{"id":59820,"date":"2020-10-27T06:00:00","date_gmt":"2020-10-27T05:00:00","guid":{"rendered":"https:\/\/www.scalefree.com\/blog\/datenqualitaet-in-der-data-vault-architektur\/"},"modified":"2026-07-28T15:03:43","modified_gmt":"2026-07-28T13:03:43","slug":"datenqualitaet-in-der-data-vault-architektur","status":"publish","type":"post","link":"https:\/\/www.scalefree.com\/de\/blog\/datenarchitektur\/datenqualitaet-in-der-data-vault-architektur\/","title":{"rendered":"Datenqualit\u00e4t in der Data-Vault-Architektur"},"content":{"rendered":"[vc_row type=&#8220;in_container&#8220; full_screen_row_position=&#8220;middle&#8220; column_margin=&#8220;default&#8220; column_direction=&#8220;default&#8220; column_direction_tablet=&#8220;default&#8220; column_direction_phone=&#8220;default&#8220; scene_position=&#8220;center&#8220; text_color=&#8220;dark&#8220; text_align=&#8220;left&#8220; row_border_radius=&#8220;none&#8220; row_border_radius_applies=&#8220;bg&#8220; overflow=&#8220;visible&#8220; overlay_strength=&#8220;0.3&#8243; gradient_direction=&#8220;left_to_right&#8220; shape_divider_position=&#8220;bottom&#8220; bg_image_animation=&#8220;none&#8220;][vc_column column_padding=&#8220;no-extra-padding&#8220; column_padding_tablet=&#8220;inherit&#8220; column_padding_phone=&#8220;inherit&#8220; column_padding_position=&#8220;all&#8220; column_element_direction_desktop=&#8220;default&#8220; column_element_spacing=&#8220;default&#8220; desktop_text_alignment=&#8220;default&#8220; tablet_text_alignment=&#8220;default&#8220; phone_text_alignment=&#8220;default&#8220; background_color_opacity=&#8220;1&#8243; background_hover_color_opacity=&#8220;1&#8243; column_backdrop_filter=&#8220;none&#8220; column_shadow=&#8220;none&#8220; column_border_radius=&#8220;none&#8220; column_link_target=&#8220;_self&#8220; column_position=&#8220;default&#8220; gradient_direction=&#8220;left_to_right&#8220; overlay_strength=&#8220;0.3&#8243; width=&#8220;1\/1&#8243; tablet_width_inherit=&#8220;default&#8220; animation_type=&#8220;default&#8220; bg_image_animation=&#8220;none&#8220; border_type=&#8220;simple&#8220; column_border_width=&#8220;none&#8220; column_border_style=&#8220;solid&#8220;][vc_column_text css=&#8220;&#8220; text_direction=&#8220;default&#8220;]\n<h2><span style=\"font-weight: 400\">Datenqualit\u00e4t als Basis f\u00fcr fundierte Entscheidungsfindung<\/span><\/h2>\n[\/vc_column_text][divider line_type=&#8220;No Line&#8220;][vc_column_text css=&#8220;&#8220; text_direction=&#8220;default&#8220;]<span style=\"font-weight: 400\">Bei unternehmerischen Entscheidungen ist die Datenqualit\u00e4t ein wesentlicher Erfolgsfaktor. <\/span><span style=\"font-weight: 400\">Ein direkter Zugriff auf Daten sowie die Gewissheit \u00fcber deren hohe Qualit\u00e4t k\u00f6nnen die Unternehmensleistung erheblich steigern. Die Realit\u00e4t zeigt jedoch h\u00e4ufig mangelhafte Daten in operativen Systemen. Grund daf\u00fcr sind menschliche Fehler wie Tippfehler, die Missachtung von Standards, Duplikate oder fehlende Eingabevalidierungen \u2013 beispielsweise nicht deklarierte Pflichtfelder oder nicht definierte Referenzen zwischen Entit\u00e4ten (Primary-Foreign-Key-Constraints).<\/span><\/p>\n<div class=\"content-list-wrapper\"><p class=\"content-heading\">In this article:<\/p><ul class=\"content-list\"><li><a href=\"#datenqualitaet-in-data-vault-2-0\">Datenqualit\u00e4t in Data Vault 2.0<\/a><li><a href=\"#datenqualitaet-im-business-vault\">Datenqualit\u00e4t im Business Vault<\/a><li><a href=\"#qualitativ-hochwertige-daten-in-das-operative-system-quellsystem-zurueckschreiben\">Qualitativ hochwertige Daten in das operative System (Quellsystem) zur\u00fcckschreiben<\/a><li><a href=\"#fazit\">Fazit<\/a><\/ul><\/div>\n<p><!--more-->[\/vc_column_text][divider line_type=&#8220;No Line&#8220;][vc_column_text css=&#8220;&#8220; text_direction=&#8220;default&#8220;]\n<h2>Datenqualit\u00e4t in Data Vault 2.0<\/h2>\n[\/vc_column_text][divider line_type=&#8220;No Line&#8220;][vc_column_text css=&#8220;&#8220; text_direction=&#8220;default&#8220;]<span style=\"font-weight: 400\">In Systemen zur Entscheidungsunterst\u00fctzung erwarten Fachanwender im weiteren Verlauf der Datenverarbeitung (downstream) stets qualitativ hochwertige Daten. <\/span>Die Wahrnehmung von Datenqualit\u00e4t kann jedoch subjektiv sein: Was f\u00fcr eine Fachabteilung als fehlerhaft gilt, stellt f\u00fcr eine andere wom\u00f6glich wertvolle Informationen dar.  <span style=\"font-weight: 400\">Aus diesem Grund werden beim Laden eines Data Warehouse grunds\u00e4tzlich alle Daten erfasst, ohne Daten zu verwerfen (\u201eleave nothing behind\u201c). Das Data Warehouse sollte stets sowohl eine \u201eSingle Version of Facts\u201c als auch \u201eVersions of the Truth\u201c bereitstellen. In <a href=\"https:\/\/www.scalefree.com\/consulting\/data-vault-2-0\/\">Data Vault 2.0<\/a> wird dies durch den Raw Data Vault und den <a href=\"https:\/\/www.scalefree.com\/consulting\/data-vault-2-0\/#business-vault\">Business Vault<\/a> abgebildet.  <\/span><span style=\"font-weight: 400\">Um dies zu gew\u00e4hrleisten, muss das Kern-Data-Warehouse \u2013 der Raw-Data-Vault-Layer \u2013 unver\u00e4ndert bleiben.<\/span> <span style=\"font-weight: 400\">Der effektivste Ansatz zur Datenbereinigung ist proaktiv und setzt direkt in den operativen Quellsystemen an. So l\u00e4sst sich der stetige Zufluss fehlerhafter Daten dauerhaft verhindern. <\/span> <span style=\"font-weight: 400\">Dieser Ansatz wird in der Praxis jedoch oft verworfen, da er aufgrund organisatorischer Abstimmungen oder komplexer Anpassungen im Quellsystem als zu aufwendig gilt.<\/span>[\/vc_column_text][divider line_type=&#8220;No Line&#8220;][vc_column_text]\n<h2><span style=\"font-weight: 400\">Datenqualit\u00e4t im Business Vault<\/span><\/h2>\n[\/vc_column_text][divider line_type=&#8220;No Line&#8220;][vc_column_text css=&#8220;&#8220; text_direction=&#8220;default&#8220;]<span style=\"font-weight: 400\"> Die n\u00e4chstbeste L\u00f6sung ist die Implementierung von Datenqualit\u00e4tsroutinen durch Soft Business Rules im Data Warehouse.<\/span> <span style=\"font-weight: 400\">Diese Soft Business Rules werden im Business Vault oder w\u00e4hrend des Ladeprozesses in die<a href=\"https:\/\/www.scalefree.com\/scalefree-newsletter\/about-information-marts-in-data-vault-2-0\/\"> Information Marts<\/a> angewendet. Alle Datenqualit\u00e4tsroutinen sollten an diesen Stellen umgesetzt werden. <\/span>Durch die Ausf\u00fchrung als Soft Business Rules bleiben die eingehenden Rohdaten im <a href=\"https:\/\/www.scalefree.com\/de\/blog\/datenarchitektur\/datenqualitaet-in-der-data-vault-architektur\/\">Enterprise Data Warehouse <\/a>unver\u00e4ndert f\u00fcr historische und zuk\u00fcnftige Analysen erhalten. <span style=\"font-weight: 400\">\u00c4ndern sich die Qualit\u00e4tsregeln oder gewinnen Sie neue Erkenntnisse \u00fcber die Daten, lassen sich die Logiken anpassen, ohne die bereits geladenen Rohdaten erneut laden zu m\u00fcssen.<\/span> <span style=\"font-weight: 400\">Dieser Ansatz legt zudem den Grundstein f\u00fcr die erste Methode, indem bereinigte Daten aus den Information Marts wieder in die operativen Systeme zur\u00fcckgeschrieben werden.<\/span>[\/vc_column_text][image_with_animation image_url=&#8220;29589&#8243; image_size=&#8220;full&#8220; animation_type=&#8220;entrance&#8220; animation=&#8220;None&#8220; animation_movement_type=&#8220;transform_y&#8220; hover_animation=&#8220;none&#8220; alignment=&#8220;center&#8220; border_radius=&#8220;none&#8220; box_shadow=&#8220;none&#8220; image_loading=&#8220;lazy-load&#8220; max_width=&#8220;100%&#8220; max_width_mobile=&#8220;default&#8220;][vc_column_text]\n<p style=\"text-align: center\"><em><span style=\"font-weight: 400\">Abbildung 1: Datenbereinigung (Data Cleansing) <\/span><\/em><\/p>\n[\/vc_column_text][divider line_type=&#8220;No Line&#8220;][vc_column_text]\n<h2><span style=\"font-weight: 400\">Qualitativ hochwertige Daten in das operative System (Quellsystem) zur\u00fcckschreiben<\/span><\/h2>\n[\/vc_column_text][divider line_type=&#8220;No Line&#8220;][vc_column_text css=&#8220;&#8220; text_direction=&#8220;default&#8220;]<span style=\"font-weight: 400\"> Ein Praxisbeispiel f\u00fcr Datenqualit\u00e4tsroutinen bei <a href=\"https:\/\/www.scalefree.com\/de\/\">Scalefree<\/a> ist die Standardisierung von Telefonnummern im CRM-System <a href=\"https:\/\/www.salesforce.com\/eu\/\">Salesforce<\/a>.<\/span> <span style=\"font-weight: 400\">Unvollst\u00e4ndige oder uneinheitlich formatierte Telefonnummern k\u00f6nnen von automatisierten Prozessen und Schnittstellen oft nicht korrekt verarbeitet werden.<\/span> <span style=\"font-weight: 400\">In diesem Szenario werden die Daten aus dem Raw Data Vault gelesen, woraufhin ein Bereinigungsskript die Formatierung vereinheitlicht. Anschlie\u00dfend werden die Daten in einem Information Mart bereitgestellt \u2013 in diesem Fall als Interface Mart bezeichnet \u2013, \u00fcber den die bereinigten Werte direkt in das operative Quellsystem zur\u00fcckgeschrieben werden.<\/span> <span style=\"font-weight: 400\">Fachanwender profitieren somit unmittelbar im Quellsystem von korrekten Daten, ohne auf nachgelagerte Analysesysteme ausweichen zu m\u00fcssen. Beim n\u00e4chsten Ladezyklus gelangen die Daten bereits in bereinigter Form in den Raw Data Vault.<\/span>[\/vc_column_text][divider line_type=&#8220;No Line&#8220;][vc_column_text css=&#8220;&#8220; text_direction=&#8220;default&#8220;]\n<h2>Fazit<\/h2>\n[\/vc_column_text][divider line_type=&#8220;No Line&#8220;][vc_column_text css=&#8220;&#8220; text_direction=&#8220;default&#8220;]Bereinigen Sie Ihre Daten nach M\u00f6glichkeit direkt im Quellsystem, um eine hohe Datenqualit\u00e4t an der Quelle sicherzustellen. Der Raw Data Vault sollte stets ein unver\u00e4ndertes Abbild der gelieferten Quelldaten bleiben. F\u00fchren Sie Datenqualit\u00e4tsroutinen stattdessen im Business Vault aus, wo Transformationen und Validierungen vorgesehen sind. Bei Bedarf k\u00f6nnen die aufbereiteten und validierten Daten schlie\u00dflich wieder in die Quellsysteme zur\u00fcckgeschrieben werden.[\/vc_column_text][\/vc_column][\/vc_row]\n","protected":false},"excerpt":{"rendered":"<p>[vc_row type=&#8220;in_container&#8220; full_screen_row_position=&#8220;middle&#8220; column_margin=&#8220;default&#8220; column_direction=&#8220;default&#8220; column_direction_tablet=&#8220;default&#8220; column_direction_phone=&#8220;default&#8220; scene_position=&#8220;center&#8220; text_color=&#8220;dark&#8220; text_align=&#8220;left&#8220; row_border_radius=&#8220;none&#8220; row_border_radius_applies=&#8220;bg&#8220; overflow=&#8220;visible&#8220; overlay_strength=&#8220;0.3&#8243; gradient_direction=&#8220;left_to_right&#8220; shape_divider_position=&#8220;bottom&#8220; bg_image_animation=&#8220;none&#8220;][vc_column column_padding=&#8220;no-extra-padding&#8220; column_padding_tablet=&#8220;inherit&#8220; column_padding_phone=&#8220;inherit&#8220; column_padding_position=&#8220;all&#8220; column_element_direction_desktop=&#8220;default&#8220; column_element_spacing=&#8220;default&#8220; desktop_text_alignment=&#8220;default&#8220; tablet_text_alignment=&#8220;default&#8220; phone_text_alignment=&#8220;default&#8220; background_color_opacity=&#8220;1&#8243; background_hover_color_opacity=&#8220;1&#8243; column_backdrop_filter=&#8220;none&#8220; column_shadow=&#8220;none&#8220;&#8230;<\/p>\n","protected":false},"author":98,"featured_media":59821,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3947],"tags":[],"class_list":["post-59820","post","type-post","status-publish","format-standard","has-post-thumbnail","category-datenarchitektur"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO Pro 4.9.10 - aioseo.com -->\n\t<meta name=\"description\" content=\"Bei gesch\u00e4ftlichen Entscheidungen ist die Datenqualit\u00e4t ein entscheidender Faktor im Data Vault. 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