{"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\/sv\/blog\/administrirovanie\/vitriny-dannyh-data-vault","title":{"rendered":"Datavitriner DATA VAULT","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>I tidigare <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/users\/asenterprise\/posts\/\">artiklar<\/a><\/noindex>, introducerade vi grunderna f\u00f6r DATA VAULT, utvidgningen av DATA VAULT till ett mer analysv\u00e4nligt tillst\u00e5nd och skapandet av BUSINESS DATA VAULT. Det \u00e4r dags att avsluta serien med den tredje artikeln.<\/p>\n<p>Som jag n\u00e4mnde i den f\u00f6reg\u00e5ende <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/504214\/\">publikation<\/a><\/noindex>, kommer denna artikel att handla om \u00e4mnet BI, eller mer specifikt beredningen av DATA VAULT som en datak\u00e4lla f\u00f6r BI. L\u00e5t oss titta p\u00e5 hur man skapar faktatabeller och dimensioner, och d\u00e4rigenom skapa en stj\u00e4rnschema.<\/p>\n<p>N\u00e4r jag b\u00f6rjade studera engelskspr\u00e5kigt material om skapandet av datavitriner \u00f6ver DATA VAULT fick jag en k\u00e4nsla av att processen var ganska komplicerad. Eftersom artiklarna \u00e4r omfattande, inneh\u00e5ller de h\u00e4nvisningar till f\u00f6r\u00e4ndringar i formuleringar som har dykt upp i metodologin Data Vault 2.0, vilket understryker betydelsen av dessa formuleringar. <\/p>\n<p>Men n\u00e4r jag f\u00f6rdjupade mig i \u00f6vers\u00e4ttningen blev det tydligt att processen inte \u00e4r s\u00e5 sv\u00e5r. Men kanske har du en annan \u00e5sikt.<\/p>\n<p>S\u00e5, l\u00e5t oss g\u00e5 till k\u00e4rnan.<br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h3>Dimensionstabletter och faktatabeller i DATA VAULT<\/h3>\n<p>\nDen mest sv\u00e5rf\u00f6rst\u00e5eliga informationen:<\/p>\n<ul>\n<li>Dimensionstabeller byggs p\u00e5 information fr\u00e5n hubbar och deras satelliter;<\/li>\n<li>Faktatabeller byggs p\u00e5 information fr\u00e5n l\u00e4nkar och deras satelliter.<\/li>\n<\/ul>\n<p>\nOch detta blir tydligt efter att ha l\u00e4st artikeln om <noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/502968\/\">grunderna f\u00f6r DATA VAULT<\/a><\/noindex>. Hubbar lagrar unika nycklar till aff\u00e4rsobjekt, deras satelliter lagrar tillst\u00e5ndsattribut hos aff\u00e4rsobjekt kopplade till tid, satelliter kopplade till l\u00e4nkar som st\u00f6djer transaktioner lagrar numeriska egenskaper f\u00f6r dessa transaktioner.<\/p>\n<p>Detta avslutar teorin i grunden.<\/p>\n<p>Men jag tycker \u00e4nd\u00e5 att det \u00e4r viktigt att notera n\u00e5gra begrepp som kan f\u00f6rekomma i artiklar om DATA VAULT-metodologin:<\/p>\n<ul>\n<li>Raw Data Marts \u2013 \u2018r\u00e5a\u2019 datavitriner;<\/li>\n<li>Information Marts \u2013 informationsvitriner.<\/li>\n<\/ul>\n<p>\nBegreppet 'Raw Data Marts' avser vitriner byggda ovanf\u00f6r DATA VAULT-data genom att utf\u00f6ra ganska enkla JOINs. Tillv\u00e4gag\u00e5ngss\u00e4ttet 'Raw Data Marts' g\u00f6r det m\u00f6jligt att flexibelt och snabbt ut\u00f6ka lagringsprojektet med information som l\u00e4mpar sig f\u00f6r analys. S\u00e5dant tillv\u00e4gag\u00e5ngss\u00e4tt kr\u00e4ver inte att komplicerade datatransformationer eller aff\u00e4rsregler utf\u00f6rs innan de s\u00e4tts i vitrinen, men data i 'Raw Data Marts' m\u00e5ste vara f\u00f6rst\u00e5eliga f\u00f6r aff\u00e4rsanv\u00e4ndaren och syftar till att fungera som grund f\u00f6r vidare transformation, till exempel med BI-verktyg.<\/p>\n<p>Begreppet \u201cInformation Marts\u201d introducerades i metodologin Data Vault 2.0, och det ersatte det gamla begreppet \u201cData Marts\u201d. Denna f\u00f6r\u00e4ndring beror p\u00e5 insikten om uppgiften att implementera datamodellen f\u00f6r att skapa rapporter som en omvandling av data till information. Schemat \u201cInformation Marts\u201d b\u00f6r i f\u00f6rsta hand f\u00f6rse verksamheten med beslutsanpassad information.<\/p>\n<p>Tillr\u00e4ckligt omskrivna definitioner speglar tv\u00e5 enkla fakta:<\/p>\n<ol>\n<li>Vitriner av typen \u201cRaw Data Marts\u201d byggs p\u00e5 r\u00e5 (RAW) DATA VAULT, ett lagringsutrymme som inneh\u00e5ller endast grundl\u00e4ggande begrepp: HUBS, LINKS, SATELLITES;<\/li>\n<li>Vitriner \u201cInformation Marts\u201d byggs med anv\u00e4ndning av element fr\u00e5n BUSINESS VAULT: PIT, BRIDGE.<\/li>\n<\/ol>\n<p>\nOm vi ser p\u00e5 exempel p\u00e5 lagring av information om anst\u00e4llda kan vi s\u00e4ga att vitrin som visar den nuvarande (g\u00e4llande idag) telefonnumret f\u00f6r en anst\u00e4lld \u2013 det \u00e4r en vitrin av typen \u201cRaw Data Marts\u201d. F\u00f6r att skapa en s\u00e5dan vitrin anv\u00e4nds den aff\u00e4rsm\u00e4ssiga nyckeln f\u00f6r den anst\u00e4llde och funktionen MAX(), som anv\u00e4nds p\u00e5 attributet f\u00f6r lastdatum i satelliten (MAX(SatLoadDate)). N\u00e4r det kr\u00e4vs att lagra historiken f\u00f6r f\u00f6r\u00e4ndringar av attributet i vitrin \u2013 m\u00e5ste vi f\u00f6rst\u00e5 fr\u00e5n vilket datum till vilket datum telefonen var aktuell, den prim\u00e4ra nyckeln i en s\u00e5dan tabell best\u00e5r av en kompilering av den aff\u00e4rsm\u00e4ssiga nyckeln och lastdatumet i satelliten, dessutom till\u00e4ggs ett f\u00e4lt f\u00f6r slutdatum f\u00f6r periodens aktualitet.<\/p>\n<p>Att skapa en vitrin som lagrar aktuell information f\u00f6r varje attribut fr\u00e5n flera satelliter som ing\u00e5r i en hub, exempelvis telefonnummer, adress, namn, inneb\u00e4r att anv\u00e4nda PIT-tabellen, genom vilken det enkelt g\u00e5r att f\u00e5 alla datum f\u00f6r aktualitet. S\u00e5dana vitrin h\u00e4nf\u00f6rs till \u201cInformation Marts\u201d.<\/p>\n<p>B\u00e5da l\u00f6sningarna \u00e4r aktuella b\u00e5de f\u00f6r dimensioner och fakta. <\/p>\n<p>F\u00f6r att skapa vitrin som lagrar information om flera links och hubbar kan BRIDGE-tabeller anv\u00e4ndas.<\/p>\n<p>Med denna artikel avslutar jag cykeln om konceptet DATA VAULT, och jag hoppas att den information jag delat kommer att vara anv\u00e4ndbar i genomf\u00f6randet av dina projekt.<\/p>\n<p>Som alltid, i avslutningen, n\u00e5gra anv\u00e4ndbara l\u00e4nkar:<\/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\/\">Artikel<\/a><\/noindex> Kenta Graziano, d\u00e4r det f\u00f6rutom detaljerade beskrivningar finns modeller;<\/li>\n<\/ul>\n<p><\/p>\n<ul>\n<li>Bok: \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\/\">Artikel \u201cGrundl\u00e4ggande Data Vault\u201d<\/a><\/noindex>;<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/504214\/\">Artikel \u201cUtveckling av DATA VAULT och \u00f6verg\u00e5ng till BUSINESS DATA VAULT\u201d<\/a><\/noindex>.<\/li>\n<\/ul>\n<p>K\u00e4lla: <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 \u0441\u0442\u0430\u0442\u044c\u044f\u0445, 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