![\"\u00favod](\"https:\/\/kursora.com\/wp-content\/uploads\/2025\/08\/uvod-do-pokrocile-analytiky-1024x585.webp\" "\\"\u00favod")
<\/p>\nV dne\u0161n\u00ed rychle se m\u011bn\u00edc\u00edm sv\u011bt\u011b je pokro\u010dil\u00e1 analytika<\/b> nezbytn\u00e1. Pom\u00e1h\u00e1 firm\u00e1m v\u00fdrazn\u011b zlep\u0161it efektivitu a rozhodov\u00e1n\u00ed<\/b>. Analyzov\u00e1n\u00edm velk\u00fdch mno\u017estv\u00ed dat najdou podniky d\u016fle\u017eit\u00e9 vzorce a de moda<\/b>. Para jim umo\u017en\u00ed pl\u00e1novat strategie efektivn\u011bji a sni\u017eovat n\u00e1klady.<\/p>\n
Spole\u010dnosti pak mohou rychleji reagovat na trh a zvy\u0161ovat svou konkurenceschopnost. Znalosti v oblasti pokro\u010dil\u00e9 analytiky se daj\u00ed z\u00edskat nap\u0159\u00edklad z praktick\u00fdch kurz\u016f. Ty jsou zam\u011b\u0159en\u00e9 na pou\u017e\u00edv\u00e1n\u00ed analytick\u00fdch metod.<\/p>\n
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V \u00favodu do pokro\u010dil\u00e9 analytiky je d\u016fle\u017eit\u00e9 pochopit z\u00e1kladn\u00ed ideje. Tenhle obor pou\u017e\u00edv\u00e1 speci\u00e1ln\u00ed metody ke zji\u0161t\u011bn\u00ed vzor\u016f a trend\u016f z minulosti. D\u011bl\u00e1 to pomoc\u00ed statistik a nejnov\u011bj\u0161\u00edch technologi\u00ed. Um\u011bl\u00e1 inteligence a strojov\u00e9 u\u010den\u00ed pom\u00e1haj\u00ed odhadnout, co se m\u016f\u017ee st\u00e1t v budoucnosti.<\/p>\n
Firmy pou\u017e\u00edvaj\u00edc\u00ed pokro\u010dilou analytiku l\u00e9pe rozum\u00ed sv\u00fdm z\u00e1kazn\u00edk\u016fm. D\u00edky tomu mohou zlep\u0161it sv\u00e9 pracovn\u00ed postupy a d\u011blat lep\u0161\u00ed rozhodnut\u00ed. Pokro\u010dil\u00e1 analytika<\/b> taky pom\u00e1h\u00e1 vylep\u0161it strategie a zvy\u0161uje \u0161ance na \u00fasp\u011bch na trhu.<\/p>\n
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Sb\u011br dat<\/b> je kl\u00ed\u010dov\u00fd pro \u00fasp\u011bch v byznysu. kdy\u017e jsou datos<\/b> kvalitn\u00ed, firmy je m\u016f\u017eou l\u00e9pe vyu\u017e\u00edt. Tato pravidla umo\u017e\u0148uj\u00ed naj\u00edt nov\u00e9 mo\u017enosti a rychleji reagovat na zm\u011bny na trhu.<\/p>\n\u00bfPro\u010d je d\u016fle\u017eit\u00e9 m\u00edt kvalitn\u00ed data?<\/h3>\n
Dobr\u00e1 datos<\/b> pom\u00e1haj\u00ed firm\u00e1m d\u011blat spr\u00e1vn\u00e1 rozhodnut\u00ed pro jejich budoucnost<\/b>. Bez spolehliv\u00fdch dat mohou firmy \u0161patn\u011b p\u0159edv\u00eddat de moda<\/b>. To m\u016f\u017ee v\u00e9st k velk\u00fdm ztr\u00e1t\u00e1m. Investice do sb\u011bru dat se vyplat\u00ed, proto\u017ee zvy\u0161uje efektivitu.<\/p>\nMetodolog\u00eda sb\u011bru a vyhodnocov\u00e1n\u00ed dat<\/h3>\n
Existuje mnoho zp\u016fsob\u016f, jak sb\u00edrat datos<\/b>. Firmy mhou pou\u017e\u00edt tyto m\u00e9todo:<\/p>\n Je d\u016fle\u017eit\u00e9 data pravideln\u011b vyhodnocovat. Para m\u016f\u017ee zahrnovat an\u00e1lisis de tendencias, las estad\u00edsticas modelan nebo vizualizaci dat. Tyto metody pom\u00e1haj\u00ed odkr\u00fdt skryt\u00e9 vzory.<\/p>\n Pokro\u010dil\u00e1 analytika<\/b> pom\u00e1h\u00e1 firm\u00e1m efektivn\u011b rozhodovat. Umo\u017e\u0148uje pr\u00e1ci se slo\u017eit\u011bj\u0161\u00edmi daty a porozum\u011bn\u00ed trend\u016fm. Schopnost predikovat budouc\u00ed v\u00fdvoje a naj\u00edt nuevos p\u0159\u00edle\u017eitosti<\/b> je jej\u00ed kl\u00ed\u010dovou v\u00fdhodou.<\/p>\n En el an\u00e1lisis pokro\u010dil\u00e9 vyu\u017e\u00edv\u00e1me r\u016fzn\u00e9 techniky jako strojov\u00e9 u\u010den\u00ed, prediktivn\u00ed anal\u00fdzu a um\u011blou inteligenci. D\u00edky nim mohou firmy l\u00e9pe reagovat na zm\u011bny a pl\u00e1novat svou budoucnost<\/b>. Este an\u00e1lisis otev\u00edr\u00e1 nov\u00e9 mo\u017enosti zkoum\u00e1n\u00ed dat.<\/p>\n An\u00e1lisis tradicional<\/b> vych\u00e1z\u00ed z minul\u00fdch dat a vytv\u00e1\u0159\u00ed reporty. Pokro\u010dil\u00e1 anal\u00edtica<\/b> ale jde d\u00e1l. Sna\u017e\u00ed se p\u0159edpov\u00eddat budoucnost<\/b> a odhalovat skryt\u00e9 p\u0159\u00edle\u017eitosti. Pom\u00e1h\u00e1 firm\u00e1m l\u00e9pe \u010delit v\u00fdzv\u00e1m a vyu\u017e\u00edvat nov\u00e9 \u0161ance.<\/p>\n Pokro\u010dil\u00e1 anal\u00edtica<\/b> obsahuje r\u016fzn\u00e9 techniky pro lep\u0161\u00ed zpracov\u00e1n\u00ed a vyhodnocen\u00ed dat v firm\u00e1ch. Mezi hlavn\u00ed pat\u0159\u00ed prediktivn\u00ed a preskriptivn\u00ed analytika<\/b>. Pom\u00e1haj\u00ed zlep\u0161ovat rozhodov\u00e1n\u00ed<\/b> a zvy\u0161uj\u00ed efektivitu i zisky.<\/p>\n An\u00e1lisis predictivo<\/b> vyu\u017e\u00edv\u00e1 historick\u00e1 data k odhadu budoucnosti. Pom\u00e1h\u00e1 firm\u00e1m \u00f3ptimoizovat pr\u00e1ci, nap\u0159\u00edklad v logistice. D\u00edky n\u00ed mohou l\u00e9pe pl\u00e1novat a p\u0159edch\u00e1zet mo\u017en\u00fdm probl\u00e9m\u016fm na trhu.<\/p>\n An\u00e1lisis prescriptivo<\/b> rad\u00ed firm\u00e1m, jak\u00fdm sm\u011brem se ub\u00edrat. Amazon ji pou\u017e\u00edv\u00e1 pro lep\u0161\u00ed nastaven\u00ed cen. D\u00edky n\u00ed firmy zjist\u00ed, jak b\u00fdt \u00fa\u010dinn\u011bj\u0161\u00ed a \u00fasp\u011b\u0161n\u011bj\u0161\u00ed na trhu.<\/p>\n Pokro\u010dil\u00e1 anal\u00edtica<\/b> je d\u016fle\u017eit\u00e1 pro efektivn\u00ed rozhodov\u00e1n\u00ed<\/b> ve firm\u00e1ch. S dosstatkem dat mohou firmy vyu\u017e\u00edt analytiku pro lep\u0161\u00ed pl\u00e1nov\u00e1n\u00ed. D\u00edky tomu vznikaj\u00ed strategie, kter\u00e9 l\u00e9pe reaguj\u00ed na trh.<\/p>\n Mana\u017ee\u0159i vyu\u017e\u00edvaj\u00edc\u00ed pokro\u010dil\u00e9 metody l\u00e9pe pochop\u00ed trh. Maj\u00ed k dispozici informace, kter\u00e9 sni\u017euj\u00ed rizika. D\u00edky tomu mohou rychle a p\u0159esn\u011b rozhodovat, co\u017e je ve v\u00fdhod\u011b oproti konkurenci.<\/p>\n Firmy s dobrou analytikou p\u0159edpov\u00eddaj\u00ed tr\u017en\u00ed zm\u011bny. Rychle se p\u0159izp\u016fsobuj\u00ed a rozum\u00ed sv\u00fdm z\u00e1kazn\u00edk\u016fm. Analytika je kl\u00ed\u010dem k \u00fasp\u011b\u0161n\u00e9mu rozhodov\u00e1n\u00ed.<\/p>\n Spole\u010dnosti jako Coca-cola<\/b> a Netflix<\/b> uk\u00e1zaly s\u00edlu pokro\u010dil\u00e9 analytiky. D\u00edky n\u00ed mohou l\u00e9pe \u0159\u00eddit operace a zlep\u0161ovat v\u00fdsledky. Anal\u00fdza dat pom\u00e1h\u00e1 t\u011bmto firm\u00e1m b\u00fdt efektivn\u011bj\u0161\u00ed.<\/p>\n Coca-cola<\/b> vyu\u017eila pokro\u010dilou analytiku pro lep\u0161\u00ed spr\u00e1vu dodavatelsk\u00e9ho \u0159et\u011bzce. D\u00edky anal\u00fdze v\u00fdroby a distribuce sn\u00ed\u017eila n\u00e1klady a vylep\u0161ila procesy. Jejich metody zefektivnily operace a urychlily doru\u010den\u00ed z\u00e1kazn\u00edk\u016fm.<\/p>\n Netflix<\/b> pou\u017e\u00edv\u00e1 prediktivn\u00ed analytiku pro pochopen\u00ed, co se u\u017eivatel\u016fm l\u00edb\u00ed. Vyu\u017e\u00edv\u00e1 data, aby lidem nab\u00edzel to, co cht\u011bj\u00ed vid\u011bt. D\u00edky tomu je spokojen\u011bj\u0161\u00ed. Esta estrategia de Netflix se utiliza para hacer compras en lugares p\u00fablicos.<\/p>\n Dnes je d\u016fle\u017eit\u00e9 um\u011bt pracovat s velk\u00fdm mno\u017estv\u00edm dat. pokro\u010dil\u00e9 analytick\u00e9 n\u00e1stroje<\/b> n\u00e1m v tom pom\u00e1haj\u00ed. D\u00edky nim m\u016f\u017eeme l\u00e9pe porozum\u011bt dat\u016fm, kter\u00e1 m\u00e1me. Nejzn\u00e1m\u011bj\u0161\u00ed n\u00e1stroje v t\u00e9to oblasti jsou Cuadro<\/b>, SAS<\/b> a IBM Watson<\/b>.<\/p>\n Cuadro<\/b> um\u00ed p\u0159etv\u00e1\u0159et slo\u017eit\u00e1 data na jednoduch\u00e9 a kr\u00e1sn\u00e9 grafy. D\u00edky tomu je anal\u00fdza dat jednoduch\u00e1 a z\u00e1bavn\u00e1. Je to skv\u011bl\u00fd n\u00e1stroj pro firmy, kter\u00e9 cht\u011bj\u00ed lep\u0161\u00ed vizualizace sv\u00fdch dat.<\/p>\n SAS<\/b> Obl\u00edben\u00e1 plataforma para analizar ese modelo estad\u00edstico. Je bohat\u011b vybavena funkcemi pro r\u016fzn\u00e9 typy anal\u00fdz. Pomoci SAS<\/b> m\u016f\u017eeme odhalit de moda<\/b> a vzorce v datech, co\u017e pom\u00e1h\u00e1 p\u0159i rozhodov\u00e1n\u00ed.<\/p>\n IBM Watson<\/b> Analytics vyu\u017e\u00edv\u00e1 um\u011blou inteligenci a strojov\u00e9 u\u010den\u00ed. Dok\u00e1\u017ee naj\u00edt vzory v datech, kter\u00e9 bychom sami p\u0159ehl\u00e9dli. To usnad\u0148uje objevov\u00e1n\u00ed souvislost\u00ed a pom\u00e1h\u00e1 p\u0159i pl\u00e1nov\u00e1n\u00ed a rozhodov\u00e1n\u00ed.<\/p>\n Implementovat analytiku do podnik\u00e1n\u00ed je z\u00e1sadn\u00ed pro z\u00edsk\u00e1n\u00ed v\u00fdhody nad konkurenc\u00ed. Spr\u00e1vn\u011b zaveden\u00e1 analytika pom\u016f\u017ee vylep\u0161it rozhodov\u00e1n\u00ed a zkvalitnit v\u00fdkony cel\u00e9 firmy. Pro \u00fasp\u011bch je nutn\u00e9 dodr\u017eet ur\u010dit\u00e9 kroky.<\/p>\n Prvn\u00ed krok je pochopit, co firma pot\u0159ebuje. Na z\u00e1klad\u011b toho se vyberou nejlep\u0161\u00ed analytick\u00e9 n\u00e1stroje<\/b> una tecnolog\u00eda. Potom je d\u016fle\u017eit\u00e9 nau\u010dit zam\u011bstnance, jak tyto n\u00e1stroje pou\u017e\u00edvat. Cel\u00fd proces by m\u011bl postupovat krok za krokem, se st\u00e1l\u00fdm hodnocen\u00edm pokrok\u016f.<\/p>\n Implementar an\u00e1lisis<\/b> \u010dasto naraz\u00ed na probl\u00e9my, jako je nedostatek kvalifikovan\u00fdch lid\u00ed nebo odpor k zm\u011bn\u00e1m. Tyto probl\u00e9my se daj\u00ed \u0159e\u0161it \u0161kolen\u00edm a budov\u00e1n\u00edm kultury otev\u0159en\u00e9 pro data. Otev\u0159en\u00e1 komunikace a zapojen\u00ed zam\u011bstnanc\u016f jsou kl\u00ed\u010dem k \u00fasp\u011b\u0161n\u00e9mu p\u0159ijet\u00ed analytiky.<\/p>\n Pokro\u010dil\u00e1 analytika je d\u016fle\u017eit\u00e1 pro firmy hledaj\u00edc\u00ed innovace<\/b>. Pomoc\u00ed n\u00ed mohou objevit nov\u00e9 tr\u017en\u00ed trendy. To usnad\u0148uje pochopen\u00ed z\u00e1kaznick\u00fdch pot\u0159eb a vede k lep\u0161\u00edmu rozhodov\u00e1n\u00ed.<\/p>\n Integrace an\u00e1lisis de datos<\/b> znamen\u00e1 z\u00e1klad pro innovace<\/b>. Firmy tak mohou odhalit, jak se spot\u0159ebitel\u00e9 chovaj\u00ed. To pom\u00e1h\u00e1 rychle reagovat na zm\u011bny a b\u00fdt o krok p\u0159ed konkurenc\u00ed.<\/p>\n Analytika nejen odhaluje nuevos p\u0159\u00edle\u017eitosti<\/b>, ale i zlep\u0161uje procesy. Vede k rychlej\u0161\u00edm a \u00fa\u010dinn\u011bj\u0161\u00edm rozhodnut\u00edm, rozd\u00edl oproti star\u0161\u00ed metody je markantn\u00ed.<\/p>\n Pokro\u010dil\u00e1 analytika poskytuje firm\u00e1m v\u00fdznamn\u00e9 p\u0159\u00ednosy. Pomoc\u00ed dat mohou l\u00e9pe kontrolovat sv\u00e9 operace a \u0161et\u0159it pen\u00edze. Identifikace a zlep\u0161en\u00ed slab\u00fdch m\u00edst sni\u017euje v\u00fddaje a zvy\u0161uje efektivitu.<\/p>\n Firmy vyu\u017e\u00edvaj\u00edc\u00ed pokro\u010dilou analytiku maj\u00ed nav\u00edc v\u00fdhodu. Dok\u00e1\u017eou naj\u00edt nov\u00e9 mo\u017enosti pro r\u016fst.<\/p>\n \u010cinnosti vedouc\u00ed ke sni\u017eov\u00e1n\u00ed n\u00e1klad\u016f jsou kl\u00ed\u010dov\u00e9. Firmy d\u00edky pokro\u010dil\u00e9 analytice z\u00edsk\u00e1vaj\u00ed v\u00fdhody, jako je:<\/p>\n D\u00edky d\u016fkladn\u00e9 anal\u00fdze dat firmy otev\u00edraj\u00ed dve\u0159e k nov\u00fdm p\u0159\u00edle\u017eitostem. Pokro\u010dil\u00e1 analytika umo\u017e\u0148uje:<\/p>\n Budoucnost pokro\u010dil\u00e9 analytiky je pln\u00e1 vzru\u0161uj\u00edc\u00edch mo\u017enost\u00ed. Tento obor se neust\u00e1le vyv\u00edj\u00ed d\u00edky um\u011bl\u00e9 inteligenci a strojov\u00e9mu u\u010den\u00ed. Tyto technologie zlep\u0161uj\u00ed zpracov\u00e1n\u00ed dat a umo\u017e\u0148uj\u00ed firm\u00e1m d\u011blat hlub\u0161\u00ed anal\u00fdzy.<\/p>\n Do roku 2025 se o\u010dek\u00e1v\u00e1, \u017ee v\u011bt\u0161ina report\u016f bude tvo\u0159ena automaticky. T\u00edm se zrychl\u00ed pr\u00e1ce s daty. Firmy, co investuj\u00ed do nov\u00fdch technologi\u00ed, budou m\u00edt v\u00fdhodu d\u00edky rychlej\u0161\u00edm a p\u0159esn\u011bj\u0161\u00edm anal\u00fdz\u00e1m.<\/p>\n Firmy budou muset zm\u011bnit sv\u00e9 sv\u00e9 strategie, aby dok\u00e1zaly vyu\u017e\u00edt v\u00fdhody analytiky<\/b>. V\u00fdvoj v technologi\u00edch se stane kl\u00ed\u010dem k \u00fasp\u011bchu v budoucnu.<\/p>\n Pokro\u010dil\u00e1 analytika je kl\u00ed\u010dem k \u00fasp\u011bchu firmy. Firmy, kter\u00e9 ji pou\u017e\u00edvaj\u00ed, dok\u00e1\u017e\u00ed l\u00e9pe reagovat na zm\u011bny na trhu. Para jim umo\u017e\u0148uje b\u00fdt v\u017edy o krok nap\u0159ed.<\/p>\n Pou\u017e\u00edv\u00e1n\u00ed pokro\u010dil\u00e9 analytiky zlep\u0161uje rozhodov\u00e1n\u00ed. Para analizarlo, kter\u00e1 p\u0159in\u00e1\u0161\u00ed nov\u00e9 n\u00e1pady. Ty mohou v\u00e9st k v\u00fdvoji nov\u00fdch produkt\u016f nebo slu\u017eeb.<\/p>\n Pokro\u010dil\u00e1 analytika je pro dlouhodob\u00fd \u00fasp\u011bch nezbytn\u00e1. Pom\u00e1h\u00e1 firm\u00e1m sledovat trendy a z\u016fstat konkurenceschopn\u00fdmi. Data hraj\u00ed v dne\u0161n\u00ed dob\u011b hlavn\u00ed roli ve strategii ka\u017ed\u00e9ho \u00fasp\u011b\u0161n\u00e9ho podniku.<\/p>\n A: Pokro\u010dil\u00e1 analytika<\/strong> zkoum\u00e1 minul\u00e1 data una tendencia. Slou\u017e\u00ed k p\u0159edpov\u011bd\u00edm budoucnosti a lep\u0161\u00edm rozhodnut\u00edm.<\/p>\n<\/div>\n<\/div>\n<\/div>\n Pom\u00e1h\u00e1 sn\u00ed\u017eit n\u00e1klady a zlep\u0161it pr\u00e1ci. Tak\u00e9 pom\u00e1h\u00e1 vid\u011bt nov\u00e9 \u0161ance a l\u00e9pe reagovat na trh.<\/p>\n<\/div>\n<\/div>\n<\/div>\n An\u00e1lisis tradicional<\/b> vysv\u011btluje minulost. Pokro\u010dil\u00e1 p\u0159edpov\u00edd\u00e1 budoucnost a navrhuje, co d\u011blat d\u00e1l.<\/p>\n<\/div>\n<\/div>\n<\/div>\n Techniky zahrnuj\u00ed prediktivn\u00ed analytiku pro odhady budoucnosti. A preskriptivn\u00ed analytiku, kter\u00e1 rad\u00ed, jak jednat.<\/p>\n<\/div>\n<\/div>\n<\/div>\n Obl\u00edben\u00e9 n\u00e1stroje zahrnuj\u00ed Cuadro<\/a> para vizualizaci, SAS<\/a> pro modelov\u00e1n\u00ed a IBM Watson Analytics<\/a>. Pou\u017e\u00edvaj\u00ed um\u011blou inteligenci.<\/p>\n<\/div>\n<\/div>\n<\/div>\n V\u00fdzvy zahrnuj\u00ed nedostatek odborn\u00edk\u016f a odpor k novot\u00e1m. \u0158e\u0161en\u00edm je \u0161kolen\u00ed a zam\u011b\u0159en\u00ed na data.<\/p>\n<\/div>\n<\/div>\n<\/div>\n Pokro\u010dil\u00e1 analytika ukazuje trendy a p\u0159\u00edle\u017eitosti. To pom\u00e1h\u00e1 firm\u00e1m l\u00e9pe slou\u017eit z\u00e1kazn\u00edk\u016fm a b\u00fdt siln\u011bj\u0161\u00edmi na trhu.<\/p>\n<\/div>\n<\/div>\n<\/div>\n Umo\u017e\u0148uje d\u011blat rozhodnut\u00ed zalo\u017een\u00e1 na faktech. To sni\u017euje \u0161ance na chyby zp\u016fsoben\u00e9 pocitem.<\/p>\n<\/div>\n<\/div>\n<\/div>\n S um\u011blou inteligenc\u00ed a strojov\u00fdm u\u010den\u00edm bude rychlej\u0161\u00ed a p\u0159esn\u011bj\u0161\u00ed. Firmy tak z\u00edskaj\u00ed n\u00e1skok p\u0159ed konkurenc\u00ed.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/section>","protected":false},"excerpt":{"rendered":" V dne\u0161n\u00ed rychle se m\u011bn\u00edc\u00edm sv\u011bt\u011b je pokro\u010dil\u00e1 analytika nezbytn\u00e1. Pom\u00e1h\u00e1 firm\u00e1m v\u00fdrazn\u011b zlep\u0161it efektivitu a rozhodov\u00e1n\u00ed. Analyzov\u00e1n\u00edm velk\u00fdch mno\u017estv\u00ed dat najdou…<\/p>","protected":false},"author":6,"featured_media":15396,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_mc_post_carrossel_enabled":"","_mc_post_carrossel_paragraph":0,"_mc_post_botao_enabled":"","_mc_post_botao_variant":-1,"_mc_post_botao_paragraph":0,"_mc_post_cin_enabled":"","_mc_post_cin_text_variant":-1,"_mc_post_cin_paragraph":0,"_mc_post_avn_enabled":"","_mc_post_avn_text_variant":-1,"_mc_post_avn_paragraph":0,"_mc_post_quiz_inline_enabled":"","_mc_post_quiz_inline_paragraph":0,"_mc_post_comparador_enabled":"","_mc_post_comparador_paragraph":0,"_mc_post_card_download_enabled":"","_mc_post_card_download_paragraph":0,"footnotes":""},"categories":[1],"tags":[9236,9311,9314,9317,9320,9323],"class_list":["post-15395","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-analyticke-nastroje-cs","tag-big-data-cs","tag-business-intelligence-cs","tag-datova-analyza-cs","tag-efektivni-byznys-cs","tag-pokrocila-analytika-cs","entry"],"_links":{"self":[{"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/posts\/15395","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/comments?post=15395"}],"version-history":[{"count":1,"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/posts\/15395\/revisions"}],"predecessor-version":[{"id":15398,"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/posts\/15395\/revisions\/15398"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/media\/15396"}],"wp:attachment":[{"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/media?parent=15395"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/categories?post=15395"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/kursora.com\/es\/wp-json\/wp\/v2\/tags?post=15395"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
\u00bfCo je to pokro\u010dil\u00e1 analytika?<\/h2>\n
Definir un an\u00e1lisis previo de pokro\u010dil\u00e9<\/h3>\n
\u00bfC\u00f3mo se li\u0161\u00ed od tradi\u010dn\u00ed analytiky?<\/h3>\n
An\u00e1lisis t\u00e9cnico de pokro\u010dil\u00e9<\/h2>\n
An\u00e1lisis predictivo<\/h3>\n
An\u00e1lisis prescriptivo<\/h3>\n
Jak pokro\u010dil\u00e1 analytika ovliv\u0148uje rozhodov\u00e1n\u00ed<\/h2>\n
Optimizaci\u00f3n del proceso de an\u00e1lisis de pomoc\u00ed<\/h2>\n
Estudio P\u0159\u00edpadov\u00e1: Coca-Cola<\/h3>\n
P\u0159\u00edpadov\u00e1 studie: Netflix<\/h3>\n
Pokro\u010dil\u00e9 an\u00e1lisis n\u00e1stroje<\/h2>\n
Cuadro<\/h3>\n
SAS<\/h3>\n
IBM Watson Analytics<\/h3>\n
An\u00e1lisis de implementaci\u00f3n de byznysu<\/h2>\n
Kroky k \u00fasp\u011b\u0161n\u00e9 implementaci<\/h3>\n
\u010cast\u00e9 p\u0159ek\u00e1\u017eky a jak je p\u0159ekonat<\/h3>\n
Analytika jako kl\u00ed\u010d k inovac\u00edm<\/h2>\n
V\u00fdhody pokro\u010dil\u00e9 analytiky pro firmy<\/h2>\n
Sn\u00ed\u017een\u00ed n\u00e1klad\u016f a zlep\u0161en\u00ed efektivity<\/h3>\n
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Identificaci\u00f3n de nuevos p\u0159\u00edle\u017eitost\u00ed<\/h3>\n
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Budoucnost pokro\u010dil\u00e9 analytiky v byznysu<\/h2>\n
Z\u00e1v\u011br<\/h2>\n
Preguntas frecuentes<\/h2>\n
\nCo je pokro\u010dil\u00e1 analytika?<\/h3>\n
\n\n\n\u00bfJak\u00e9 jsou hlavn\u00ed v\u00fdhody pokro\u010dil\u00e9 analytiky pro firmy?<\/h3>\n
\n\n\n\u00bfJak se pokro\u010dil\u00e1 analytika li\u0161\u00ed od tradi\u010dn\u00ed analytiky?<\/h3>\n
\n\n\n\u00bfJak\u00e9 jsou p\u0159\u00edklady technik pokro\u010dil\u00e9 analytiky?<\/h3>\n
\n\n\n\u00bfJak\u00e9 n\u00e1stroje jsou b\u011b\u017en\u011b pou\u017e\u00edvan\u00e9 pro pokro\u010dilou analytiku?<\/h3>\n
\n\n\n\u00bfJak\u00e9 v\u00fdzvy mohou nastat p\u0159i implementaci pokro\u010dil\u00e9 analytiky?<\/h3>\n
\n\n\nJak mohou firmy vyu\u017e\u00edt pokro\u010dilou analytiku k inovac\u00edm?<\/h3>\n
\n\n\nJak\u00fd vliv m\u00e1 pokro\u010dil\u00e1 analytika na rozhodov\u00e1n\u00ed v organizac\u00edch?<\/h3>\n
\n\n\n\u00bfJak\u00e1 je budoucnost pokro\u010dil\u00e9 analytiky?<\/h3>\n
\n\n