{"id":39573,"date":"2019-10-31T22:36:07","date_gmt":"2019-10-31T19:36:07","guid":{"rendered":"https:\/\/prohoster.info\/blog\/zakat-epohi-big-data\/"},"modified":"2019-10-31T22:36:07","modified_gmt":"2019-10-31T19:36:07","slug":"zakat-epohi-big-data","status":"publish","type":"post","link":"https:\/\/prohoster.info\/cs\/blog\/administrirovanie\/zakat-epohi-big-data","title":{"rendered":"\u00dasvit \u00e9ry Big Data","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Mnoho zahrani\u010dn\u00edch autor\u016f se shoduje na tom, \u017ee \u00e9ra Big Data skon\u010dila. V tomto p\u0159\u00edpad\u011b se pod term\u00ednem Big Data rozum\u00ed technologie zalo\u017een\u00e9 na Hadoopu. Mnoho autor\u016f dokonce s jistotou m\u016f\u017ee uv\u00e9st datum, kdy Big Data opustila tento sv\u011bt, a t\u00edmto datem je 05.06.2019. <\/p>\n<p>Co se tedy stalo v tento v\u00fdznamn\u00fd den? <\/p>\n<p>V tento den spole\u010dnost MAPR sl\u00edbila zastavit svou \u010dinnost, pokud nenajde prost\u0159edky pro dal\u0161\u00ed fungov\u00e1n\u00ed. Pozd\u011bji, v srpnu 2019, byla MAPR koupena spole\u010dnost\u00ed HP. Ale pokud se vr\u00e1t\u00edme zp\u011bt k \u010dervnu, nelze si nev\u0161imnout trag\u00e9die tohoto obdob\u00ed pro trh Big Data. V tomto m\u011bs\u00edci do\u0161lo k p\u00e1du akciov\u00fdch kurz\u016f spole\u010dnosti CLOUDERA \u2013 vedouc\u00edho hr\u00e1\u010de na tomto trhu, kter\u00e1 v lednu t\u00e9ho\u017e roku provedla f\u00fazi s chronicky ztr\u00e1tov\u00fdm HORTOWORKS. P\u00e1d byl velmi v\u00fdrazn\u00fd a dos\u00e1hl 43 %, co\u017e nakonec vedlo ke sn\u00ed\u017een\u00ed tr\u017en\u00ed kapitalizace CLOUDERA z 4,1 na 1,4 miliardy dolar\u016f.<\/p>\n<p>Nemo\u017eno nezm\u00ednit, \u017ee f\u00e1my o nafouknut\u00ed bubliny v oblasti technologi\u00ed, kter\u00e9 vych\u00e1zej\u00ed z Hadoopu, kolovaly u\u017e od prosince 2014, ale odv\u00e1\u017en\u011b p\u0159e\u017eila t\u00e9m\u011b\u0159 dal\u0161\u00edch p\u011bt let. Tyto f\u00e1my pramenily z odm\u00edtnut\u00ed spole\u010dnosti Google, kter\u00e1 stoj\u00ed za technologi\u00ed Hadoop, od sv\u00e9ho vyn\u00e1lezu. Av\u0161ak technologie se ujala v obdob\u00ed p\u0159echodu firem na cloudov\u00e1 \u0159e\u0161en\u00ed a bou\u0159liv\u00e9ho rozvoje um\u011bl\u00e9 inteligence. Proto, kdy\u017e se ohl\u00e9dneme zp\u011bt, m\u016f\u017eeme s jistotou \u0159\u00edci, \u017ee konec byl o\u010dek\u00e1van\u00fd.<\/p>\n<p>Tak\u017ee \u00e9ra Big Data skon\u010dila, ale b\u011bhem pr\u00e1ce s velk\u00fdmi daty si firmy uv\u011bdomily v\u0161echny nuance s nimi spojen\u00e9, v\u00fdhody, kter\u00e9 mohou Big Data p\u0159in\u00e9st byznysu, a tak\u00e9 se nau\u010dily vyu\u017e\u00edvat um\u011blou inteligenci k vyt\u011b\u017een\u00ed hodnoty z nezpracovan\u00fdch dat.<\/p>\n<p>O to zaj\u00edmav\u011bj\u0161\u00ed se st\u00e1v\u00e1 ot\u00e1zka, co nahrad\u00ed tuto technologii a jak se budou d\u00e1le vyv\u00edjet analytick\u00e9 technologie. <br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h3>Dopln\u011bn\u00e1 analytika<\/h3>\n<p>\n B\u011bhem popisovan\u00fdch ud\u00e1lost\u00ed spole\u010dnosti p\u016fsob\u00edc\u00ed v oblasti anal\u00fdzy dat nezah\u00e1lely. O tom sv\u011bd\u010d\u00ed informace o transakc\u00edch, kter\u00e9 se uskute\u010dnily v roce 2019. V tomto roce do\u0161lo k nejv\u011bt\u0161\u00ed transakci na trhu \u2013 akvizici platformy Tableau od Salesforce za 15,7 miliardy dolar\u016f. Men\u0161\u00ed transakce se uskute\u010dnila mezi Googlem a Lookerem. A samoz\u0159ejm\u011b nelze opomenout akvizici platformy big data Attunity spole\u010dnost\u00ed Qlik.<\/p>\n<p>L\u00edd\u0159i trhu BI a odborn\u00edci Gartner hovo\u0159\u00ed o obrovsk\u00e9m posunu v p\u0159\u00edstupech k anal\u00fdze dat, kter\u00fd tento trh \u00fapln\u011b zru\u0161\u00ed a BI nahrad\u00ed AI. V tomto kontextu je d\u016fle\u017eit\u00e9 poznamenat, \u017ee zkratka AI neznamen\u00e1 \"Artificial Intelligence\", ale \"Augmented Intelligence\". Poj\u010fme se pod\u00edvat bl\u00ed\u017ee na to, co se skr\u00fdv\u00e1 za term\u00ednem \"Dopln\u011bn\u00e1 anal\u00fdza\". <\/p>\n<p>Dopln\u011bn\u00e1 anal\u00fdza, podobn\u011b jako roz\u0161\u00ed\u0159en\u00e1 realita, vych\u00e1z\u00ed z n\u011bkolika spole\u010dn\u00fdch postul\u00e1t\u016f:<\/p>\n<ul>\n<li>mo\u017enost komunikovat pomoc\u00ed zpracov\u00e1n\u00ed p\u0159irozen\u00e9ho jazyka (NLP), tzn. v lidsk\u00e9m jazyce;<\/li>\n<li>vyu\u017eit\u00ed um\u011bl\u00e9 inteligence znamen\u00e1, \u017ee data budou p\u0159edem zpracov\u00e1na strojov\u00fdm inteligenc\u00ed;<\/li>\n<li>a samoz\u0159ejm\u011b doporu\u010den\u00ed dostupn\u00e1 u\u017eivateli syst\u00e9mu, kter\u00e1 byla pr\u00e1v\u011b generov\u00e1na um\u011blou inteligenc\u00ed.<\/li>\n<\/ul>\n<p>\n Podle n\u00e1zoru v\u00fdrobc\u016f analytick\u00fdch platforem by jejich pou\u017eit\u00ed m\u011blo b\u00fdt dostupn\u00e9 pro u\u017eivatele, kte\u0159\u00ed nemaj\u00ed speci\u00e1ln\u00ed dovednosti, jako je znalost SQL nebo podobn\u00e9ho skriptovac\u00edho jazyka, nemaj\u00ed statistick\u00e9 nebo matematick\u00e9 vzd\u011bl\u00e1n\u00ed, ani neovl\u00e1daj\u00ed popul\u00e1rn\u00ed jazyky zam\u011b\u0159en\u00e9 na zpracov\u00e1n\u00ed dat a p\u0159\u00edslu\u0161n\u00e9 knihovny. Tito lid\u00e9, naz\u00fdvan\u00ed \"Citizen Data Scientist\", by m\u011bli m\u00edt pouze vynikaj\u00edc\u00ed obchodn\u00ed kvalifikaci. Jejich \u00fakolem je zachytit obchodn\u00ed poznatky z podn\u011bt\u016f a p\u0159edpov\u011bd\u00ed, kter\u00e9 jim poskytne um\u011bl\u00e1 inteligence, a zp\u0159esnit sv\u00e9 domn\u011bnky pomoc\u00ed NLP.<\/p>\n<p>P\u0159i popisu procesu, jak\u00fdm u\u017eivatel\u00e9 pracuj\u00ed se syst\u00e9my t\u00e9to t\u0159\u00eddy, si m\u016f\u017eeme p\u0159edstavit n\u00e1sleduj\u00edc\u00ed obraz. \u010clov\u011bk, kdy\u017e p\u0159ijde do pr\u00e1ce a spust\u00ed p\u0159\u00edslu\u0161nou aplikaci, krom\u011b obvykl\u00e9ho souboru report\u016f a dashboard\u016f, kter\u00e9 lze analyzovat standardn\u00edmi metodami (t\u0159\u00edd\u011bn\u00ed, seskupov\u00e1n\u00ed, prov\u00e1d\u011bn\u00ed aritmetick\u00fdch operac\u00ed), vid\u00ed ur\u010dit\u00e9 n\u00e1pov\u011bdy a doporu\u010den\u00ed, n\u011bco jako: \u201eAbychom dos\u00e1hli KPI t\u00fdkaj\u00edc\u00edho se po\u010dtu prodej\u016f, m\u011bli byste aplikovat slevu na produkty z kategorie \u201aZahradnictv\u00ed\u2018.\u201c Krom\u011b toho se \u010dlov\u011bk m\u016f\u017ee obr\u00e1tit na firemn\u00ed messenger: Skype, Slack atd. M\u016f\u017ee robotovi polo\u017eit ot\u00e1zky textem nebo hlasem: \u201eVyber mi p\u011bt nejziskov\u011bj\u0161\u00edch klient\u016f.\u201c Po obdr\u017een\u00ed odpov\u011bdi by m\u011bl u\u010dinit optim\u00e1ln\u00ed rozhodnut\u00ed na z\u00e1klad\u011b sv\u00fdch zku\u0161enost\u00ed v byznysu a p\u0159in\u00e9st spole\u010dnosti zisk. <\/p>\n<p>Pokud se vr\u00e1t\u00edme zp\u011bt a pod\u00edv\u00e1me se na slo\u017een\u00ed analyzovan\u00fdch informac\u00ed, produkty t\u0159\u00eddy roz\u0161\u00ed\u0159en\u00e9 analytiky mohou v t\u00e9to f\u00e1zi lidem usnadnit \u017eivot. Ide\u00e1ln\u011b by m\u011blo b\u00fdt zam\u00fd\u0161leno, \u017ee u\u017eivatel pouze nazna\u010d\u00ed analytick\u00e9mu produktu zdroje po\u017eadovan\u00fdch informac\u00ed, a program se postar\u00e1 o vytvo\u0159en\u00ed modelu dat, propojen\u00ed tabulek a podobn\u00e9 \u00fakoly.<\/p>\n<p>To v\u0161e by m\u011blo p\u0159edev\u0161\u00edm zajistit \u201edemokratizaci\u201c dat, tzn. ka\u017ed\u00fd \u010dlov\u011bk m\u016f\u017ee analyzovat cel\u00fd soubor informac\u00ed, kter\u00e9 m\u00e1 firma k dispozici. Proces rozhodov\u00e1n\u00ed by m\u011bl b\u00fdt podpo\u0159en metodami statistick\u00e9 anal\u00fdzy. Doba p\u0159\u00edstupu k dat\u016fm by m\u011bla b\u00fdt minim\u00e1ln\u00ed, tak\u017ee by nebylo t\u0159eba ps\u00e1t skripty a SQL dotazy. A samoz\u0159ejm\u011b, mohlo by to u\u0161et\u0159it n\u00e1klady na vysoce placen\u00e9 specialisty na Data Science.<\/p>\n<p>Hypoteticky technologie otev\u00edraj\u00ed velmi optimistick\u00e9 vyhl\u00eddky pro podnik\u00e1n\u00ed.<\/p>\n<h3>Co nahrazuje Big Data<\/h3>\n<p>\n Ale vlastn\u011b jsem za\u010dal sv\u016fj \u010dl\u00e1nek s Big Data. A tuto t\u00e9ma jsem nemohl rozvinout bez kr\u00e1tk\u00e9ho exkurzu do modern\u00edch BI n\u00e1stroj\u016f, jejich\u017e z\u00e1kladem \u010dasto slou\u017e\u00ed Big Data. Osud velk\u00fdch dat je nyn\u00ed jasn\u011b p\u0159edur\u010den a jsou to cloudov\u00e9 technologie. Upozornil jsem na transakce uzav\u0159en\u00e9 s v\u00fdrobci BI, abych demonstroval, \u017ee nyn\u00ed ka\u017ed\u00fd analytick\u00fd syst\u00e9m m\u00e1 pod sebou cloudov\u00e9 \u00falo\u017ei\u0161t\u011b a cloudov\u00e9 slu\u017eby maj\u00ed BI jako front end.<\/p>\n<p>Nem\u00e9n\u011b d\u016fle\u017eit\u00e9 je si uv\u011bdomit, \u017ee mezi pil\u00ed\u0159i v oblasti datab\u00e1z\u00ed, jako jsou ORACLE a Microsoft, se vyv\u00edj\u00ed jejich obchodn\u00ed sm\u011bry a to sm\u011brem k cloudu. V\u0161echny nab\u00edzen\u00e9 slu\u017eby lze naj\u00edt v oblaku, ale n\u011bkter\u00e9 cloudov\u00e9 slu\u017eby ji\u017e nelze z\u00edskat on-premise. Bylo vykon\u00e1no zna\u010dn\u00e9 \u00fasil\u00ed ve vyu\u017e\u00edv\u00e1n\u00ed model\u016f strojov\u00e9ho u\u010den\u00ed, byly vytvo\u0159eny knihovny dostupn\u00e9 u\u017eivatel\u016fm, a nastaveny rozhran\u00ed pro usnadn\u011bn\u00ed pr\u00e1ce s modely od jejich v\u00fdb\u011bru a\u017e po nastaven\u00ed doby spu\u0161t\u011bn\u00ed.<\/p>\n<p>Dal\u0161\u00ed d\u016fle\u017eitou v\u00fdhodou pou\u017e\u00edv\u00e1n\u00ed cloudov\u00fdch slu\u017eeb, kterou uv\u00e1d\u011bj\u00ed v\u00fdrobci, je prakticky neomezen\u00e9 mno\u017estv\u00ed datov\u00fdch sad na jak\u00e9koli t\u00e9ma pro tr\u00e9nink model\u016f. <\/p>\n<p>Nicm\u00e9n\u011b, vyvst\u00e1v\u00e1 ot\u00e1zka, jak si cloudov\u00e9 technologie povedou v na\u0161\u00ed zemi?<br \/>\n<br \/>Zdroj: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/473640\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u043e \u0438\u043d\u043e\u0441\u0442\u0440\u0430\u043d\u043d\u044b\u0445 \u0430\u0432\u0442\u043e\u0440\u043e\u0432 \u0441\u0445\u043e\u0434\u044f\u0442\u0441\u044f \u043a \u0442\u043e\u043c\u0443, \u0447\u0442\u043e \u044d\u043f\u043e\u0445\u0430 Big Data \u043f\u043e\u0434\u043e\u0448\u043b\u0430 \u043a \u043a\u043e\u043d\u0446\u0443. \u0418 \u0432 \u0434\u0430\u043d\u043d\u043e\u043c \u0441\u043b\u0443\u0447\u0430\u0435 \u043f\u043e\u0434 \u0442\u0435\u0440\u043c\u0438\u043d\u043e\u043c Big Data \u043f\u043e\u043d\u0438\u043c\u0430\u044e\u0442\u0441\u044f \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438, \u043e\u0441\u043d\u043e\u0432\u0430\u043d\u043d\u044b\u0435 \u043d\u0430 Hadoop. \u041c\u043d\u043e\u0433\u0438\u0435 \u0430\u0432\u0442\u043e\u0440\u044b, \u0434\u0430\u0436\u0435 \u043c\u043e\u0433\u0443\u0442 \u0441 \u0443\u0432\u0435\u0440\u0435\u043d\u043d\u043e\u0441\u0442\u044c\u044e \u043d\u0430\u0437\u0432\u0430\u0442\u044c \u0434\u0430\u0442\u0443, \u043a\u043e\u0433\u0434\u0430 Big Data \u043e\u0441\u0442\u0430\u0432\u0438\u043b\u0430 \u044d\u0442\u043e\u0442 \u043c\u0438\u0440 \u0438 \u044d\u0442\u0430 \u0434\u0430\u0442\u0430 \u2014 05.06.2019. \u0427\u0442\u043e \u0436\u0435 \u043f\u0440\u043e\u0438\u0437\u043e\u0448\u043b\u043e \u0432 \u044d\u0442\u043e\u0442 \u0437\u043d\u0430\u043c\u0435\u043d\u0430\u0442\u0435\u043b\u044c\u043d\u044b\u0439 \u0434\u0435\u043d\u044c? \u0412 \u044d\u0442\u043e\u0442 \u0434\u0435\u043d\u044c, [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-39573","post","type-post","status-publish","format-standard","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u043e \u0438\u043d\u043e\u0441\u0442\u0440\u0430\u043d\u043d\u044b\u0445 \u0430\u0432\u0442\u043e\u0440\u043e\u0432 \u0441\u0445\u043e\u0434\u044f\u0442\u0441\u044f \u043a \u0442\u043e\u043c\u0443, \u0447\u0442\u043e \u044d\u043f\u043e\u0445\u0430 Big Data \u043f\u043e\u0434\u043e\u0448\u043b\u0430 \u043a \u043a\u043e\u043d\u0446\u0443. \u0418 \u0432 \u0434\u0430\u043d\u043d\u043e\u043c \u0441\u043b\u0443\u0447\u0430\u0435 \u043f\u043e\u0434 \u0442\u0435\u0440\u043c\u0438\u043d\u043e\u043c Big Data \u043f\u043e\u043d\u0438\u043c\u0430\u044e\u0442\u0441\u044f \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438, \u043e\u0441\u043d\u043e\u0432\u0430\u043d\u043d\u044b\u0435 \u043d\u0430 Hadoop.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Yuri Gagarin\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/prohoster.info\/cs\/blog\/administrirovanie\/zakat-epohi-big-data\" \/>\n\t\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 5.0.3\" \/>\n\t\t<meta property=\"og:locale\" content=\"cs_CZ\" \/>\n\t\t<meta property=\"og:site_name\" content=\"ProHoster | \u041a\u0443\u043f\u0438\u0442\u044c \u043d\u0430\u0434\u0435\u0436\u043d\u044b\u0439 \u0445\u043e\u0441\u0442\u0438\u043d\u0433 \u0434\u043b\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 DDoS, VPS VDS \u0441\u0435\u0440\u0432\u0435\u0440\u044b\" \/>\n\t\t<meta property=\"og:type\" content=\"article\" \/>\n\t\t<meta property=\"og:title\" content=\"\ud83e\udd47\u0417\u0430\u043a\u0430\u0442 \u044d\u043f\u043e\u0445\u0438 Big Data | ProHoster\" \/>\n\t\t<meta property=\"og:description\" content=\"\u041c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u043e \u0438\u043d\u043e\u0441\u0442\u0440\u0430\u043d\u043d\u044b\u0445 \u0430\u0432\u0442\u043e\u0440\u043e\u0432 \u0441\u0445\u043e\u0434\u044f\u0442\u0441\u044f \u043a \u0442\u043e\u043c\u0443, \u0447\u0442\u043e \u044d\u043f\u043e\u0445\u0430 Big Data \u043f\u043e\u0434\u043e\u0448\u043b\u0430 \u043a \u043a\u043e\u043d\u0446\u0443. \u0418 \u0432 \u0434\u0430\u043d\u043d\u043e\u043c \u0441\u043b\u0443\u0447\u0430\u0435 \u043f\u043e\u0434 \u0442\u0435\u0440\u043c\u0438\u043d\u043e\u043c Big Data \u043f\u043e\u043d\u0438\u043c\u0430\u044e\u0442\u0441\u044f \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438, \u043e\u0441\u043d\u043e\u0432\u0430\u043d\u043d\u044b\u0435 \u043d\u0430 Hadoop.\" \/>\n\t\t<meta property=\"og:url\" content=\"https:\/\/prohoster.info\/cs\/blog\/administrirovanie\/zakat-epohi-big-data\" \/>\n\t\t<meta property=\"og:image\" content=\"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg\" \/>\n\t\t<meta property=\"og:image:secure_url\" content=\"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg\" \/>\n\t\t<meta property=\"og:image:width\" content=\"350\" \/>\n\t\t<meta property=\"og:image:height\" content=\"350\" \/>\n\t\t<meta property=\"article:published_time\" content=\"2019-10-31T19:36:07+00:00\" \/>\n\t\t<meta property=\"article:modified_time\" content=\"2019-10-31T19:36:07+00:00\" \/>\n\t\t<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/prohoster\" \/>\n\t\t<meta property=\"article:author\" content=\"https:\/\/www.facebook.com\/prohoster\" \/>\n\t\t<!-- All in One SEO -->\n\n","aioseo_head_json":{"title":"\ud83e\udd47\u00dasvit nov\u00e9 \u00e9ry po Big Data | ProHoster","description":"Mnoho zahrani\u010dn\u00edch autor\u016f se shoduje na tom, \u017ee \u00e9ra Big Data skon\u010dila. 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