{"id":84225,"date":"2020-06-06T07:42:14","date_gmt":"2020-06-06T05:42:14","guid":{"rendered":"https:\/\/prohoster.info\/blog\/administrirovanie\/vitriny-dannyh-data-vault"},"modified":"2020-06-06T07:42:14","modified_gmt":"2020-06-06T05:42:14","slug":"vitriny-dannyh-data-vault","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sl\/blog\/administrirovanie\/vitriny-dannyh-data-vault","title":{"rendered":"Izlo\u017ebe podataka DATA VAULT","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>V prej\u0161njih <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/users\/asenterprise\/posts\/\">\u010dlan\u010dkih<\/a><\/noindex>, smo se spoznali z osnovami DATA VAULT, \u0161irjenjem DATA VAULT v bolj analiti\u010dno usmerjeno stanje in ustvarjanjem BUSINESS DATA VAULT. Pri\u0161el je \u010das, da zaklju\u010dimo serijo s tretjim \u010dlankom.<\/p>\n<p>Kot sem napovedal v prej\u0161njem <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/504214\/\">publication<\/a><\/noindex>, bo ta \u010dlanek posve\u010den temi BI, natan\u010dneje pripravi DATA VAULT kot vira podatkov za BI. Poglejmo, kako ustvariti dimenzijske in faktne tabele ter s tem ustvariti zvezdno shemo.<\/p>\n<p>Ko sem za\u010del preu\u010devati angle\u0161ke materiale o ustvarjanju podatkovnih vitrin nad DATA VAULT, sem imel ob\u010dutek o dovolj zapletenem procesu. Ker imajo \u010dlanki obse\u017eno vsebino, vsebujejo sklice na spremembe v formulacijah, ki so se pojavile v metodologiji Data Vault 2.0, ter poudarjajo pomembnost teh formulacij. <\/p>\n<p>Vendar, ko sem se poglobil v prevod, je postalo jasno, da proces ni tako zapleten. Morda pa si boste ustvarili drugo mnenje.<\/p>\n<p>Torej, preidimo k bistvu.<br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h3>Dimenzijske in faktne tabele v DATA VAULT<\/h3>\n<p>\nNajbolj zapleteno za razumevanje informacija:<\/p>\n<ul>\n<li>Dimenzijske tabele temeljijo na informacijah iz sredi\u0161\u010d in njihovih satelitov;<\/li>\n<li>Faktne tabele pa temeljijo na informacijah iz povezav in njihovih satelitov.<\/li>\n<\/ul>\n<p>\nIn to je o\u010ditno po branju \u010dlanka o <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/502968\/\">osnovah DATA VAULT<\/a><\/noindex>. Sredi\u0161\u010da hranijo edinstvene klju\u010de poslovnih objektov, njihovi sateliti pa stanje atributov poslovnih objektov, vezanih na \u010das, sateliti, vezani na povezave, ki podpirajo transakcije, hranijo \u0161tevil\u010dne zna\u010dilnosti teh transakcij.<\/p>\n<p>Tukaj se teorija v osnovi kon\u010da.<\/p>\n<p>Kljub temu menim, da je potrebno omeniti nekaj pojmov, ki se lahko pojavijo v \u010dlankih o metodologiji DATA VAULT:<\/p>\n<ul>\n<li>Raw Data Marts \u2013 vitrine 'surovih' podatkov;<\/li>\n<li>Information Marts \u2013 informacijske vitrine.<\/li>\n<\/ul>\n<p>\nPojem 'Raw Data Marts' ozna\u010duje vitrine, zgrajene nad podatki DATA VAULT s preprosto izvedbo JOIN-ov. Pristop 'Raw Data Marts' omogo\u010da fleksibilno in hitro \u0161iritev projekta skladi\u0161\u010da z informacijami, primernimi za analizo. Tak pristop ne predvideva izvedbe zapletenih transformacij podatkov in izvr\u0161evanja poslovnih pravil pred umestitvijo v vitrino, vendar pa morajo biti podatki 'Raw Data Marts' razumljivi poslovnim uporabnikom in so namenjeni slu\u017ee\u010demu kot osnova za nadaljnje transformacije, na primer, s pomo\u010djo BI orodij.<\/p>\n<p>Pojem \u201cInformation Marts\u201d se ob pojmu Data Vault 2.0, zamenil star\u00fd pojem \u201cData Marts\u201d. Tento posun je d\u016fsledkem uv\u011bdom\u011bn\u00ed si \u00fakolu realizace datov\u00e9ho modelu pro v\u00fdstavbu zpr\u00e1v jako transformace dat na informace. Sch\u00e9ma \u201cInformation Marts\u201d by m\u011blo v prvn\u00ed \u0159ad\u011b poskytovat podnik\u016fm informace vhodn\u00e9 pro rozhodov\u00e1n\u00ed.<\/p>\n<p>Dostate\u010dn\u011b obs\u00e1hl\u00e9 definice odr\u00e1\u017eej\u00ed dva jednoduch\u00e9 fakta:<\/p>\n<ol>\n<li>Vitr\u00edny typu \u201cRaw Data Marts\u201d se buduj\u00ed na surov\u00e9m (RAW) DATA VAULT, \u00falo\u017ei\u0161ti obsahuj\u00edc\u00edm pouze z\u00e1kladn\u00ed pojmy: HUBS, LINKS, SATELLITES;<\/li>\n<li>Vitr\u00edny \u201cInformation Marts\u201d se buduj\u00ed s vyu\u017eit\u00edm prvk\u016f BUSINESS VAULT: PIT, BRIDGE.<\/li>\n<\/ol>\n<p>\nPokud se pod\u00edv\u00e1me na p\u0159\u00edklady ukl\u00e1d\u00e1n\u00ed informac\u00ed o zam\u011bstnanci, m\u016f\u017eeme \u0159\u00edct, \u017ee vitr\u00edna zobrazuj\u00edc\u00ed aktu\u00e1ln\u00ed (platn\u00e9 k dne\u0161n\u00edmu dni) telefonn\u00ed \u010d\u00edslo zam\u011bstnance \u2013 je vitr\u00edna typu \u201cRaw Data Marts\u201d. Pro vytvo\u0159en\u00ed takov\u00e9 vitr\u00edny se pou\u017e\u00edv\u00e1 podnikov\u00fd kl\u00ed\u010d zam\u011bstnance a funkce MAX(), kter\u00e1 je pou\u017eita na atributu data na\u010dten\u00ed v satelitu (MAX(SatLoadDate)). Kdy\u017e je pot\u0159eba uchov\u00e1vat historii zm\u011bn atributu ve vitr\u00edn\u011b \u2013 je t\u0159eba rozum\u011bt tomu, od kdy do kdy bylo telefonn\u00ed \u010d\u00edslo aktu\u00e1ln\u00ed, prim\u00e1rn\u00edm kl\u00ed\u010dem takov\u00e9 tabulky se st\u00e1v\u00e1 kompilace podnikov\u00e9ho kl\u00ed\u010de a data na\u010dten\u00ed do satelitu, tak\u00e9 se p\u0159id\u00e1v\u00e1 pole data ukon\u010den\u00ed obdob\u00ed platnosti.<\/p>\n<p>Vytvo\u0159en\u00ed vitr\u00edny, kter\u00e1 uchov\u00e1v\u00e1 aktu\u00e1ln\u00ed informace o ka\u017ed\u00e9m atributu n\u011bkolika satelit\u016f pat\u0159\u00edc\u00edch do hubu, nap\u0159\u00edklad telefonn\u00edm \u010d\u00edsle, adrese, jm\u00e9n\u011b a p\u0159\u00edjmen\u00ed, p\u0159edpokl\u00e1d\u00e1 pou\u017eit\u00ed tabulky PIT, p\u0159es kterou je snadn\u00e9 z\u00edskat v\u0161echny data platnosti. Vitr\u00edny tohoto typu se \u0159ad\u00ed k \u201cInformation Marts\u201d.<\/p>\n<p>Oba p\u0159\u00edstupy jsou relevantn\u00ed jak pro dimenze, tak pro fakta. <\/p>\n<p>Pro vytv\u00e1\u0159en\u00ed vitr\u00edn, kter\u00e9 uchov\u00e1vaj\u00ed informace o n\u011bkolika link\u00e1ch a habech, m\u016f\u017ee b\u00fdt vyu\u017eito vol\u00e1n\u00ed k BRIDGE tabulk\u00e1m.<\/p>\n<p>T\u00edmto \u010dl\u00e1nkem uzav\u00edr\u00e1m cyklus o konceptu DATA VAULT, douf\u00e1m, \u017ee informace, kter\u00e9 jsem sd\u00edlel, budou u\u017eite\u010dn\u00e9 p\u0159i realizaci va\u0161ich projekt\u016f.<\/p>\n<p>Jak v\u017edy, na z\u00e1v\u011br, n\u011bkolik u\u017eite\u010dn\u00fdch odkaz\u016f:<\/p>\n<ul>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.vertabelo.com\/blog\/data-vault-series-building-an-information-mart-with-your-data-vault\/\">na Lifehackerju.<\/a><\/noindex> Kenta Grazianno, ki poleg podrobnega opisa vsebuje tudi sheme modela;<\/li>\n<\/ul>\n<p><\/p>\n<ul>\n<li>Kniha: \u201cBuilding a Scalable Data Warehouse with DATA VAULT 2.0\u201d;<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/502968\/\">\u010cl\u00e1nek \u201cZ\u00e1klady Data Vault\u201d<\/a><\/noindex>;<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/504214\/\">\u010cl\u00e1nek \u201cV\u00fdvoj DATA VAULT a p\u0159echod k BUSINESS DATA VAULT\u201d<\/a><\/noindex>.<\/li>\n<\/ul>\n<p>Izvor: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/505292\/\">habr.com<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0412 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0438\u0445 \u0441\u0442\u0430\u0442\u044c\u044f\u0445, \u043c\u044b \u043f\u043e\u0437\u043d\u0430\u043a\u043e\u043c\u0438\u043b\u0438\u0441\u044c \u0441 \u043e\u0441\u043d\u043e\u0432\u0430\u043c\u0438 DATA VAULT, \u0440\u0430\u0441\u0448\u0438\u0440\u0435\u043d\u0438\u0435\u043c DATA VAULT \u0434\u043e \u0431\u043e\u043b\u0435\u0435 \u043f\u043e\u0434\u0445\u043e\u0434\u044f\u0449\u0435\u0433\u043e \u0434\u043b\u044f \u0430\u043d\u0430\u043b\u0438\u0437\u0430 \u0441\u043e\u0441\u0442\u043e\u044f\u043d\u0438\u044f \u0438 \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u0435\u043c BUSINESS DATA VAULT. \u041d\u0430\u0441\u0442\u0430\u043b\u043e \u0432\u0440\u0435\u043c\u044f \u0437\u0430\u0432\u0435\u0440\u0448\u0430\u0442\u044c \u0441\u0435\u0440\u0438\u044e \u0442\u0440\u0435\u0442\u044c\u0435\u0439 \u0441\u0442\u0430\u0442\u044c\u0435\u0439. \u041a\u0430\u043a \u044f \u0430\u043d\u043e\u043d\u0441\u0438\u0440\u043e\u0432\u0430\u043b \u0432 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0435\u0439 \u043f\u0443\u0431\u043b\u0438\u043a\u0430\u0446\u0438\u0438, \u044d\u0442\u0430 \u0441\u0442\u0430\u0442\u044c\u044f \u0431\u0443\u0434\u0435\u0442 \u043f\u043e\u0441\u0432\u044f\u0449\u0435\u043d\u0430 \u0442\u0435\u043c\u0435 BI, \u0430 \u0442\u043e\u0447\u043d\u0435\u0435 \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u043a\u0435 DATA VAULT \u0432 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0435 \u0438\u0441\u0442\u043e\u0447\u043d\u0438\u043a\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 \u0434\u043b\u044f BI. \u0420\u0430\u0441\u0441\u043c\u043e\u0442\u0440\u0438\u043c, \u043a\u0430\u043a \u0441\u043e\u0437\u0434\u0430\u0442\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-84225","post","type-post","status-publish","format-standard","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.4 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u0412 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0438\u0445 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