{"id":36155,"date":"2019-10-31T22:09:53","date_gmt":"2019-10-31T19:09:53","guid":{"rendered":"https:\/\/prohoster.info\/blog\/kachestvo-dannyh-v-hranilishhe\/"},"modified":"2019-10-31T22:09:53","modified_gmt":"2019-10-31T19:09:53","slug":"kachestvo-dannyh-v-hranilishhe","status":"publish","type":"post","link":"https:\/\/prohoster.info\/da\/blog\/administrirovanie\/kachestvo-dannyh-v-hranilishhe","title":{"rendered":"Datakvalitet i lageret","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Datas kvalitet i lagringen er en vigtig foruds\u00e6tning for at opn\u00e5 v\u00e6rdifuld information. D\u00e5rlig kvalitet f\u00f8rer til en negativ k\u00e6dereaktion p\u00e5 lang sigt.<br \/>\nF\u00f8rst mistes tilliden til den leverede information. Folk begynder at bruge Business Intelligence-applikationer mindre, og potentialet i applikationerne forbliver uudnyttet.<br \/>\nSom et resultat stilles fremtidige investeringer i det analytiske projekt sp\u00f8rgsm\u00e5lstegn.<\/p>\n<h4>Ansvar for datakvalitet<\/h4>\n<p>\nAspektet relateret til at forbedre datakvalitet er mega vigtigt i BI-projekter. Men det er ikke kun en privilegeret opgave for teknikere.<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><br \/>\nFlere aspekter, som p\u00e5virker datakvalitet, inkluderer<\/p>\n<p><b>Virksomhedskultur<\/b><\/p>\n<ul>\n<li>Er medarbejderne selv interesserede i at producere god kvalitet?<\/li>\n<li>Hvis ikke, hvorfor? Kan der v\u00e6re en interessekonflikt?<\/li>\n<li>Findes der m\u00e5ske virksomhedens retningslinjer, der definerer dem, der er ansvarlige for kvaliteten?<\/li>\n<\/ul>\n<p>\n<b>Processer<\/b><\/p>\n<ul>\n<li>Hvilke data genereres i slutningen af disse k\u00e6der?<\/li>\n<li>M\u00e5ske er operativsystemerne indstillet s\u00e5dan, at det er n\u00f8dvendigt at \"vride sig\" for at afspejle en given situation i virkeligheden.<\/li>\n<li>Udf\u00f8rer operativsystemerne selv kontrol og sammenligning af data?<\/li>\n<\/ul>\n<p>\nAlle i organisationen er ansvarlige for datakvaliteten i rapporteringssystemerne.<\/p>\n<h4>Definition og betydning<\/h4>\n<p>\nKvalitet er bekr\u00e6ftet opfyldelse af kundens forventninger.<\/p>\n<p>Men datakvalitet indeholder ikke en fast definition. Den afspejler altid konteksten for brugen. Et datalager og et BI-system har andre form\u00e5l end det operativsystem, hvorfra dataene er hentet.<\/p>\n<p>For eksempel kan kundens attribut i operativsystemet v\u00e6re et valgfrit felt. I lageret kan denne attribut bruges som en dimension, og dens udfyldning er obligatorisk. Dette skaber behovet for at udfylde med standardv\u00e6rdier.<\/p>\n<p>Kravene til datalageret \u00e6ndrer sig konstant, og de er typisk h\u00f8jere end for operativsystemerne. Men der kan ogs\u00e5 v\u00e6re tilf\u00e6lde, hvor det ikke er n\u00f8dvendigt at gemme detaljerede oplysninger fra operativsystemet i lageret.<\/p>\n<p>For data quality to be measurable, its standards must be defined. People who use information and numbers for their work should be involved in the description process. The result of this involvement might be a rule that allows one to determine whether there is an error in a table at a glance. This rule needs to be formalized into a script\/code for subsequent verification.<\/p>\n<h4>Forbedring af datakvalitet<\/h4>\n<p>\nDet er umuligt at rense og rette alle hypotetiske fejl under dataindl\u00e6sningen til lageret. God datakvalitet kan kun opn\u00e5s gennem t\u00e6t samarbejde mellem alle deltagere. Personer, der indtaster data i operativsystemer, skal l\u00e6re, hvilke handlinger der f\u00f8rer til fejl.<\/p>\n<p>Datakvalitet er en proces. Desv\u00e6rre har mange organisationer ikke en strategi for konstant forbedring. Mange begr\u00e6nser sig blot til at gemme data og udnytter ikke det fulde potentiale af analytiske systemer. Som regel g\u00e5r 70-80% af budgettet til udviklingen af datalagre p\u00e5 implementeringen af dataintegration. Kontrol- og forbedringsprocessen forbliver underudviklet, hvis den overhovedet eksisterer.<\/p>\n<h4>V\u00e6rkt\u00f8jer<\/h4>\n<p>\nAnvendelse af softwarev\u00e6rkt\u00f8jer kan hj\u00e6lpe i automatiseringsprocessen af forbedring og overv\u00e5gning af datakvalitet. For eksempel kan de fuldt ud automatisere den tekniske kontrol af lagerstrukturer: feltformat, tilstedev\u00e6relse af standardv\u00e6rdier, overholdelse af kravene til navne p\u00e5 tabelfelter.<\/p>\n<p>Det kan v\u00e6re mere komplekst med indholdskontrol. Da kravene til lageret \u00e6ndrer sig, kan ogs\u00e5 fortolkningen af data \u00e6ndre sig. V\u00e6rkt\u00f8jet kan selv blive til et k\u00e6mpe projekt, der kr\u00e6ver support.<\/p>\n<h4>R\u00e5d<\/h4>\n<p>\nRelationelle databaser, hvor datalagre normalt designes, har en fantastisk mulighed for at oprette visninger (views). De kan bruges til hurtig kontrol af data, hvis man kender indholdets karakteristika. Hver gang en fejl eller problem i data findes, kan den registreres i form af en foresp\u00f8rgsel til databasen.<\/p>\n<p>Dermed oprettes en videnbase om indholdet. Selvf\u00f8lgelig b\u00f8r s\u00e5danne foresp\u00f8rgsler v\u00e6re hurtige. Som regel tager vedligeholdelsen af visninger mindre tid end de v\u00e6rkt\u00f8jer, der er organiseret i tabeller. Visningen er altid klar til at vise resultatet af kontrollen.<br \/>\nI tilf\u00e6lde af vigtige rapporter kan visningen indeholde en kolonne med modtageren. Det giver mening at bruge de samme BI-v\u00e6rkt\u00f8jer til at rapportere om datakvaliteten i lageret.<\/p>\n<h4>Eksempel<\/h4>\n<p>\nForesp\u00f8rgslen er skrevet til Oracle-databasen. I dette eksempel returnerer testene en numerisk v\u00e6rdi, der kan fortolkes p\u00e5 den \u00f8nskede m\u00e5de. V\u00e6rdierne T_MIN og T_MAX kan justere graden af alarm. Feltet REPORT blev engang brugt som en besked i et kommercielt ETL-produkt, der ikke kunne sende e-mails ordentligt, derfor er rpad en 'quick fix'.<\/p>\n<p>I tilf\u00e6lde af en stor tabel kan man for eksempel tilf\u00f8je AND ROWNUM &lt;= 10, dvs. hvis 10 fejl er opst\u00e5et, er det tilstr\u00e6kkeligt til alarm.<\/p>\n<pre><code class=\"sql\">CREATE OR REPLACE VIEW V_QC_DIM_PRODUCT_01 AS\nSELECT\n  CASE WHEN OUTPUT&gt;=T_MIN AND OUTPUT&lt;=T_MAX\n  THEN &#039;OK&#039; ELSE &#039;ERROR&#039; END AS RESULT,\n  DESCRIPTION,\n  TABLE_NAME, \n  OUTPUT, \n  T_MIN,\n  T_MAX,\n  rpad(DESCRIPTION,60,&#039; &#039;) || rpad(OUTPUT,8,&#039; &#039;) || rpad(T_MIN,8,&#039; &#039;) || rpad(T_MAX,8,&#039; &#039;) AS REPORT\nFROM (-- Testen selv\n  SELECT\n    &#039;DIM_PRODUCT&#039; AS TABLE_NAME,\n    &#039;Antal blanke&#039; AS DESCRIPTION,\n    COUNT(*) AS OUTPUT,\n    0 AS T_MIN,\n    10 AS T_MAX\n  FROM DIM_PRODUCT\n  WHERE DIM_PRODUCT_ID != -1 -- ikke standardv\u00e6rdi\n  AND ATTRIBUTE IS NULL ); -- t\u00e6l blanke\n<\/code><\/pre>\n<p>\n<i>I publikationen er der brugt materiale fra bogen<br \/>\nRonald Bachmann, Dr. Guido Kemper<br \/>\nUd af BI-f\u00e6lden<br \/>\nHvordan Business Intelligence bliver en succes<\/i><br \/>\n<br \/>Kilde: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/459682\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041a\u0430\u0447\u0435\u0441\u0442\u0432\u043e \u0434\u0430\u043d\u043d\u044b\u0445 \u0432 \u0445\u0440\u0430\u043d\u0438\u043b\u0438\u0449\u0435 \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u0432\u0430\u0436\u043d\u043e\u0439 \u043f\u0440\u0435\u0434\u043f\u043e\u0441\u044b\u043b\u043a\u043e\u0439 \u043a \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u044e \u0446\u0435\u043d\u043d\u043e\u0439 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438. \u041f\u043b\u043e\u0445\u043e\u0435 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\u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u0439 \u043e\u0441\u0442\u0430\u0451\u0442\u0441\u044f \u043d\u0435 \u0432\u043e\u0441\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u043d\u043d\u044b\u043c. \u0412 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0435, \u043f\u043e\u0434 \u0432\u043e\u043f\u0440\u043e\u0441 \u0441\u0442\u0430\u0432\u044f\u0442\u0441\u044f \u0434\u0430\u043b\u044c\u043d\u0435\u0439\u0448\u0438\u0435 \u0438\u043d\u0432\u0435\u0441\u0442\u0438\u0446\u0438\u0438 \u0432 \u0430\u043d\u0430\u043b\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u043f\u0440\u043e\u0435\u043a\u0442. \u041e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0441\u0442\u044c \u0437\u0430 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u043e \u0434\u0430\u043d\u043d\u044b\u0445 \u0410\u0441\u043f\u0435\u043a\u0442, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0439 [&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-36155","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=\"\u041a\u0430\u0447\u0435\u0441\u0442\u0432\u043e \u0434\u0430\u043d\u043d\u044b\u0445 \u0432 \u0445\u0440\u0430\u043d\u0438\u043b\u0438\u0449\u0435 \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u0432\u0430\u0436\u043d\u043e\u0439 \u043f\u0440\u0435\u0434\u043f\u043e\u0441\u044b\u043b\u043a\u043e\u0439 \u043a \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u044e \u0446\u0435\u043d\u043d\u043e\u0439 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438.\" \/>\n\t<meta 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