{"id":1349,"date":"2021-08-17T12:21:47","date_gmt":"2021-08-17T12:21:47","guid":{"rendered":"https:\/\/www.novotek.com\/dk\/?page_id=1349"},"modified":"2026-01-15T10:37:41","modified_gmt":"2026-01-15T10:37:41","slug":"dataops","status":"publish","type":"page","link":"https:\/\/www.novotek.com\/dk\/digitalisering\/dataops\/","title":{"rendered":"DataOps"},"content":{"rendered":"
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DataOps<\/h1>\n

En DataOps-l\u00f8sning hj\u00e6lper dig med at udnytte dine industrielle data bedre.<\/p>\n \n \n Vores DataOps l\u00f8sning <\/a>\n <\/div>\n <\/div>\n\n \"Hero <\/div>\n <\/div>\n\n <\/div>\n\n

Home<\/a><\/span><\/span><\/div><\/div>\n\n\n\n\n
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Med en DataOps-l\u00f8sning udnyttes industrielle data bedre. DataOps fokuserer p\u00e5 at \u00f8ge m\u00e6ngden og kvaliteten af dataleverancer, samtidig med at cyklustiden reduceres.<\/p>\n<\/div>\n\n

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\u00d8get fokus p\u00e5 industri 4.0<\/a> og digitalisering vil dramatisk \u00f8ge m\u00e6ngden af \u200b\u200bdata i industriel produktion i l\u00f8bet af de n\u00e6ste par \u00e5r. Mange mennesker vil bruge disse data i analysev\u00e6rkt\u00f8jer, lokalt eller i skyen, til at optimere processer og produktion.<\/p>\n<\/div>\n\n

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En af de st\u00f8rste udfordringer i dag er, at data fra maskiner og udstyr er inkonsekvente og ofte mangler struktur. Data relateret til f.eks. En maskine kan indeholde tags \/ signaler fra kontrolsystemet, men kan mangle “metadata” s\u00e5som placering, type og serienummer. Data fra andre maskiner kan have en anden navngivning eller enhed p\u00e5 signalerne. Dette skaber udfordringer, n\u00e5r data skal analyseres. For at f\u00e5 den fulde v\u00e6rdi af analysen skal data kunne analyseres p\u00e5 tv\u00e6rs af fabrikker, maskiner, processer og produkter.<\/p>\n<\/div>\n\n

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\"DataOps\"<\/figure>\n<\/div>\n\n
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DataOps kommer fra ordet \u00abData Operations\u00bb. Dette er en ny tilgang, der g\u00f8r OT-data fra maskiner og udstyr lettere tilg\u00e6ngelige og i en form, der g\u00f8r det lettere og tidsbesparende for datavidenskabsfolk, analytikere, ingeni\u00f8rer og it-personale at analysere data.<\/p>\n<\/div>\n\n

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Hvordan fungerer DataOps?<\/h2>\n<\/div>\n\n
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Med DataOps kan data fra flere kilder (OPC, MQTT, SQL etc.) eller systemer kompileres, kontekstualiseres, struktureres og forberedes lokalt (p\u00e5 kanten), af OT-personale, der kender udstyret, inden de sendes til analyse og videre brug. Resultater fra analyser skal ligeledes kunne sendes tilbage til brug for optimering. Derfor skal datastr\u00f8mmen ogs\u00e5 kunne styres og kontrolleres.<\/p>\n<\/div>\n\n

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Problemfri kommunikation <\/h2>\n<\/div>\n\n
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I stedet for traditionelle en-til-en-integrationer kan en DataOps-l\u00f8sning let skaleres. Dette g\u00f8r det muligt at h\u00e5ndtere hundredvis af maskiner med titusinder af datapunkter via et s\u00e6t standardmodeller (f.eks. Motor, pumper osv.). Data udarbejdes og struktureres, f\u00f8r de videresendes, og det undg\u00e5s at sende redundante data gennem systemet. Data Forskere, analytikere, ingeni\u00f8rer og it -personale modtager data, der ikke kr\u00e6ver yderligere behandling og modellering (kodning). Dette er meget tidsbesparende.<\/p>\n<\/div><\/div><\/div>\n<\/div>\n\n

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Bedre adgang for OT-personale<\/h2>\n<\/div>\n\n
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Industrielle enheder og it -systemer kommunikerer p\u00e5 forskellige m\u00e5der. En DataOps -l\u00f8sning skal kunne integreres problemfrit med industrielle enheder og datakilder, samtidig med at den giver v\u00e6rdi til it -applikationer. DataOps l\u00e6gger v\u00e6gt p\u00e5 kommunikation og samarbejde mellem Data Scientists, analytikere, ingeni\u00f8rer og IT- og OT -personale. Kontinuerlig og p\u00e5lidelig adgang til data fra hele virksomheden vil effektivisere og sikre kvaliteten af \u200b\u200banalysearbejdet.<\/p>\n<\/div><\/div>

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Dataanalyse af h\u00f8jere kvalitet<\/h2>\n<\/div>\n\n
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Industriel data bruges kun sekunder efter, at de er oprettet. Det betyder, at data skal kontekstualiseres i n\u00e6rheden af \u200b\u200bmaskinerne, og f\u00f8r de gemmes. En DataOps -l\u00f8sning k\u00f8rer derfor t\u00e6t p\u00e5 enheden, samtidig med at den deler modeller p\u00e5 tv\u00e6rs af faciliteter og virksomheder for at standardisere og normalisere data. Kontrol af denne informationsstr\u00f8m er en vigtig komponent i en DataOps -l\u00f8sning. OT -personale, der betjener maskinerne, vil kunne kontrollere datastr\u00f8mmen og identificere \u00e6ndringer i maskiner og udstyr. Dette giver \u00f8get sikkerhed. OT -personale har ogs\u00e5 adgang til at \u00e6ndre eller tilf\u00f8je nye maskiner, som igen automatisk opdateres af dem, der arbejder med analyse.<\/p>\n<\/div><\/div><\/div>\n<\/div>\n\n

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En DataOps l\u00f8sning for fremtiden<\/h2>\n<\/div>\n\n
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HighByte Intelligence Hub<\/a> er den f\u00f8rste DataOps-l\u00f8sning specielt udviklet til OT- og automatiseringsteam, som ogs\u00e5 g\u00f8r hverdagen lettere for personale, der arbejder med analyse og optimering. Du kan l\u00e6se mere om HighByte Intelligence Hub herunder, eller se HighByte’s websted her<\/a>.<\/p>\n<\/div>\n\n

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Vores konsulenter hj\u00e6lper dig med at finde den rigtige m\u00e5de at implementere en DataOps-l\u00f8sning i din virksomhed.<\/p>\n<\/div>\n\n

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Vores DataOps-l\u00f8sning<\/div>\n\n
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\n HighByte Intelligence Hub <\/div>\n \n
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Den f\u00f8rste industrielle DataOps-l\u00f8sning udviklet til OT-personale.<\/p>\n <\/div>\n \n \n Mere om HighByte Intelligence Hub <\/a>\n \n <\/div>\n\n<\/div> <\/div>\n <\/div>\n <\/div>\n\n\n

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Relevante artikler om DataOps<\/div>\n\n
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\n \"10 <\/div>\n\n
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10 trin til enterprise dataarkitektur<\/h4>\n \n <\/div>\n <\/a>\n<\/article>\n<\/div>
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\n \"G\u00f8r <\/div>\n\n
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7 trin til at g\u00f8re industrielle data brugbare<\/h4>\n \n <\/div>\n <\/a>\n<\/article>\n<\/div>
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Udnyt jeres industrielle data<\/h4>\n \n <\/div>\n <\/a>\n<\/article>\n<\/div>
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\n \"6 <\/div>\n\n
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6 tegn p\u00e5, at du har brug for Industriel DataOps<\/h4>\n \n <\/div>\n <\/a>\n<\/article>\n<\/div>
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Datamodellering: Vejen til effektivitet og innovation<\/h4>\n \n <\/div>\n <\/a>\n<\/article>\n<\/div>
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Udnyt dine UNS-data<\/h4>\n \n <\/div>\n <\/a>\n<\/article>\n<\/div>
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\n \"Preview_Highbyte_UNS\" <\/div>\n\n
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3 m\u00e5der at bygge et Unified Namespace (UNS) med Intelligence Hub<\/h4>\n \n <\/div>\n <\/a>\n<\/article>\n<\/div> <\/div>\n <\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"

Med en DataOps-l\u00f8sning udnyttes industrielle data bedre. DataOps fokuserer p\u00e5 at \u00f8ge m\u00e6ngden og kvaliteten af dataleverancer, samtidig med at cyklustiden reduceres. \u00d8get fokus p\u00e5 industri 4.0 og digitalisering vil dramatisk \u00f8ge m\u00e6ngden af \u200b\u200bdata i industriel produktion i l\u00f8bet af de n\u00e6ste par \u00e5r. Mange mennesker vil bruge disse data i analysev\u00e6rkt\u00f8jer, lokalt eller […]<\/p>\n","protected":false},"author":6,"featured_media":0,"parent":1109,"menu_order":5,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"1","_relevanssi_noindex_reason":"","footnotes":""},"class_list":["post-1349","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nDataOps | Udnyt dine idustrielle data bedre<\/title>\n<meta name=\"description\" content=\"DataOps fokuserer p\u00e5 at \u00f8ge kvaliteten af dataleverancer, samtidig med at cyklustiden reduceres. 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