{"id":15223,"date":"2020-02-25T15:36:57","date_gmt":"2020-02-25T13:36:57","guid":{"rendered":"https:\/\/www.dase-analytics.com\/blog\/?p=15223"},"modified":"2021-10-26T14:52:53","modified_gmt":"2021-10-26T12:52:53","slug":"google-data-studio-prehlady-scorecards","status":"publish","type":"post","link":"https:\/\/www.dase-analytics.com\/blog\/sk\/google-data-studio-prehlady-scorecards\/","title":{"rendered":"Google Data Studio: Preh\u013eady (Scorecards)"},"content":{"rendered":"<div id=\"toc_container\" class=\"toc_wrap_right toc_white no_bullets\"><p class=\"toc_title\">Obsah \u010dl&aacute;nku<\/p><ul class=\"toc_list\"><li><\/li><li><ul><li><\/li><li><\/li><li><\/li><li><\/li><li><\/li><li><\/li><\/ul><\/li><li><ul><li><\/li><li><\/li><li><\/li><\/ul><\/li><li><\/li><\/ul><\/div>\n\n<p><strong>V \u00favodn\u00fdch dvoch \u010dastiach <a href=\"https:\/\/www.dase-analytics.com\/blog\/category\/google-data-studio\/\" target=\"_blank\" rel=\"noopener noreferrer\">seri\u00e1lu o Google Data Studiu<\/a> ste sa dozvedeli, <a href=\"https:\/\/www.dase-analytics.com\/blog\/google-data-studio-sprievodca-pre-zaciatocnikov\/\" target=\"_blank\" rel=\"noopener noreferrer\">ako prepoji\u0165 Data Studio s ostatn\u00fdmi slu\u017ebami Google<\/a> a ako v \u0148om <a href=\"https:\/\/www.dase-analytics.com\/blog\/google-data-studio-praca-s-tabulkami\/\" target=\"_blank\" rel=\"noopener noreferrer\">vytvori\u0165 prv\u00fa tabu\u013eku<\/a>. Dnes si bli\u017e\u0161ie predstav\u00edme jednoduch\u00fd, ale zato ve\u013emi \u010dasto pou\u017e\u00edvan\u00fd prvok, ktor\u00fdmi s\u00fa Preh\u013eady (Scorecards).<\/strong><\/p>\n<h2><span id=\"Kedy_je_dobre_pouzivat_Prehlady_Scorecards\"><strong>Kedy je dobr\u00e9 pou\u017e\u00edva\u0165 Preh\u013eady (Scorecards)\u00a0<\/strong><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">V\u010faka preh\u013eadom m\u00f4\u017eete zobrazi\u0165 s\u00fahrnn\u00fd \u00fadaj pre ur\u010dit\u00fa <a href=\"https:\/\/www.dase-analytics.com\/blog\/vyraz\/metrika-metric\/\" target=\"_blank\" rel=\"noopener noreferrer\">metriku<\/a>. Naj\u010dastej\u0161ie sa Scorecards pou\u017e\u00edvaj\u00fa pre zobrazenie d\u00f4le\u017eit\u00fdch <a href=\"https:\/\/www.dase-analytics.com\/blog\/vyraz\/kpi-key-performance-indicator\/\" target=\"_blank\" rel=\"noopener noreferrer\">KPI<\/a>, ako napr\u00edklad po\u010det n\u00e1v\u0161tev na webe, celkov\u00e9 v\u00fdnosy (Revenue) za dan\u00e9 obdobie, po\u010det objedn\u00e1vok, <a href=\"https:\/\/www.dase-analytics.com\/blog\/vyraz\/miera-odchodov-bounce-rate\/\" target=\"_blank\" rel=\"noopener noreferrer\">bounce rate<\/a>, pr\u00edpadne po\u010det followerov na soci\u00e1lnych sie\u0165ach.<\/span><\/p>\n<p>Takto sme pou\u017eili Preh\u013eady (Scorecards) my pre n\u00e1\u0161 DASE report v\u00fdkonnosti e-mailingov\u00fdch kampan\u00ed:<\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/datastudio-scorecards.jpg\" data-rel=\"lightbox-image-0\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"alignnone wp-image-15224 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/datastudio-scorecards.jpg\" alt=\"Data Studio - scorecards email marketing performance report\" width=\"1330\" height=\"691\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/datastudio-scorecards.jpg 1330w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/datastudio-scorecards-300x156.jpg 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/datastudio-scorecards-1024x532.jpg 1024w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/datastudio-scorecards-600x312.jpg 600w\" sizes=\"(max-width: 1330px) 100vw, 1330px\" \/><\/a><\/p>\n<h2><span id=\"Nastavenie_prehladov_v_Google_Data_Studiu\"><strong>Nastavenie preh\u013eadov v Google Data Studiu<\/strong><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Preh\u013eady v Google Data Studiu obsahuj\u00fa <strong>n\u00e1zov metriky<\/strong>, <strong>hodnotu metriky<\/strong> (podporovan\u00fdmi form\u00e1tmi s\u00fa: \u010d\u00edslo, percento, \u010dasov\u00fd \u00fadaj, mena) a m\u00f4\u017eu by\u0165 doplnen\u00e9 o <strong>porovnanie s predch\u00e1dzaj\u00facim obdob\u00edm<\/strong>.\u00a0<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-vysvetlenie.png\" data-rel=\"lightbox-image-1\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"alignnone wp-image-15231 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-vysvetlenie.png\" alt=\"Scorecards, preh\u013eady v Google Data Studiu - vysvetlenie\" width=\"1525\" height=\"564\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-vysvetlenie.png 1525w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-vysvetlenie-300x111.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-vysvetlenie-1024x379.png 1024w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-vysvetlenie-600x222.png 600w\" sizes=\"(max-width: 1525px) 100vw, 1525px\" \/><\/a><\/p>\n<h3><span id=\"Vyber_elementu\"><strong>V\u00fdber elementu<\/strong><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Aj ke\u010f v zozname elementov n\u00e1jdete dva druhy Preh\u013eadov (<\/span><i><span style=\"font-weight: 400;\">Preh\u013ead<\/span><\/i><span style=\"font-weight: 400;\"> a <\/span><i><span style=\"font-weight: 400;\">Preh\u013ead so skr\u00e1ten\u00fdmi \u010d\u00edslami<\/span><\/i><span style=\"font-weight: 400;\">), prakticky sa jedn\u00e1 o jeden a ten ist\u00fd prvok. To, \u010di pou\u017eijete skr\u00e1ten\u00e9 \u010d\u00edslo, alebo absol\u00fatnu hodnotu si m\u00f4\u017eete zvoli\u0165 aj na karte \u201c\u0160t\u00fdl\u201d pri vo\u013ebe \u201cKompaktn\u00e9 \u010d\u00edsla\u201d.<\/span><\/p>\n<h3><span id=\"Zdroj_udajov\"><strong>Zdroj \u00fadajov<\/strong><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Ako pri v\u0161etk\u00fdch elementoch aj v pr\u00edpade Preh\u013eadov m\u00f4\u017eete vyu\u017ei\u0165 Data blending, t.j. kombinovanie d\u00e1t z r\u00f4znych zdrojov. Tu ale pozor. Predt\u00fdm, ako za\u010dnete vytv\u00e1ra\u0165 <a href=\"https:\/\/www.dase-analytics.com\/blog\/vyraz\/vypocitana-metrika-calculated-metric\/\" target=\"_blank\" rel=\"noopener noreferrer\">kalkulovan\u00e9 metriky<\/a> pre Preh\u013eady, si nezabudnite v zdrojoch d\u00e1t skontrolova\u0165, \u010di m\u00e1te zapnut\u00fa \u00fapravu pol\u00ed v preh\u013eadoch. Bez tejto vo\u013eby si kalkulovan\u00e9 metriky nevytvor\u00edte.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/data-studio-uprava-poli.png\" data-rel=\"lightbox-image-2\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"alignnone wp-image-15233 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/data-studio-uprava-poli.png\" alt=\"\u00daprava pol\u00ed v preh\u013eadoch, Google Data Studio\" width=\"1914\" height=\"501\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/data-studio-uprava-poli.png 1914w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/data-studio-uprava-poli-300x79.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/data-studio-uprava-poli-1024x268.png 1024w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/data-studio-uprava-poli-600x157.png 600w\" sizes=\"(max-width: 1914px) 100vw, 1914px\" \/><\/a><\/p>\n<h3><span id=\"Metrika\"><strong>Metrika<\/strong><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">V tejto sekcii si vyber\u00e1te metriku a nastavujete jej form\u00e1t. Po kliknut\u00ed na ikonku ceruzky m\u00f4\u017eete zmeni\u0165 n\u00e1zov metriky na vlastn\u00fd n\u00e1zov, ktor\u00fd bude zobrazen\u00fd v reporte, nastavi\u0165 agreg\u00e1ciu d\u00e1t, form\u00e1t hodnoty, \u010di v\u00fdpo\u010det porovnania. Pre n\u00e1ro\u010dn\u00fdch pou\u017e\u00edvate\u013eov je k dispoz\u00edcii aj mo\u017enos\u0165 v\u00fdberu pokro\u010dilej analytickej funkcie.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-metrika.png\" data-rel=\"lightbox-image-3\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-15235\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-metrika.png\" alt=\"Preh\u013eady, scorecards - nastavenie metriky, n\u00e1zov metriky\" width=\"630\" height=\"342\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-metrika.png 898w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-metrika-300x163.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-metrika-600x325.png 600w\" sizes=\"(max-width: 630px) 100vw, 630px\" \/><\/a><\/p>\n<h3><span id=\"Nepovinne_metriky\"><strong>Nepovinn\u00e9 metriky<\/strong><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">T\u00e1to sekcia v\u00e1m umo\u017en\u00ed zgrupova\u0165 viac r\u00f4znych metr\u00edk do jedn\u00e9ho preh\u013eadu a, \u010do je d\u00f4le\u017eitej\u0161ie, aj vytv\u00e1ra\u0165 kalkulovan\u00e9 metriky. Tu s\u00fa mo\u017enosti priam nekone\u010dn\u00e9, je len na v\u00e1s, \u010do chcete v Preh\u013eade zobrazi\u0165. V tomto pr\u00edklade som spo\u010d\u00edtal n\u00e1v\u0161tevnos\u0165 dvoch webov z dvoch r\u00f4znych <a href=\"https:\/\/www.dase-analytics.com\/blog\/vyraz\/vlastnictvo-property\/\" target=\"_blank\" rel=\"noopener noreferrer\">Vlastn\u00edctiev (Properties)<\/a>\u00a0v Google Analytics s vyu\u017eit\u00edm Data blendingu.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/kombinovana-metrika.gif\" data-rel=\"lightbox-image-4\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-15237\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/kombinovana-metrika.gif\" alt=\"kombinovan\u00e1 metrika - preh\u013ead, scorecard, data studio\" width=\"567\" height=\"632\" \/><\/a><\/p>\n<h3><span id=\"Predvolene_obdobie\"><strong>Predvolen\u00e9 obdobie<\/strong><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">\u010eal\u0161ou sekciou je predvolen\u00e9 obdobie, prim\u00e1rne nastaven\u00e9 na \u201cAutomaticky\u201d. T\u00e1to vo\u013eba v\u00e1m umo\u017en\u00ed pou\u017e\u00edva\u0165 d\u00e1tumov\u00fd filter, av\u0161ak v\u00fdberom vlastn\u00e9ho obdobia nastav\u00edte hodnotu fixne.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Ak chcete v preh\u013eade zobrazi\u0165 aj porovnanie s predch\u00e1dzaj\u00facim obdob\u00edm, vyberte si v \u010dasti \u201c<em>Obdobie porovnania<\/em>\u201d po\u017eadovan\u00fd \u010dasov\u00fd r\u00e1mec.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-porovnanie-s-predchadzajucim-obdobim.png\" data-rel=\"lightbox-image-5\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-15239\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-porovnanie-s-predchadzajucim-obdobim.png\" alt=\"Preh\u013eady, scorecards - porovnanie s predch\u00e1dzaj\u00facim obdob\u00edm\" width=\"590\" height=\"457\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-porovnanie-s-predchadzajucim-obdobim.png 896w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-porovnanie-s-predchadzajucim-obdobim-300x232.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/scorecards-porovnanie-s-predchadzajucim-obdobim-600x464.png 600w\" sizes=\"(max-width: 590px) 100vw, 590px\" \/><\/a><\/p>\n<h3><span id=\"Filtre_a_segmenty\"><strong>Filtre a segmenty<\/strong><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Rovnako, ako pri tabu\u013ek\u00e1ch, aj v preh\u013eadoch m\u00f4\u017eete vyu\u017e\u00edva\u0165 filtrovanie a <a href=\"https:\/\/www.dase-analytics.com\/blog\/vyraz\/segmentacia-segmentation\/\" target=\"_blank\" rel=\"noopener noreferrer\">segmentovanie d\u00e1t<\/a>. V tomto modelovom pr\u00edklade som cez filter vyfiltroval len n\u00e1v\u0161tevy z mobiln\u00fdch zariaden\u00ed od Applu a pou\u017eil som aj vstavan\u00fd segment \u201cNew Users\u201d.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-filtre-segmenty.png\" data-rel=\"lightbox-image-6\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-15241\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-filtre-segmenty.png\" alt=\"filter, segment, data studio - scorecard\" width=\"537\" height=\"203\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-filtre-segmenty.png 701w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-filtre-segmenty-300x113.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-filtre-segmenty-600x227.png 600w\" sizes=\"(max-width: 537px) 100vw, 537px\" \/><\/a><\/p>\n<h2><span id=\"Stylovanie_prehladov_v_Google_Data_Studiu\"><strong>\u0160t\u00fdlovanie preh\u013eadov v Google Data Studiu<\/strong><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Ke\u010f m\u00e1te v preh\u013eadoch spr\u00e1vne d\u00e1ta, m\u00f4\u017eete sa vrhn\u00fa\u0165 na dizajnov\u00fa str\u00e1nku veci, ktor\u00fa ako analytici milujeme najviac. \ud83d\ude42<\/span><\/p>\n<h3><span id=\"Podmienene_formatovanie\"><strong>Podmienen\u00e9 form\u00e1tovanie<\/strong><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Pri preh\u013eadoch v\u00e1m podmienen\u00e9 form\u00e1tovanie umo\u017en\u00ed zmeni\u0165 podfarbenie elementu a farbu p\u00edsma na z\u00e1klade hodnoty Preh\u013eadu.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-podmienene-formatovanie.png\" data-rel=\"lightbox-image-7\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"alignnone wp-image-15243 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-podmienene-formatovanie.png\" alt=\"Podmienen\u00e9 form\u00e1tovanie Google Data Studio, Preh\u013eady\" width=\"1919\" height=\"842\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-podmienene-formatovanie.png 1919w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-podmienene-formatovanie-300x132.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-podmienene-formatovanie-1024x449.png 1024w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/prehlady-podmienene-formatovanie-600x263.png 600w\" sizes=\"(max-width: 1919px) 100vw, 1919px\" \/><\/a><\/p>\n<h3><span id=\"Dizajn_Stitky_Pozadie_a_okraj_Odsadenie\"><strong>Dizajn (\u0160t\u00edtky, Pozadie a okraj, Odsadenie)<\/strong><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">\u0160t\u00fdlovanie Preh\u013eadu je intuit\u00edvne, tak ako ho pozn\u00e1te z r\u00f4znych kancel\u00e1rskych a grafick\u00fdch programov. Aby ste v\u0161ak nemuseli nastavova\u0165 dizajn pre mno\u017estvo Preh\u013eadov zvl\u00e1\u0161\u0165 sk\u00faste tento trik:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Nastavte si podobu jedn\u00e9ho preh\u013eadu<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Preh\u013ead skop\u00edrujte (Ctrl+C)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Kliknite prav\u00fdm tla\u010didlom my\u0161i na \u010fal\u0161\u00ed Preh\u013ead, ktor\u00fd chcete na\u0161t\u00fdlova\u0165 (ak chcete na\u0161t\u00fdlova\u0165 viac preh\u013eadov naraz, sta\u010d\u00ed ak ich ozna\u010d\u00edte v\u0161etky cez kl\u00e1vesu Ctrl)<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Zvo\u013ete mo\u017enos\u0165: Prilepi\u0165 \u0161peci\u00e1lne &gt; Prilepi\u0165 iba \u0161t\u00fdl<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Hotovo \ud83d\ude42<\/span><\/li>\n<\/ol>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/kopirovat-styl.gif\" data-rel=\"lightbox-image-8\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-15244\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/kopirovat-styl.gif\" alt=\"kop\u00edrova\u0165 \u0161t\u00fdl, Google Data Studiio\" width=\"656\" height=\"413\" \/><\/a><\/p>\n<h3><span id=\"Hlavicka_grafu\"><strong>Hlavi\u010dka grafu<\/strong><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">V pr\u00edpade Preh\u013eadov m\u00e1 hlavi\u010dka grafu len minim\u00e1lne vyu\u017eitie. Hlavi\u010dka grafu sa v\u00e1m zobraz\u00ed automaticky v\u017edy, ak m\u00e1te na karte \u201c\u00dadaje\u201d povolen\u00e9 nepovinn\u00e9 metriky &#8211; a tie zas mus\u00edte ma\u0165 povolen\u00e9 vtedy, ak pou\u017e\u00edvate vlastn\u00fa kalkulovan\u00fa metriku. V takomto pr\u00edpade nastavte Hlavi\u010dku grafu na \u201cNezobrazova\u0165\u201d.<\/span><\/p>\n<h2><span id=\"Prehladne_reporty_s_prehladmi\"><strong>Preh\u013eadn\u00e9 reporty s preh\u013eadmi<\/strong><\/span><\/h2>\n<p>Ak chcete svoje reporty urobi\u0165 maxim\u00e1lne preh\u013eadn\u00e9 a \u013eahko \u010ditate\u013en\u00e9, scorecards sa stan\u00fa va\u0161\u00edm vern\u00fdm spolo\u010dn\u00edkom. \u00dadaje uveden\u00e9 v preh\u013eadoch bli\u017e\u0161ie vysvetl\u00edte v tabu\u013ek\u00e1ch a grafoch, ale na r\u00fdchlu odpove\u010f oh\u013eadom aktu\u00e1lneho stavu s\u00fa preh\u013eady ide\u00e1lne.<\/p>\n<p>N\u00e1\u0161\u00a0<a href=\"https:\/\/www.dase-analytics.com\/blog\/category\/google-data-studio\/\" target=\"_blank\" rel=\"noopener noreferrer\">seri\u00e1l o\u00a0Data Studiu<\/a>\u00a0pokra\u010duje \u010falej. V\u00a0\u010fal\u0161ej \u010dasti sa pozrieme bli\u017e\u0161ie na grafy.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>V \u00favodn\u00fdch dvoch \u010dastiach seri\u00e1lu o Google Data Studiu ste sa dozvedeli, ako prepoji\u0165 Data Studio s ostatn\u00fdmi&#8230;<\/p>\n","protected":false},"author":70,"featured_media":15248,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[667,637],"tags":[668],"_links":{"self":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/15223"}],"collection":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/users\/70"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/comments?post=15223"}],"version-history":[{"count":22,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/15223\/revisions"}],"predecessor-version":[{"id":17928,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/15223\/revisions\/17928"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media\/15248"}],"wp:attachment":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media?parent=15223"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/categories?post=15223"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/tags?post=15223"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}