u0111ang t\u1edbi l\u00fac gay c\u1ea5n. H\u1ecd t\u1ea5t c\u1ea3 \u0111\u1ec1u c\u1ea7n ai \u0111\u00f3 c\u00f3 k\u0129 n\u0103ng trong Hadoop, NoSQL, HBase, Pig, Hive v.v. \u0110\u1eb7c bi\u1ec7t nh\u1eefng ng\u01b0\u1eddi t\u1ed1t nghi\u1ec7p m\u00e0 c\u00f3 th\u1ec3 ph\u00e2n t\u00edch v\u00e0 \u0111i t\u1edbi th\u00f4ng tin c\u00f3 ngh\u0129a t\u1eeb kh\u1ed1i l\u01b0\u1ee3ng l\u1edbn d\u1eef li\u1ec7u r\u00f3t v\u00e0o trong c\u00f4ng ti h\u1ecd tr\u00ean c\u01a1 s\u1edf h\u00e0ng ng\u00e0y. M\u1ed9t ng\u01b0\u1eddi qu\u1ea3n l\u00ed thu\u00ea ng\u01b0\u1eddi b\u1ea3o t\u00f4i: \u201c\u0110\u00e2y l\u00e0 cu\u1ed9c \u0111ua th\u00e2u t\u00f3m c\u00e1c c\u00f4ng nh\u00e2n Big data nhi\u1ec1u nh\u1ea5t c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c v\u00e0 ai c\u00f3 nhi\u1ec1u nh\u1ea5t s\u1ebd th\u1eafng.\u201d<\/span><\/p>\n

Ng\u00e0nh c\u00f4ng nghi\u1ec7p n\u00e0y d\u1ef1 b\u00e1o r\u1eb1ng Big data s\u1ebd t\u1ea1o ra tr\u00ean 2 tri\u1ec7u vi\u1ec7c l\u00e0m m\u1edbi \u1edf ri\u00eang M\u0129, nh\u01b0ng ch\u1ec9 c\u00f3 th\u1ec3 ki\u1ebfm \u0111\u01b0\u1ee3c qu\u00e3ng 400,000 ng\u01b0\u1eddi t\u1ed1t nghi\u1ec7p l\u00e0 t\u1ed1i \u0111a. Nhu c\u1ea7u to\u00e0n c\u1ea7u \u0111\u01b0\u1ee3c \u01b0\u1edbc l\u01b0\u1ee3ng qu\u00e3ng 3 t\u1edbi 4 tri\u1ec7u c\u00f4ng nh\u00e2n tr\u01b0\u1edbc n\u0103m 2020 nh\u01b0ng cung c\u1ea5p c\u1ee7a to\u00e0n th\u1ebf gi\u1edbi ch\u1ec9 c\u00f3 th\u1ec3 t\u1ea1o ra \u0111\u01b0\u1ee3c kh\u00f4ng \u0111\u1ea7y m\u1ed9t ph\u1ea7n ba nhu c\u1ea7u. Do nhu c\u1ea7u b\u1ea5t th\u1ea7n n\u00e0y, c\u00e1c c\u00f4ng ti l\u00e0m kho\u00e1n ngo\u00e0i \u1edf \u1ea4n \u0110\u1ed9 v\u00e0 Trung Qu\u1ed1c \u0111ang v\u1ed9i v\u00e0ng thu\u00ea ng\u01b0\u1eddi t\u1ed1t nghi\u1ec7p Big data nh\u01b0ng kh\u00f4ng th\u1ec3 t\u00ecm \u0111\u01b0\u1ee3c c\u00f4ng nh\u00e2n. M\u1ed9t quan ch\u1ee9c ch\u00ednh ph\u1ee7 \u1ea4n \u0110\u1ed9 n\u00f3i v\u1edbi c\u00e1c b\u00e1o ch\u00ed: \u201cT\u1ea1i sao kh\u00f4ng c\u00f3 k\u1ebf ho\u1ea1ch \u0111\u1ec3 d\u1ea1y m\u00f4n n\u00e0y trong c\u00e1c \u0111\u1ea1i h\u1ecdc c\u1ee7a ch\u00fang ta? T\u1ea1i sao ch\u00fang ta v\u1eabn d\u1ea1y vi\u1ebft m\u00e3 v\u00e0 ki\u1ec3m th\u1eed n\u01a1i ph\u1ea7n l\u1edbn nh\u1eefng vi\u1ec7c l\u00e0m tr\u1ea3 l\u01b0\u01a1ng th\u1ea5p n\u00e0y \u0111ang chuy\u1ec3n sang ch\u00e2u Phi v\u00e0 \u0110\u00f4ng Nam \u00c1 v\u00e0 b\u1ecf qua m\u00f4n h\u1ecdc c\u00f3 nhu c\u1ea7u cao th\u1ebf? V\u1ea5n \u0111\u1ec1 l\u00e0 ch\u00fang ta s\u1ebd \u1edf \u0111\u00e2u trong n\u0103m 2020? V\u1edbi s\u00e1u n\u0103m c\u00f2n l\u1ea1i, ch\u00fang ta c\u00f3 th\u1ec3 t\u1ea1o ra \u0111\u1ee7 c\u00f4ng nh\u00e2n c\u00f3 k\u0129 n\u0103ng \u0111\u1ec3 \u0111\u00e1p \u1ee9ng cho nhu c\u1ea7u n\u00e0y kh\u00f4ng?\u201d M\u1ed9t t\u00ecnh hu\u1ed1ng t\u01b0\u01a1ng t\u1ef1 c\u0169ng \u0111ang x\u1ea3y ra \u1edf Trung Qu\u1ed1c n\u01a1i c\u00f3 h\u00e0ng tri\u1ec7u ng\u01b0\u1eddi t\u1ed1t nghi\u1ec7p b\u1ecb th\u1ea5t nghi\u1ec7p. Nhi\u1ec1u b\u00e1o ch\u00ed \u0111ang ph\u00ea ph\u00e1n h\u1ec7 th\u1ed1ng gi\u00e1o d\u1ee5c: \u201cNh\u1eefng ng\u01b0\u1eddi l\u00e3nh \u0111\u1ea1o gi\u00e1o d\u1ee5c \u0111\u00e3 l\u00e0m h\u1ecfng thanh ni\u00ean c\u1ee7a ch\u00fang ta. Ch\u00fang ta c\u1ea7n l\u00e0m nhi\u1ec1u h\u01a1n \u0111\u1ec3 gi\u00f3ng th\u1eb3ng vi\u1ec7c cung c\u1ea5p c\u1ee7a gi\u00e1o d\u1ee5c v\u1edbi nhu c\u1ea7u cao c\u1ee7a th\u1ecb tr\u01b0\u1eddng.\u201d Trong c\u00e1c ph\u00f2ng ch\u00e1t, nh\u1eefng ng\u01b0\u1eddi t\u1ed1t nghi\u1ec7p b\u1ecb th\u1ea5t nghi\u1ec7p ch\u00e1n n\u1ea3n c\u0169ng l\u00ean ti\u1ebfng v\u1ec1 gi\u1eadn d\u1eef c\u1ee7a h\u1ecd: \u201cCh\u00fang t\u00f4i v\u1eabn \u0111ang b\u1ecb d\u1ea1y cho nh\u1eefng th\u1ee9 m\u00e0 kh\u00f4ng ai mu\u1ed1n trong khi c\u00f3 c\u00e1c m\u00f4n c\u00f3 nhu c\u1ea7u cao nh\u01b0ng kh\u00f4ng ai d\u1ea1y. \u0110\u00e2y l\u00e0 l\u00fac thay th\u1ebf h\u1ec7 th\u1ed1ng gi\u00e1o d\u1ee5c l\u1ed7i th\u1eddi c\u1ee7a ch\u00fang ta.\u201d S\u1ef1 ki\u1ec7n l\u00e0 c\u00f4ng ngh\u1ec7 thay \u0111\u1ed5i nhanh ch\u00f3ng th\u1ebf v\u00e0 nhu c\u1ea7u \u0111ang d\u1ecbch chuy\u1ec3n nhanh ch\u00f3ng, cho d\u00f9 m\u1ecdi \u0111\u1ea1i h\u1ecdc c\u00f3 th\u1ec3 thay \u0111\u1ed5i \u0111\u00e0o t\u1ea1o c\u1ee7a h\u1ecd, v\u1eabn s\u1ebd kh\u00f4ng \u0111\u1ee7 nhanh.<\/p>\n

V\u1ea5n \u0111\u1ec1 l\u00e0 l\u00e0m sao sinh vi\u00ean t\u1ef1 chu\u1ea9n b\u1ecb cho h\u1ecd v\u1ec1 ngh\u1ec1 nghi\u1ec7p trong Big data? Th\u1ee9 nh\u1ea5t, Big data y\u00eau c\u1ea7u b\u1eb1ng c\u1ea5p chuy\u00ean s\u00e2u cho n\u00ean sinh vi\u00ean c\u1ea7n ti\u1ebfp t\u1ee5c h\u1ecdc b\u1eb1ng th\u1ea1c s\u0129 trong Khoa h\u1ecdc d\u1eef li\u1ec7u, Qu\u1ea3n l\u00ed h\u1ec7 th\u00f4ng tin, hay K\u0129 ngh\u1ec7 ph\u1ea7n m\u1ec1m. Th\u1ee9 hai, Big data l\u00e0 l\u0129nh v\u1ef1c l\u1edbn y\u00eau c\u1ea7u nh\u1eefng \u0111\u00e0o t\u1ea1o kh\u00e1c nhau tu\u1ef3 theo vi\u1ec7c l\u00e0m. V\u1ec1 c\u0103n b\u1ea3n c\u00f3 ba ki\u1ec3u v\u1ecb tr\u00ed: nh\u00e0 Khoa h\u1ecdc d\u1eef li\u1ec7u, ng\u01b0\u1eddi Ki\u1ebfn tr\u00fac\/ph\u00e2n t\u00edch d\u1eef li\u1ec7u; v\u00e0 K\u0129 s\u01b0 d\u1eef li\u1ec7u. \u0110\u1ec3 chu\u1ea9n b\u1ecb cho nh\u1eefng v\u1ecb tr\u00ed n\u00e0y, sinh vi\u00ean c\u1ea7n x\u00e2y d\u1ef1ng m\u1ed9t n\u1ec1n t\u1ea3ng t\u1ed1t. H\u1ecd c\u1ea7n h\u1ecdc c\u00e1c l\u1edbp l\u1eadp tr\u00ecnh trong Java, Mathlab, Python v\u00e0 R v\u00ec \u0111\u00e2y l\u00e0 nh\u1eefng ng\u00f4n ng\u1eef ph\u1ed5 bi\u1ebfn d\u00f9ng trong Big data; h\u1ecd c\u1ea7n h\u1ecdc c\u00e1c m\u00f4n trong c\u1ea5u tr\u00fac d\u1eef li\u1ec7u, c\u01a1 s\u1edf d\u1eef li\u1ec7u, khai ph\u00e1 d\u1eef li\u1ec7u v\u00e0 trinh s\u00e1t doanh nghi\u1ec7p \u0111\u1ec3 hi\u1ec3u c\u00e1ch d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c d\u00f9ng; h\u1ecd c\u0169ng c\u1ea7n h\u1ecdc c\u00e1c m\u00f4n trong th\u1ed1ng k\u00ea v\u00e0 x\u00e1c su\u1ea5t v\u00ec ph\u00e2n t\u00edch Big data ph\u1ea7n l\u1edbn l\u00e0 v\u1ec1 to\u00e1n h\u1ecdc v\u00e0 th\u1ed1ng k\u00ea. H\u1ecd n\u00ean \u0111i ra ngo\u00e0i c\u00e1c m\u00f4n to\u00e1n h\u1ecdc ch\u00ednh qui c\u01a1 b\u1ea3n v\u00e0o c\u00e1c m\u00f4n chuy\u00ean s\u00e2u trong khu v\u1ef1c h\u1ed3i qui \u0111a bi\u1ebfn v\u00e0 ph\u01b0\u01a1ng tr\u00ecnh vi ph\u00e2n. V\u00ec nh\u1eefng \u0111\u00e0o t\u1ea1o nghi\u00eam ng\u1eb7t n\u00e0y chu\u1ea9n b\u1ecb cho ngh\u1ec1 nghi\u1ec7p trong Big data, \u00edt sinh vi\u00ean s\u1ebd \u0111i v\u00e0o trong n\u00f3 m\u1eb7c cho nhu c\u1ea7u cao; c\u00f3 th\u1ec3 l\u00e0 thi\u1ebfu h\u1ee5t n\u00e0y s\u1ebd k\u00e9o d\u00e0i trong m\u1ed9t th\u1eddi gian l\u00e2u.<\/p>\n

M\u1eb7c d\u1ea7u Big data \u0111\u00e3 \u0111\u01b0\u1ee3c d\u00f9ng trong c\u00f4ng nghi\u1ec7p t\u1eeb nhi\u1ec1u n\u0103m, g\u1ea7n \u0111\u00e2u kh\u1ed1i l\u01b0\u1ee3ng d\u1eef li\u1ec7u \u0111ang t\u0103ng l\u00ean nhanh ch\u00f3ng th\u1ebf v\u00e0 c\u00f3 nh\u1eefng c\u00f4ng c\u1ee5 m\u1edbi \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf \u0111\u1ec3 tr\u00edch ra gi\u00e1 tr\u1ecb t\u1eeb \u0111a d\u1ea1ng r\u1ed9ng c\u00e1c d\u1eef li\u1ec7u n\u00e0y th\u1ebf r\u1ed3i \u0111\u1ed9t nhi\u00ean n\u00f3 b\u00f9ng n\u1ed5. Big data l\u00e0 c\u00e1ch th\u1ee9c m\u1edbi \u0111\u1ec3 tr\u00edch r\u00fat v\u00e0 t\u1ed5 ch\u1ee9c th\u00f4ng tin \u0111\u1ec3 d\u1ef1 \u0111o\u00e1n m\u1ecdi s\u1ef1 \u0111ang x\u1ea3y ra theo th\u1eddi gian th\u1ef1c. N\u00f3 c\u00e1ch m\u1edbi \u0111\u1ec3 l\u00e0m kinh doanh trong th\u1ebf gi\u1edbi \u0111\u01b0\u1ee3c k\u1ebft n\u1ed1i n\u00e0y n\u01a1i m\u1ecdi s\u1ef1 x\u1ea3y ra nhanh ch\u00f3ng. Big data s\u1ebd bu\u1ed9c m\u1ecdi ng\u01b0\u1eddi thay \u0111\u1ed5i nhanh ch\u00f3ng v\u00e0 n\u00f3 s\u1ebd t\u00e1c \u0111\u1ed9ng t\u1edbi m\u1ecdi ng\u00e0nh c\u00f4ng nghi\u1ec7p. V\u1edbi Big data, c\u00f4ng ti c\u00f3 th\u1ec3 d\u1ef1 b\u00e1o s\u1ea3n ph\u1ea9m n\u00e0o c\u00f3 nhu c\u1ea7u cao \u0111\u1ec3 thay \u0111\u1ed5i chi\u1ebfn l\u01b0\u1ee3c ti\u1ebfp th\u1ecb c\u1ee7a h\u1ecd, l\u1ef1c l\u01b0\u1ee3ng b\u00e1n h\u00e0ng c\u1ee7a h\u1ecd, v\u00e0 c\u00e1c qui tr\u00ecnh ch\u1ebf t\u1ea1o \u0111\u1ec3 t\u1ea1o ra ch\u00fang m\u1ed9t c\u00e1ch nhanh ch\u00f3ng. V\u00ec doanh nghi\u1ec7p c\u1ee7a h\u1ecd thay \u0111\u1ed5i, \u0111\u1ed1i th\u1ee7 c\u1ea1nh tranh s\u1ebd kh\u00f4ng c\u00f3 kh\u1ea3 n\u0103ng \u0111\u00e1p \u1ee9ng \u0111\u1ee7 nhanh \u0111\u1ec3 c\u1ea1nh tranh. Ch\u1eb3ng h\u1ea1n, b\u1eb1ng vi\u1ec7c d\u00f9ng ph\u00e2n t\u00edch Big data, Samsung \u0111\u00e3 c\u00f3 kh\u1ea3 n\u0103ng d\u1ef1 b\u00e1o t\u00ednh n\u0103ng n\u00e0o kh\u00e1ch h\u00e0ng mu\u1ed1n c\u00f3 trong \u0111i\u1ec7n tho\u1ea1i di \u0111\u1ed9ng \u0111\u1ec3 ph\u00e1t tri\u1ec3n \u0111i\u1ec7n tho\u1ea1i c\u1ee7a h\u1ecd (lo\u1ea1t Galaxy) khi Motorola, Sony, Nokia v\u1eabn c\u00f2n ph\u1ee5 thu\u1ed9c v\u00e0o \u00fd ki\u1ebfn c\u1ee7a ng\u01b0\u1eddi qu\u1ea3n l\u00ed b\u00e1n h\u00e0ng c\u1ee7a h\u1ecd. Ng\u00e0y nay Samsung \u0111\u00e3 th\u00e2u t\u00f3m ph\u1ea7n l\u1edbn th\u1ecb tr\u01b0\u1eddng di \u0111\u1ed9ng, th\u1eadm ch\u00ed c\u00f2n t\u1ed1t h\u01a1n Apple trong khi Nokia, Motorola, v\u00e0 Sony m\u1ea5t h\u1ea7u h\u1ebft th\u1ecb tr\u01b0\u1eddng v\u00e0 c\u00f3 th\u1ec3 ph\u1ea3i ra kh\u1ecfi kinh doanh.<\/p>\n

V\u1edbi Big data, c\u00e1c quy\u1ebft \u0111\u1ecbnh s\u1ebd \u0111\u01b0\u1ee3c d\u1ef1a tr\u00ean th\u1ed1ng k\u00ea v\u00e0 x\u00e1c su\u1ea5t h\u01a1n l\u00e0 \u00fd ki\u1ebfn c\u00e1 nh\u00e2n. Ch\u00fang ta h\u00e3y t\u01b0\u1edfng t\u01b0\u1ee3ng m\u1ed9t cu\u1ed9c h\u1ecdp ng\u01b0\u1eddi \u0111i\u1ec1u h\u00e0nh \u0111\u1ec3 quy\u1ebft \u0111\u1ecbnh t\u00ednh n\u0103ng cho s\u1ea3n ph\u1ea9m m\u1edbi. M\u1ed9t ng\u01b0\u1eddi qu\u1ea3n l\u00ed n\u00f3i: \u201cT\u00f4i ngh\u0129 s\u1ea3n ph\u1ea9m ti\u1ebfp c\u1ee7a ch\u00fang ta n\u00ean c\u00f3 c\u00e1c ch\u1ee9c n\u0103ng XYZ v\u00ec t\u00f4i ngh\u0129 n\u00f3 l\u00e0 t\u1ed1t.\u201d Ng\u01b0\u1eddi qu\u1ea3n l\u00ed kh\u00e1c n\u00f3i: \u201cTheo ph\u00e2n t\u00edch Big data c\u1ee7a ch\u00fang t\u00f4i \u0111\u01b0\u1ee3c thu th\u1eadp t\u1eeb m\u1ed9t tr\u0103m tri\u1ec7u d\u1eef li\u1ec7u t\u1eeb m\u1ea1ng x\u00e3 h\u1ed9i, internet, b\u00e1o ch\u00ed, ph\u00f2ng chat, c\u00e1c b\u00e0i b\u00e1o khoa h\u1ecdc, t\u1ea1p ch\u00ed, t\u00f4i k\u1ebft lu\u1eadn r\u1eb1ng n\u1ebfu ch\u00fang ta c\u00f3 c\u00e1c ch\u1ee9c n\u0103ng ABC ch\u00fang ta s\u1ebd c\u00f3 85% th\u1ecb ph\u1ea7n v\u00e0 c\u00f3 th\u1ec3 t\u0103ng l\u1ee3i nhu\u1eadn l\u00ean 65%; n\u1ebfu ch\u00fang ta c\u00f3 c\u00e1c ch\u1ee9c n\u0103ng XYZ, ch\u00fang ta s\u1ebd ch\u1ec9 c\u00f3 42% th\u1ecb ph\u1ea7n v\u00e0 t\u0103ng l\u1ee3i nhu\u1eadn l\u00ean 32%; v\u00e0 n\u1ebfu ch\u00fang ta c\u00f3 c\u00e1c ch\u1ee9c n\u0103ng JLK th\u00ec ch\u00fang ta s\u1ebd m\u1ea5t 35% th\u1ecb tr\u01b0\u1eddng v\u00e0 l\u1ed7 18 tri\u1ec7u \u0111\u00f4 la. Ph\u00e2n t\u00edch h\u01a1n k\u1ebft lu\u1eadn r\u1eb1ng d\u1ef1 b\u00e1o n\u00e0y \u0111\u1ea1t ch\u00ednh x\u00e1c 83% v\u00e0 x\u00e1c su\u1ea5t h\u01a1n 90% r\u1eb1ng ch\u00fang ta c\u00f3 th\u1ec3 th\u00e2u t\u00f3m \u0111\u01b0\u1ee3c th\u1ecb tr\u01b0\u1eddng trong v\u00f2ng 6 th\u00e1ng n\u1ebfu ch\u00fang ta c\u00f3 c\u00e1c ch\u1ee9c n\u0103ng ABC v\u00e0 ch\u00fang ta c\u00f3 th\u1ec3 \u0111\u1ea9y ba t\u1edbi n\u0103m \u0111\u1ed1i th\u1ee7 c\u1ea1nh tranh ra kh\u1ecfi th\u1ecb tr\u01b0\u1eddng \u0111\u1ebfn cu\u1ed1i n\u0103m.\u201d B\u1ea1n ngh\u0129 ng\u01b0\u1eddi ch\u1ee7 c\u00f4ng ti s\u1ebd h\u00e0nh \u0111\u1ed9ng theo c\u00e1i g\u00ec? \u00d4ng \u1ea5y s\u1ebd ra quy\u1ebft \u0111\u1ecbnh d\u1ef1a tr\u00ean \u00fd ki\u1ebfn c\u1ee7a ng\u01b0\u1eddi qu\u1ea3n l\u00ed b\u00e1n h\u00e0ng hay c\u00e1c d\u1ef1 b\u00e1o d\u1ef1a tr\u00ean ph\u00e2n t\u00edch k\u0129 l\u01b0\u1ee1ng v\u1ec1 th\u1ecb tr\u01b0\u1eddng? \u0110\u00f3 l\u00e0 s\u1ee9c m\u1ea1nh c\u1ee7a Big data.<\/p>\n

V\u00ed d\u1ee5 kh\u00e1c v\u1ec1 Big data l\u00e0 trong c\u1eeda h\u00e0ng b\u00e1n l\u1ebb. T\u01b0\u1edfng t\u01b0\u1ee3ng m\u1ed9t kh\u00e1ch h\u00e0ng mu\u1ed1n mua tivi m\u00e0n h\u00ecnh ph\u1eb3ng nh\u01b0ng kh\u00f4ng ch\u1eafc mua \u1edf \u0111\u00e2u hay c\u1eeda h\u00e0ng n\u00e0o c\u00f3 gi\u00e1 t\u1ed1t nh\u1ea5t. Ng\u01b0\u1eddi \u0111\u00f3 d\u00f9ng app di \u0111\u1ed9ng \u0111\u1ec3 so s\u00e1nh gi\u00e1 gi\u1eefa v\u00e0i c\u1eeda h\u00e0ng. App n\u00e0y qu\u00e9t qua m\u1ecdi c\u1eeda h\u00e0ng trong th\u00e0nh ph\u1ed1 v\u00e0 hi\u1ec3n th\u1ecb danh s\u00e1ch c\u00e1c gi\u00e1 tivi m\u00e0n h\u00ecnh ph\u1eb3ng \u0111\u1ec3 cho ng\u01b0\u1eddi \u0111\u00f3 c\u00f3 th\u1ec3 ch\u1ecdn c\u1eeda h\u00e0ng gi\u00e1 th\u1ea5p nh\u1ea5t. B\u1eb1ng vi\u1ec7c d\u00f9ng Big data thu th\u1eadp th\u00f4ng tin tr\u00ean Internet, ng\u01b0\u1eddi ch\u1ee7 c\u1eeda h\u00e0ng l\u1eadp t\u1ee9c \u0111\u01b0\u1ee3c th\u00f4ng b\u00e1o v\u1ec1 kh\u00e1ch h\u00e0ng ti\u1ec1m n\u0103ng \u0111ang ki\u1ec3m gi\u00e1. V\u1edbi ph\u00e2n t\u00edch Big data, ng\u01b0\u1eddi \u0111\u00f3 c\u0169ng nh\u1eadn \u0111\u01b0\u1ee3c th\u00f4ng tin v\u1ec1 kh\u00e1ch h\u00e0ng n\u00e0y nh\u01b0 t\u00edn d\u1ee5ng t\u00e0i ch\u00ednh, t\u00e0i kho\u1ea3n ng\u00e2n h\u00e0ng v\u00e0 c\u00e1c th\u00f4ng tin li\u00ean quan kh\u00e1c v.v. Ng\u01b0\u1eddi ch\u1ee7 c\u1eeda h\u00e0ng s\u1ebd ph\u1ea3i ra quy\u1ebft \u0111\u1ecbnh nhanh ch\u00f3ng. N\u1ebfu gi\u00e1 c\u1ee7a \u00f4ng ta cao h\u01a1n ng\u01b0\u1eddi kh\u00e1c, \u00f4ng ta ph\u1ea3i gi\u1ea3m gi\u00e1 v\u00e0 g\u1eedi m\u1ed9t tin nh\u1eafn t\u1edbi kh\u00e1ch h\u00e0ng th\u00f4ng b\u00e1o cho anh ta r\u1eb1ng anh ta c\u00f3 “gi\u1ea3m gi\u00e1 \u0111\u1eb7c bi\u1ec7t” cho ph\u00e9p anh ta mua tivi v\u1edbi gi\u00e1 th\u1ea5p h\u01a1n ng\u01b0\u1eddi kh\u00e1c nh\u01b0ng anh ta ph\u1ea3i \u0111\u00e1p \u1ee9ng nhanh ch\u00f3ng v\u00ec vi\u1ec7c gi\u1ea3m gi\u00e1 c\u00f3 gi\u1edbi h\u1ea1n th\u1eddi gian. N\u1ebfu kh\u00e1ch h\u00e0ng v\u1eabn kh\u00f4ng ch\u1eafc, v\u00e0i ph\u00fat sau anh ta nh\u1eadn \u0111\u01b0\u1ee3c tin nh\u1eafn kh\u00e1c th\u00fac gi\u1ee5c anh ta mua v\u1edbi l\u1eddi h\u1ee9a l\u00e0 c\u1eeda h\u00e0ng s\u1ebd chuy\u1ec3n giao ti vi t\u1edbi t\u1eadn nh\u00e0 v\u00e0 l\u1eafp \u0111\u1eb7t mi\u1ec5n ph\u00ed ph\u1ee5. B\u1ea1n ngh\u0129 kh\u00e1ch h\u00e0ng n\u00e0y s\u1ebd l\u00e0m g\u00ec? C\u00f3 \u0111\u01b0\u1ee3c tivi anh ta mu\u1ed1n v\u1edbi gi\u00e1 th\u1ea5p nh\u1ea5t v\u00e0 c\u00f3 m\u1ecdi th\u1ee9 \u0111\u01b0\u1ee3c th\u1ef1c hi\u1ec7n m\u00e0 kh\u00f4ng ph\u1ea3i r\u1eddi kh\u1ecfi nh\u00e0? C\u00e1c c\u1eeda h\u00e0ng kh\u00e1c kh\u00f4ng d\u00f9ng Big data s\u1ebd kh\u00f4ng bao gi\u1edd bi\u1ebft r\u1eb1ng h\u1ecd v\u1eeba m\u1ea5t m\u1ed9t th\u01b0\u01a1ng v\u1ee5 ti\u1ec1m n\u0103ng. \u0110\u00f3 l\u00e0 s\u1ee9c m\u1ea1nh c\u1ee7a Big data.<\/p>\n

Trong \u201cth\u1ecb tr\u01b0\u1eddng to\u00e0n c\u1ea7u \u0111\u01b0\u1ee3c d\u1eabn l\u00e1i b\u1edfi c\u00f4ng ngh\u1ec7\u201d n\u00e0y, m\u1ecdi ng\u01b0\u1eddi qu\u1ea3n l\u00ed \u0111\u1ec1u c\u1ea7n hi\u1ec3u s\u1ee9c m\u1ea1nh c\u1ee7a C\u00f4ng ngh\u1ec7 th\u00f4ng tin (CNTT). Vi\u1ec7c d\u00f9ng Big data nh\u01b0 m\u1ed9t c\u00f4ng c\u1ee5 c\u1ea1nh tranh n\u00ean \u0111\u01b0\u1ee3c d\u1ea1y trong m\u1ecdi ch\u01b0\u01a1ng tr\u00ecnh qu\u1ea3n l\u00ed. C\u00e1ch ti\u1ebfp c\u1eadn li\u00ean ng\u00e0nh n\u00e0y c\u1ee7a “Khoa h\u1ecdc d\u1eef li\u1ec7u” n\u01a1i to\u00e1n h\u1ecdc, th\u1ed1ng k\u00ea v\u00e0 c\u00f4ng ngh\u1ec7 th\u00f4ng tin \u0111\u01b0\u1ee3c t\u1ed5 h\u1ee3p l\u1ea1i s\u1ebd l\u00e0 y\u1ebfu t\u1ed1 ch\u00ednh trong kinh doanh to\u00e0n c\u1ea7u n\u01a1i c\u00e1c c\u00f4ng ti d\u00f9ng c\u00f4ng ngh\u1ec7 s\u1ebd c\u00f3 \u01b0u th\u1ebf. \u0110\u1ec3 l\u00e0m \u0111i\u1ec1u \u0111\u00f3, \u0111i\u1ec1u tuy\u1ec7t \u0111\u1ed1i m\u1ea5u ch\u1ed1t l\u00e0 c\u00f4ng ti ph\u1ea3i c\u00f3 chi\u1ebfn l\u01b0\u1ee3c c\u00f4ng ngh\u1ec7 th\u00f4ng tin t\u1ea1i ch\u1ed7. Kh\u00f4ng c\u00f3 l\u00ed do trong \u0111\u1ea7u t\u01b0 v\u00e0o Big data nh\u01b0 chi\u1ebfn l\u01b0\u1ee3c m\u00e0 kh\u00f4ng c\u00f3 ng\u01b0\u1eddi qu\u1ea3n l\u00ed h\u1ec7 th\u00f4ng tin c\u00f3 k\u0129 n\u0103ng, ng\u01b0\u1eddi c\u00f3 th\u1ec3 gi\u00f3ng th\u1eb3ng chi\u1ebfn l\u01b0\u1ee3c CNTT v\u1edbi chi\u1ebfn l\u01b0\u1ee3c doanh nghi\u1ec7p v\u00e0 bi\u1ebft c\u00e1ch th\u1ef1c hi\u1ec7n n\u00f3 m\u1ed9t c\u00e1ch th\u00e0nh c\u00f4ng. Khi c\u00e1c c\u00f4ng ti nh\u00ecn v\u00e0o Big data \u0111\u1ec3 gi\u00fap cho h\u1ecd ra quy\u1ebft \u0111\u1ecbnh, ng\u01b0\u1eddi \u0111i\u1ec1u h\u00e0nh ph\u1ea3i ch\u1eafc r\u1eb1ng h\u1ecd c\u00f3 chi\u1ebfn l\u01b0\u1ee3c CNTT t\u1ea1i ch\u1ed7, c\u00f4ng ti ph\u1ea3i b\u1eaft \u0111\u1ea7u b\u1eb1ng vi\u1ec7c c\u00f3 ng\u01b0\u1eddi qu\u1ea3n l\u00ed h\u1ec7 th\u00f4ng tin \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh c\u00f4ng ti c\u00f3 th\u1ec3 l\u00e0m g\u00ec v\u1edbi Big data: C\u00e1c v\u1ecb tr\u00ed nh\u01b0 Nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u th\u01b0\u1eddng y\u00eau c\u1ea7u c\u00e1c k\u0129 n\u0103ng m\u00e1y t\u00ednh v\u00e0 th\u1ed1ng k\u00ea; Ng\u01b0\u1eddi ph\u00e2n t\u00edch d\u1eef li\u1ec7u s\u1ebd y\u00eau c\u1ea7u k\u0129 n\u0103ng qu\u1ea3n l\u00ed v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u, v\u00e0 K\u0129 s\u01b0 d\u1eef li\u1ec7u s\u1ebd y\u00eau c\u1ea7u k\u0129 n\u0103ng l\u1eadp tr\u00ecnh v\u00e0 di\u1ec5n gi\u1ea3i d\u1eef li\u1ec7u. Tuy nhi\u00ean c\u00e1c k\u0129 n\u0103ng k\u0129 thu\u1eadt l\u00e0 kh\u00f4ng \u0111\u1ee7, c\u00e1c c\u00f4ng ti mu\u1ed1n nh\u1eefng ng\u01b0\u1eddi c\u00f3 tri th\u1ee9c v\u1ec1 ph\u01b0\u01a1ng ph\u00e1p v\u00e0 \u1ee9ng d\u1ee5ng c\u1ee7a ph\u00e2n t\u00edch, nh\u01b0ng c\u0169ng hi\u1ec3u v\u1ea5n \u0111\u1ec1 doanh nghi\u1ec7p v\u00e0 c\u00f3 kh\u1ea3 n\u0103ng l\u00e0m vi\u1ec7c trong t\u1ed5 v\u00e0 c\u00f3 th\u1ec3 trao \u0111\u1ed5i hi\u1ec7u qu\u1ea3 t\u1ed1t v\u1edbi ng\u01b0\u1eddi \u0111i\u1ec1u h\u00e0nh.<\/p>\n

M\u1ecdi tu\u1ea7n t\u00f4i \u0111\u1ec1u nh\u1eadn \u0111\u01b0\u1ee3c \u0111i\u1ec7n tho\u1ea1i t\u1eeb c\u00e1c c\u00f4ng ti t\u00ecm thu\u00ea ng\u01b0\u1eddi t\u1ed1t nghi\u1ec7p Big data. T\u1ea5t nhi\u00ean ch\u00fang t\u00f4i c\u00f3 danh ti\u1ebfng t\u1ed1t v\u1ec1 ph\u00e1t tri\u1ec3n nh\u00e0 chuy\u00ean nghi\u1ec7p Big data c\u00f3 ph\u1ea9m ch\u1ea5t m\u00e0 l\u00e0m vi\u1ec7c t\u1ed1t trong c\u00f4ng nghi\u1ec7p. T\u00f4i tin d\u1eef li\u1ec7u \u0111ang tr\u1edf th\u00e0nh t\u00e0i nguy\u00ean c\u00f3 gi\u00e1 tr\u1ecb nh\u1ea5t d\u1eabn l\u00e1i t\u0103ng tr\u01b0\u1edfng kinh t\u1ebf to\u00e0n c\u1ea7u ng\u00e0y nay. Trong th\u1eddi \u0111\u1ea1i tri th\u1ee9c n\u00e0y, d\u1eef li\u1ec7u l\u00e0 y\u1ebfu t\u1ed1 ch\u00ednh cho s\u1ef1 ki\u1ec7n v\u00e0 ch\u00e2n l\u00ed.<\/p>\n

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—English version—<\/p>\n

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The demand for Big data<\/p>\n

In the past six months, more companies came to CMU looking for Big data graduates as the skilled shortage is getting critical. They all need someone with skills in Hadoop, NoSQL, HBase, Pig, Hive etc. Especially graduates that can analyze and come up with meaningful information from the massive of data pouring into their company on a daily basis. A hiring manager told me: \u201cThis is a race to capture Big data workers as many as possible and who has the most will win.\u201d<\/p>\n

The industry predicts that Big data will create over 2 million new jobs in the U.S. alone, but can only get about 400,000 graduates at the maximum. The global needs are estimated to be around 3 to 4 million workers by 2020 but the entire world\u2019s supply can only produce less than a third of the demand. Due to this sudden needs, outsourcing companies in India and China are hurrying to hire Big data graduates but could not find workers. An Indian government officer told newspapers: \u201cWhy there is no plan to teach this subject in our universities? Why are we still teaching coding and testing where most of these low paying jobs are moving to Africa and South East Asia and ignore such a high demand subject? The question is where will we be in 2020? With only six year left, can we produce enough skilled workers to meet this demand?\u201d A similar situation is also happening in China where there are millions of unemployed graduates. Several\u00a0 newspapers are criticizing the education systems: \u201cThe educational leaders have failed our young people. We need to do more to align educational offerings with the high demand of the marketplace.\u201d Among chat rooms, frustrated unemployed graduates also voiced their anger: \u201cWe are still being taught about things what nobody want when there are high demand subjects but nobody teach. It is time to replace our obsolete education system.\u201d The fact is technology change so fast and demands are shifting quickly, even if all universities can change their trainings, it would not be fast enough.<\/p>\n

The question is how do students prepare themselves for a career in Big data? First, Big data requires advanced degree so students need to continue on to a Master\u2019s degree in Data Science, Information System Management, or Software Engineering. Second, Big data is a large field that requires different trainings depends on the jobs. Basically there are three types of positions: The Data Scientist; The Data Architect\/Analyst; and the Data Engineer. In order to prepare for these positions, students need to build a good foundation. They need to take programming classes in Java, Mathlab, Python and R as these are the popular languages using in Big data; they need to take courses in data structures, database, data mining and business intelligence to understand how data are being used; they also need to take courses in statistics and probability since Big data analytics is mostly about mathematics and statistics. They should go beyond basic regular math courses into advanced courses in area of multivariate regression and differential equations. Because of these rigorous trainings to prepare for a career in Big data, few students would go into it despite the high demand; it is possible that this shortage will last for a long time.<\/p>\n

Although Big data has been using in the industry for years. Recently the volume of data is increasing so fast and there are new tools designed to extract value from these wide variety of data then suddenly it explodes. Big data is a new way to extract and organize information to predict things that is happening in real time. It is a new way to do business in this connected world where things happen fast. Big data will force people to change quickly and it will impact every industry. With Big data, company can predict which products are in high demand to change their marketing strategy, their sales force, and manufacturing processes to produce them quickly. As their business change, competitors will not be able to respond fast enough to compete. For example, by using Big data analytics, Samsung was able to predict what features customers want in mobile phones to develop their phones (The Galaxy series) when Motorola, Sony, Nokia are still depending on the opinions of their sale managers. Today Samsung has captured a large part of the mobile market, even better than Apple when Nokia, Motorola, and Sony lost most of the market and could be out of business.<\/p>\n

With Big data, decisions will be based more on statistics and probability rather than personal opinions Let\u2019s us imagine an executive meeting to decide the features of new product. One manager says: \u201cI think our next product should have XYZ functions because I think it is good.\u201d Another manager says: \u201cAccording to our Big data analytics collected from one hundred million data from social network, internet, newspapers, chat rooms, scientific articles, magazines, I conclude that if we have ABC functions we will have 85% of the market share and could increase profit by 65%; if we have XYZ functions, we will only have 42% of the market share and increase profit by 32%; and if we have JLK functions then we will lose 35% of the market and lose 18 million dollars. Further analysis concludes that this prediction has 83% accuracy and more than 90% probability that we could capture the market within 6 months if we have ABC functions and we could push three of the five competitors out of the market by year end.\u201d What do you think the company owner would act? Will he be making decision based on a sale manager\u2019s opinion or a predictions based on thorough analysis of the market? That is the power of Big data.<\/p>\n

Another example of Big data is in retail stores. Imagine a customer wants to buy a flat screen TV but not sure where to buy or who has the best price. He uses the mobile app to compare price among several stores. The app scans all the stores within the city and displays a list of the flat screen TV prices so he could choose the lowest price store. By using Big data that collect information in the Internet, a store owner is immediately being informed about a potential customer who is checking on price. With Big data analytics, he also receives information about this customer such as financial credit, bank account and other relevant information etc. The store owner will have to make decision quickly. If his price is higher than others, he should reduce the price and sending a text message to the customer informing him that he has a \u201cspecial discount\u201d allows him to buy the TV at lower price than others but he must respond immediately since the discount has a time limit. If the customer is still not sure, few minutes later he will receive another text message urging him to buy with a promise that the store will deliver the TV to his home and installs it at no extra cost. What do you think the customer would do? Get the TV that he wants at the lowest price and have everything done without have to leave home? Other stores that do not use Big data will never know that they just lost a potential sale. That is the power of Big data.<\/p>\n

In this \u201cTechnology-driving global market\u201d, every manager needs to understand the power of Information Technology (IT). The use of Big data as a competitive tool should be taught in all management programs. This new interdisciplinary approach of “Data science” where math, statistics and information technology are combined will be a major factor in global business where companies that use technology will have the advantages. To do that it is absolutely critical that company to have an information technology strategy in place. There is no reason in investing in Big data as a strategy without skilled information systems managers who can align the IT strategy with the business strategy and know how to implement it successfully. As companies look to Big data to help them making decisions, executive must make sure that they have an IT strategy in place, the company must start by having information systems managers to define what the company could do with Big data: Positions such as Data Scientist often require computer and statistical skills; Data Analysts will require data management and analytic skills, and Data Engineer will require programming and data interpretation skills. However technical skills are not enough, companies want people who have knowledge of the methods and applications of analytics, but also understand business problem and able to work in teams and can effectively communicate well to executives.<\/p>\n

Every week I get calls from companies looking to hire Big data graduates. Of course we have a good reputation for developing qualified big data professionals that work well in the industry. I believe data is becoming the most valuable resource driving the global economic growth today. In this knowledge age, data is the main factor for facts and truth.<\/p>\n","protected":false},"excerpt":{"rendered":"

Trong s\u00e1u th\u00e1ng qua, nhi\u1ec1u c\u00f4ng ti t\u1edbi CMU \u0111\u1ec3 t\u00ecm ng\u01b0\u1eddi t\u1ed1t nghi\u1ec7p Big data v\u00ec thi\u1ebfu h\u1ee5t k\u0129 n\u0103ng n\u00e0y \u0111ang t\u1edbi l\u00fac … <\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[26],"tags":[],"class_list":["post-4187","post","type-post","status-publish","format-standard","hentry","category-xu-huong-cong-nghe"],"_links":{"self":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/4187","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=4187"}],"version-history":[{"count":2,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/4187\/revisions"}],"predecessor-version":[{"id":4189,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/4187\/revisions\/4189"}],"wp:attachment":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4187"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4187"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4187"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}