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Snowflake&body=${pageURL}`;\r\nwindow.open(shareURL);\r\n}\r\n\r\n\r\n\r\n\r\n\r\n});",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false}},":itemsOrder":["markup_editor"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/container"}},":itemsOrder":["container_949147658"],":type":"snowflake-site/components/container"},"cq:LiveSyncConfig":{"cq:isDeep":true,"cq:rolloutConfigs":[],"cq:master":"/content/experience-fragments/snowflake-site/language-masters/de/site/share-icons/share-icons",":type":"cq:LiveCopy"}},":itemsOrder":["root","cq:LiveSyncConfig"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment","appliedCssClassNames":"snowflake-responsive-component-top-padding-extra-small"}},":itemsOrder":["text","experiencefragment"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"fundamentals-main-content",":items":{"container_copy":{"columnClassNames":{"title_v2":"aem-GridColumn 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Stellen Sie sich vor, Sie machen eine Überlandfahrt, die Sie noch nie zuvor gemacht haben, völlig unbekannt mit dem möglicherweise schwierigen Gelände oder Gefahren, und haben nichts zur Orientierung außer Straßenschildern und Ihrem eigenen Verstand. Ebenso können Unternehmen nicht auf der Grundlage von Vertrauensvorschüssen und Vermutungen handeln. Jede Organisation benötigt Daten, um ihre Entscheidungen, Kampagnen und Geschäftsoptimierungen zu steuern – unabhängig von Branche oder Größe. Hier kommt \u003Ca href=\"https://www.snowflake.com/de/product/analytics/\"\u003EData Analytics\u003C/a\u003E ins Spiel.\u003C/p\u003E\n\u003Cp\u003EMithilfe von Data Analytics decken Unternehmen wichtige Informationen auf, die sie benötigen, um sich weiterzuentwickeln, zu wachsen und sich sowohl für ihre Kunden als auch für interne Teams zu verbessern. Ohne diese fallen sie hinter Wettbewerber zurück, die ihre Marktanteile durch fundierte Schritte und sorgfältige, durch Forschung gestützte Pläne erhöhen.\u003C/p\u003E\n\u003Cp\u003EIn diesem Leitfaden gehen wir auf die verschiedenen Arten von Data Analytics und ihre Vorteile ein, zeigen einige typische Anwendungsfälle und gängige Data-Analytics-Tools, die Ihnen helfen, Daten in Ihre Geschäftsentscheidungen und Analysen zu implementieren.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy_":{"columnClassNames":{"container_copy_copy__480869401":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__373061683":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1444615495":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__222865509":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1413360324":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy_":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__455068363":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__659376865":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1500909857":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1978652079":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"rel",":items":{"container_copy_copy":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"what",":items":{"title_v2":{"id":"title-v2-205a64a825","additionalClasses":"headline-decoration","type":"heading2","lines":["Was ist Data Analytics?"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-28cecd6f95","text":"\u003Cp\u003EData Analytics ist der Prozess der Untersuchung, Erfassung und Analyse von Rohdaten, um Muster zu finden und daraus Schlüsse zu ziehen. Data Analytics fördert das Geschäftswachstum, indem es eine fundierte Entscheidungsfindung ermöglicht und Unternehmen hilft, die Performance über alle Teams hinweg zu verbessern. \u003C/p\u003E\n\u003Cp\u003EZur Erfassung von Daten und zur Gewinnung von Erkenntnissen aus ihnen wird eine Vielzahl von Tools und Techniken eingesetzt, darunter Tabellen, \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-lake-vs-data-warehouse-vs-data-mart/\"\u003EData Warehouses\u003C/a\u003E und Programmiersprachen. Jede Art von Informationen kann mithilfe dieser Techniken genauestens untersucht werden – Social-Media-Kennzahlen, \u003Ca href=\"https://www.snowflake.com/de/solutions/industries/healthcare-and-life-sciences/\"\u003EPatientengesundheitsdaten\u003C/a\u003E, Inventurschwund-Zahlen und vieles mehr. Unabhängig von der Größe einer Organisation oder davon, ob sie dedizierte Data Analysts hat, um die Daten zu durchforsten, kann jedes Team gängige Datenanalyse-Tools nutzen, um die benötigten Informationen aufzudecken. Ein großer Vorteil der Data Analytics ist, dass sie eine Masse von Informationen durchdringen kann, um Trends und Muster aufzudecken, die sonst im gesamten digitalen Rauschen untergehen würden.\u003C/p\u003E\n\u003Cp\u003EVon Gaming-Unternehmen, die das Verhalten von Spielern im Spiel analysieren, über eine \u003Ca href=\"https://www.snowflake.com/de/solutions/industries/financial-services/\"\u003EBank,\u003C/a\u003E die das Kundenverhalten auf potenzielle Anzeichen von Betrug untersucht, bis hin zu Händlern, die vorhersagen, wann ein Kunde seinen nächsten Kauf tätigen wird – Data Analytics ermöglichen es Unternehmen, personalisierte Erlebnisse zu schaffen, Risiken zu mindern und die Markentreue zu steigern.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy_":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"a",":items":{"title_v2":{"id":"title-v2-1cbb5e8ffa","additionalClasses":"headline-decoration","type":"heading2","lines":["Arten von Data Analytics"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-a248d7fb18","text":"\u003Cp\u003EEs gibt vier Arten von Data Analytics, die aufeinander aufbauen: Sie gehen vom Verständnis vergangener Ereignisse zur Beeinflussung zukünftiger Ergebnisse durch datengestützte Erkenntnisse und Empfehlungen über.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E1. Deskriptive Analytik: Was ist passiert?\u003C/h4\u003E\n\u003Cp\u003EDieser Typ fasst Verlaufsdaten zusammen, um zu verstehen, was über einen bestimmten Zeitraum passiert ist, z. B. ob es einen Anstieg der Likes in Ihren Social-Media-Beiträgen, eine höhere Anzahl von Spieltransaktionen oder einen Rückgang der vierteljährlichen Produktverkäufe gab. Deskriptive Analytik ist die grundlegendste Analyseebene.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E2. Diagnostische Analytik: Warum ist es passiert?\u003C/h4\u003E\n\u003Cp\u003EHier wird es etwas komplexer – und etwas interessanter. Diagnostische Analytik konzentriert sich auf die Gründe für diese vergangenen Ereignisse und umfasst eine Kombination aus Dateneingabe und Theoretisierung. Haben Sie die richtige Kombination von Hashtags verwendet, um die Sichtbarkeit Ihres Beitrags zu erhöhen? Vielleicht hat das zeitlich begrenzte In-Game-Event diesen Anstieg der Transaktionen begünstigt?\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E3. Prädiktive Analytik: Was wird passieren?\u003C/h4\u003E\n\u003Cp\u003ENachdem Sie nun das Was und das Warum verstanden haben, müssen Sie mit der Planung beginnen, wohin Sie von hier aus gehen. \u003Ca href=\"https://www.snowflake.com/en/fundamentals/predictive-analytics-marketing/\"\u003EPrädiktive Analytik\u003C/a\u003E hilft Ihnen herauszufinden, was wahrscheinlich als Nächstes geschehen wird. Eine Kundin kauft jeden Monat Katzenstreu um diese Zeit. Daher ist die Wahrscheinlichkeit groß, dass sie einen weiteren Kauf tätigen wird. Ihr Bankkunde hat seine Rechnungen in der Vergangenheit pünktlich bezahlt, sodass es wahrscheinlich ist, dass er auch bei der Kreditrückzahlung zuverlässig sind.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E4. Präskriptive Analytik: Was sollen wir tun?\u003C/h4\u003E\n\u003Cp\u003EHier können Sie alle gesammelten und analysierten Daten und Informationen in Empfehlungen für Ihre weitere Vorgehensweise umwandeln. Ihre Marke verzeichnet einen deutlichen Anstieg der Verkäufe im Monatsvergleich, und Ihr letzter Produkt-Drop war innerhalb weniger Minuten nach der Veröffentlichung ausverkauft. Daher sollten Sie für den nächsten Drop ein Vorbestellungssystem einrichten, um die Kundenzufriedenheit zu verbessern.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__1444615495":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"use",":items":{"title_v2":{"id":"title-v2-a8bdb8b428","additionalClasses":"headline-decoration","type":"heading2","lines":["Vorteile von Data Analytics"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-590bb766cb","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EEine starke Data-Analytics-Strategie kann transformative Auswirkungen auf Ihr Unternehmen haben und Ihrem Unternehmen einen besseren Überblick darüber geben, was gut läuft und was verbessert werden muss. Sie schließt die Lücke zwischen Wissen und Handeln und versetzt Ihre Teams in die Lage, für Effizienz und Kundenzufriedenheit zu optimieren. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E1. Fundierte Entscheidungsfindung\u003C/h4\u003E\n\u003Cp\u003EKeine Vermutungen, keine Annahmen. Treffen Sie datengestützte Entscheidungen anhand von Belegen und Mustern in historischen Datasets, um genauere und zuverlässigere Ergebnisse zu erhalten.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E2. Gesteigerte betriebliche Effizienz\u003C/h4\u003E\n\u003Cp\u003EWie man so schön sagt: Wissen ist die halbe Miete. Und Data Analytics liefern verwertbare Erkenntnisse, die operative Ineffizienzen, Engpässe und Verbesserungsmöglichkeiten in der gesamten Organisation aufzeigen können. Dies verschafft Unternehmen die notwendigen Informationen, um Prozesse zu optimieren, Kosten zu senken, die Produktivität zu steigern und nicht funktionierende Strategien zu eliminieren oder zu verfeinern.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E3. Risikominderung\u003C/h4\u003E\n\u003Cp\u003EDa sich Betrug ständig weiterentwickelt und an Häufigkeit zunimmt, müssen Organisationen wachsam gegenüber böswilligen Akteuren (Bad Actors) bleiben. Datenanalytik ermöglicht die proaktive Identifizierung von Bedrohungen und Anomalien und erleichtert es Organisationen, mithilfe von KI und maschinellem Lernen gezielte Strategien zur Risikominderung zu entwickeln.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E4. Besseres Kundenverständnis\u003C/h4\u003E\n\u003Cp\u003EData Analytics liefert Unternehmen die wichtigen Kundendaten und Einblicke, die sie benötigen, um die Kundenerfahrung zu personalisieren, ihre Produkte und Dienstleistungen zu verbessern und die Kundenzufriedenheit und -treue zu steigern. Das ist ein riesiger Wettbewerbsvorteil, der nicht nur die Kundenbindung, sondern auch die Neukundenakquise und das allgemeine Unternehmenswachstum verbessert.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__1978652079":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"benefits",":items":{"title_v2":{"id":"title-v2-36ed3b8bc4","additionalClasses":"headline-decoration","type":"heading2","lines":["Schritte von Data Analytics"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-54d7c3e0ab","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EEine Fülle von Daten ist zwar großartig, doch es gibt einige Schritte, die Sie ergreifen müssen, um sie von einem Rohdatenzustand zu einem aussagekräftigen, verwertbaren Einblick zu bringen. Ein typisches Data-Analytics-Projekt beinhaltet die Durcharbeitung des Data-Analytics-Lebenszyklus: Definition des Ziels, Erfassung der Daten, Bereinigung und Aufbereitung der Daten und Analyse. \u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E1. Definition des Ziels\u003C/h4\u003E\n\u003Cp\u003EWas genau verspricht sich Ihr Team von den gesammelten Daten? Welchen Prozess oder Betrieb wollen Sie alle optimieren? Welche Kampagne unterstützen Sie? Zeit und Ressourcen für das Sammeln großer Datenmengen aufzuwenden, ist nur dann hilfreich, wenn Sie klare, definierte Ziele haben. Zeichnen Sie auf, was Sie erreichen wollen, um den Datenbedarf zu bestimmen und wie die Daten gruppiert und getrennt werden sollten.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E2. Erfassen der Daten\u003C/h4\u003E\n\u003Cp\u003ENachdem Sie nun genau wissen, wonach Sie suchen, können Ihre Datenanalysten relevante Daten sammeln, um Ihre Ziele zu unterstützen. Dies kann alles sein, vom Datenverkehr auf Ihrer Website über einen bestimmten Zeitraum hinweg, Kundenumfragen, Social-Media-Engagement-Statistiken, Transaktionsdaten, Risikobewertung und vieles mehr.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E3. Bereinigen und Aufbereiten der Daten\u003C/h4\u003E\n\u003Cp\u003EUntersuchen Sie Daten auf Fehler, Inkonsistenzen und Ausreißer, die die Zuverlässigkeit und Verwendbarkeit des Datasets beeinträchtigen könnten. Organisieren Sie sie dann für eine einfache Analyse. Tabellenkalkulationen eignen sich ideal für kleinere Datasets, werden aber bei größeren Datasets langsam und unhandlich. \u003Ca href=\"https://www.snowflake.com/de/fundamentals/ai-for-business-intelligence/\"\u003EBusiness-Intelligence\u003C/a\u003E-Tools eignen sich ideal für Datenvisualisierung und Dashboards, während \u003Ca href=\"https://www.snowflake.com/de/product/analytics/\"\u003EDatenbanken und Data Warehouses\u003C/a\u003E für sehr große Datasets erforderlich sind.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003E4. Analysieren der Daten\u003C/h4\u003E\n\u003Cp\u003ESo haben Sie Ihr sauberes, vorbereitetes Dataset. Jetzt ist der richtige Zeitpunkt, um Muster, Beziehungen und Trends mithilfe von Logik und statistischen Techniken zu ermitteln. Erinnern Sie sich noch an die Arten von Data Analytics, die wir vorhin besprochen haben? Hier nutzen Ihre Datenanalyst:innen diese Methoden, um das Was und Warum Ihrer Daten zu verstehen und die nächsten Schritte zu planen. \u003C/p\u003E\n\u003Cp\u003ETabellenkalkulationen und kostenlose Versionen von BI-Tools sind beliebte Ressourcen zur Analyse kleiner Datasets und werden in der Regel von kleineren Teams verwendet, die möglicherweise nicht einmal einen dedizierten Datenanalysten im Personal haben. Auf Unternehmensebene verarbeiten Cloud-Services und Big-Data-Verarbeitungsframeworks sowie Cloud-Services mittlere bis sehr große Datasets, oft in Verbindung mit BI-Plattformen mit vollem Funktionsumfang, um umfassende Berichte und Visualisierungen zu erstellen.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__455068363":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"how",":items":{"title_v2":{"id":"title-v2-aebd19000d","additionalClasses":"headline-decoration","type":"heading2","lines":["Data-Analytics-Techniken"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-87dbafe05e","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EGrob gesagt werden Data-Analytics-Techniken in die Kategorien überwachtes und unüberwachtes Lernen unterteilt. Überwachte Techniken lernen aus gelabelten Daten, um Vorhersagen zu treffen, während unüberwachte Techniken Muster in ungelabelten Daten finden.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003ERegressionsanalyse\u003C/h4\u003E\n\u003Cp\u003EHierbei handelt es sich um eine überwachte Lernmethode, die verwendet wird, um einen kontinuierlichen Zahlenwert basierend auf einer oder mehreren unabhängigen Variablen vorherzusagen. Anders ausgedrückt: Es ist eine statistische Methode, um die Beziehung zwischen einer abhängigen Variable und einer oder mehreren unabhängigen Variablen zu verstehen, indem eine Linie oder Kurve an die Daten angepasst wird. Sie hilft festzustellen, welche Variablen Auswirkungen haben.\u003C/p\u003E\n\u003Cp\u003EEine zentrale Frage, die die \u003Ca href=\"https://hbr.org/2015/11/a-refresher-on-regression-analysis\"\u003ERegressionsanalyse\u003C/a\u003E beantwortet, lautet: „Wie viel oder wie viele?“ und hilft Unternehmen zu bestimmen, welche Faktoren am wichtigsten und am wenigsten wichtig sind.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EKlassifizierungsanalyse\u003C/h4\u003E\n\u003Cp\u003EDie Klassifizierungsanalyse beantwortet die Frage: „Zu welcher Klasse oder Kategorie gehört das?“ und ist ein leistungsstarkes Tool, um Informationen sinnvoll zu nutzen und fundierte Entscheidungen zu treffen.\u003C/p\u003E\n\u003Cp\u003EDiese überwachte Lernmethode wird verwendet, um Daten zu sortieren und in Gruppen zu kategorisieren, indem ein Klassifizierungsmodell trainiert und ihnen dann neue Daten zur Verfügung gestellt werden, um vorherzusagen, zu welcher Kategorie sie gehören. Im Wesentlichen geht es bei der \u003Ca href=\"https://www.indicative.com/resource/classification-analysis/\"\u003EKlassifikationsanalyse\u003C/a\u003E darum, vergangene, gelabelte Daten zu nutzen, um ein Modell darin zu trainieren, neue, ungelabelte Daten korrekt zu kategorisieren.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EClusteranalyse\u003C/h4\u003E\n\u003Cp\u003EIm Gegensatz zu den beiden vorherigen Techniken ist die \u003Ca href=\"https://www.qualtrics.com/experience-management/research/cluster-analysis/\"\u003EClusteranalyse\u003C/a\u003E eine unüberwachte Lernmethode, mit der ähnliche Datenpunkte in Clustern gruppiert werden. Es gibt keine vordefinierten Labels oder Kategorien; der Algorithmus erkennt die Gruppierungen innerhalb der Daten. Clusteranalysen beantworten die Frage: „Wie können wir diese Daten gruppieren?“\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__222865509":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"ai",":items":{"title_v2":{"id":"title-v2-362842f2ab","additionalClasses":"headline-decoration","type":"heading2","lines":["Anwendungsfälle für Data Analytics"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-31f79faabf","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EWie bereits eingangs erwähnt, kann jede Branche von Data Analytics profitieren und Unternehmen jeder Größe verschaffen sich einen Wettbewerbsvorteil, indem sie ihre eigenen Daten nutzen, um zu optimieren, sich weiterzuentwickeln und zu wachsen. Schauen wir uns drei Branchen an – \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-analytics-for-retailers/\"\u003EHandel\u003C/a\u003E, Gesundheitswesen und Finanzen – um herauszufinden, wie sie Datenanalytik in ihre Arbeitsabläufe und Prozesse integrieren.\u003Cbr\u003E\n \u003C/p\u003E\n\u003Ch4\u003EHandel\u003Cbr\u003E\n \u003C/h4\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003EPersonalisierung von Werbung: Händler können die über alle Kund:innen gesammelten Daten – wie Kaufhistorien, demografische Merkmale und Verhaltensdaten – nutzen, um die E-Mail- und Social-Media-Werbeaktionen, die sie an diese Kund:innen senden, zu personalisieren. Ein maßgeschneidertes Einkaufserlebnis trägt zum Aufbau von Markentreue und zur Steigerung des Wallet Share bei.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EBestandsmanagement im Online-Handel: Um sicherzustellen, dass die Lagerbestände die Kundennachfrage decken können, analysieren Online-Händler vergangenes Kaufverhalten, Lagerbestände sowie Drittanbieter- und öffentliche Daten. Gut gefüllte digitale Regale erhöhen die Kundenbindung und verhindern, dass Kund:innen abwandern, um das Gewünschte anderswo zu bekommen.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ESicherheit in Filialen: Für physische Geschäfte ist es entscheidend, Gefahren zu beseitigen, die Kund:innen oder Mitarbeitende potenziell verletzen könnten. Die Analyse verschiedener Datenpunkte, wie z. B. Unfallberichte und Aufzeichnungen über Sicherheitsschulungen, sowie die Nutzung der vier Arten von Data Analytics, können der Führungsebene helfen, verbesserte Sicherheitsschulungen für Mitarbeitende zu entwickeln, um die Häufigkeit von Vorfällen zu reduzieren.\u003Cbr\u003E\n \u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch4\u003EGesundheitswesen\u003Cbr\u003E\n \u003C/h4\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003EPrognose von Krankheiten: Prädiktive Analytik verwendet Patientendaten wie Lebensstil, Genetik und Krankengeschichte, um Patient:innen zu identifizieren, bei denen ein hohes Risiko besteht, bestimmte Krankheiten zu entwickeln. So können Ärzt:innen personalisierte Behandlungspläne entwickeln und mit der Vorbeugung beginnen, um der Krankheit zuvorzukommen.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003ERessourcenzuweisung: Krankenhäuser können Daten wie saisonale Notaufnahmen nutzen, um die Patientenaufnahme zu prognostizieren und so Personal und Versorgung zu optimieren, um Wartezeiten zu verkürzen und die Patientenzufriedenheit zu steigern.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EBetrugserkennung: Datenanalytik kann Krankenhäusern, Apotheken und Versicherungen helfen, Betrug zu verhindern, indem sie Abrechnungsmuster, Rezeptnutzung und Versicherungsansprüche analysiert, um Anomalien und unbefugte Transaktionen zu erkennen.\u003Cbr\u003E\n \u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch4\u003EFinanzen\u003Cbr\u003E\n \u003C/h4\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003ERisikomanagement: Banken können eine Reihe von Kundendaten analysieren, darunter Ausgabengewohnheiten, Einkommensstabilität und Zahlungshistorie, um die Kreditwürdigkeit einer Person zu bestimmen.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EKundenabwanderungsprognose: Wenn bestimmte Daten (z. B. keine aktuellen Bankaktivitäten oder hohe Gebühren) darauf hindeuten, dass Kund:innen ihr Konto schließen könnten, kann die Bank proaktiv Dienstleistungen oder Anreize anbieten, diese zu behalten, wie z. B. einen speziellen Spartarif.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EAlgorithmischer Handel und Marktanalyse: Hochfrequenzhandelsunternehmen nutzen komplexe Algorithmen, um Marktdaten zu analysieren, Marktchancen und -trends zu identifizieren und Trades in Sekundenschnelle auszuführen.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__1413360324":{"columnClassNames":{"title_v2_copy":"aem-GridColumn aem-GridColumn--default--12","text_copy":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"tools",":items":{"title_v2_copy":{"id":"title-v2-637426029a","additionalClasses":"headline-decoration","type":"heading2","lines":["Gängige Tools für Data Analytics"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text_copy":{"id":"text-fd716b5977","additionalClasses":"list--blue-bullets","text":"\u003Cul\u003E\n\u003Cli\u003ETabellenkalkulation: Microsoft Excel, Google Tabellen\u003C/li\u003E\n\u003Cli\u003EBusiness-Intelligence-Tools: Tableau, Microsoft Power BI\u003C/li\u003E\n\u003Cli\u003EProgrammiersprachen: Python, R, SQL\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2_copy","text_copy"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__659376865":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"conclusion",":items":{"title_v2":{"id":"title-v2-3df4336b11","additionalClasses":"headline-decoration","type":"heading2","lines":["Fazit"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-e385575b18","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EData Analytics ist für einen Wettbewerbsvorteil in praktisch jeder Branche unerlässlich. Datengestützte Entscheidungsfindung schafft sinnvolle Effizienz, indem interne Prozesse optimiert, die Kundenerfahrung verbessert, die Markentreue erhöht – und im Falle des Gesundheitswesens die Patientengesundheit verbessert wird. \u003C/p\u003E\n\u003Cp\u003EDaten nehmen weiterhin atemberaubend schnell zu, was die Komplexität der analytischen Herausforderungen erhöht. Gleichzeitig bieten Tools und Techniken – darunter auch fortschrittliche KI-Anwendungen – neue Möglichkeiten, mit Daten zu interagieren, um wertvolle Einblicke zu gewinnen. Sie können davon ausgehen, dass der sich wandelnde Bereich der Data Analytics auch im digitalen Zeitalter ein wesentlicher Teil des Erfolgs bleibt.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__1500909857":{"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","simple_snowflake_acc":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"faq",":items":{"title_v2":{"id":"title-v2-8904f36566","additionalClasses":"headline-decoration","type":"heading2","lines":["Häufig gestellte Fragen zu Data Analytics"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"simple_snowflake_acc":{"id":"simple-snowflake-accordion-ebaa9eb6f5","additionalClasses":"list--blue-bullets","showDivider":false,"accordionItemsList":[{"title":"Was sind die besten Kurse für Data Analytics?","richText":"\u003Cp\u003EBudget, Lernstil und Karriereziele unterscheiden sich. Doch die besten Data-Analytics-Kurse vermitteln Ihnen eine starke Grundlage für Kernkompetenzen wie Programmiersprachen und Datenvisualisierungstools. Es gibt viele kostenlose Online-Kurse auf Plattformen wie Coursera oder DataCamp, die eine Einführung in Data Analytics bieten. Forbes hat \u003Ca href=\"https://www.forbes.com/advisor/education/certifications/best-data-analytics-certifications/\"\u003Eeine Liste der besten Online-Zertifizierungen für Data Analytics\u003C/a\u003E zusammengestellt. Snowflake bietet unsere \u003Ca href=\"https://learn.snowflake.com/en/certifications/snowpro-advanced-dataanalyst/?pdf_name=SnowProDataAnalystStudyGuide\"\u003ESnowPro® Advanced: Data-Analyst-Zertifizierung\u003C/a\u003E für fortgeschrittenes Wissen und fortgeschrittene Fähigkeiten, die zur Anwendung umfassender Datenanalyseprinzipien mit Snowflake verwendet werden.\u003C/p\u003E\n"},{"title":"Welche Tools werden zur Analyse von Big Data eingesetzt?","richText":"\u003Cp\u003EEs gibt eine Reihe spezialisierter Tools, die riesige Datenmengen verarbeiten, schnell verarbeiten und aussagekräftige Erkenntnisse gewinnen können. Hier einige Beispiele:\u003Cbr\u003E\n \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003EBig-Data-Frameworks: \u003Ca href=\"https://www.snowflake.com/de/product/features/snowpark/\"\u003ESnowflake Snowpark\u003C/a\u003E, \u003Ca href=\"https://hadoop.apache.org/\"\u003EApache Hadoop\u003C/a\u003E, \u003Ca href=\"https://spark.apache.org/\"\u003EApache Spark\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003ECloudbasierte Data Warehouses: \u003Ca href=\"https://cloud.google.com/bigquery?utm_source=google&utm_medium=cpc&utm_campaign=na-US-all-en-dr-bkws-all-all-trial-e-dr-1710134&utm_content=text-ad-none-any-DEV_c-CRE_772298885512-ADGP_Hybrid+%7C+BKWS+-+EXA+%7C+Txt-Data+Analytics-Data+Analytics-BigQuery-KWID_43700082585516178-kwd-63326440124&utm_term=KW_google%20bigquery-ST_google+bigquery&gclsrc=aw.ds&gad_source=1&gad_campaignid=22970352687&gclid=Cj0KCQjwoP_FBhDFARIsANPG24P3VZl3_a-liWj18JKg9cBt96oy0h9fSeV7h9G4GzXW5-1YxrW6tdUaAsoCEALw_wcB\"\u003EGoogle BigQuery\u003C/a\u003E, \u003Ca href=\"https://aws.amazon.com/pm/redshift/?trk=a136dbb3-ff50-468b-9a66-852dc1ca985b&sc_channel=ps&ef_id=Cj0KCQjwoP_FBhDFARIsANPG24OEawaY6lV0Vnxy6v98luBjDNhrPJ71Q1KZ_r_NcuG4ZvpzRg5ZYF8aAsHOEALw_wcB:G:s&s_kwcid=AL!4422!3!651751058853!e!!g!!amazon%20redshift!19852662155!145019245577&gad_campaignid=19852662155&gbraid=0AAAAADjHtp_w47gFWrFMuAm5btwOo9ScF&gclid=Cj0KCQjwoP_FBhDFARIsANPG24OEawaY6lV0Vnxy6v98luBjDNhrPJ71Q1KZ_r_NcuG4ZvpzRg5ZYF8aAsHOEALw_wcB\"\u003EAmazon Redshift\u003C/a\u003E, \u003Ca href=\"https://www.snowflake.com/en/product/analytics/\"\u003ESnowflake\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003EBI und Visualisierungstools: \u003Ca href=\"https://www.tableau.com/\"\u003ETableau\u003C/a\u003E, \u003Ca href=\"https://www.microsoft.com/en-us/power-platform/products/power-bi\"\u003EMicrosoft Power BI\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003EProgrammiersprachen und Bibliotheken: \u003Ca href=\"https://www.python.org/\"\u003EPython\u003C/a\u003E, \u003Ca href=\"https://www.r-project.org/\"\u003ER\u003C/a\u003E, \u003Ca href=\"https://www.coursera.org/specializations/learn-sql-basics-data-science/paidmedia?utm_medium=sem&utm_source=gg&utm_campaign=b2c_namer_learn-sql-basics-data-science_ucdavis_ftcof_specializations_px_dr_bau_gg_sem_pr-bd_us-ca_en_m_hyb_24-12_x&campaignid=20743946861&adgroupid=154886907309&device=c&keyword=sql&matchtype=b&network=g&devicemodel=&creativeid=679514232408&assetgroupid=&targetid=kwd-10206160&extensionid=&placement=&gad_source=1&gad_campaignid=20743946861&gbraid=0AAAAADdKX6azVKefwfYb2NyuzsKTgMGOJ&gclid=Cj0KCQjwoP_FBhDFARIsANPG24PZTNLiGUpmlyl3WDAV8k-_Yop5rD7fxGmgImdMCl0YROUq1DUPB04aAsUhEALw_wcB\"\u003ESQL\u003C/a\u003E\u003C/li\u003E\n\u003C/ul\u003E\n"},{"title":"Was ist ein Beispiel für Data Analytics?","richText":"\u003Cp\u003EKundensegmentierung im \u003Ca href=\"https://www.snowflake.com/en/fundamentals/data-analytics-for-retailers/\"\u003EHandel\u003C/a\u003E. \u003Ca href=\"https://www.snowflake.com/de/solutions/industries/retail-consumer-goods/\"\u003EHändler\u003C/a\u003E können die enorme Menge an Kundendaten nutzen, um Kund:innen in verschiedene Segmente zu gruppieren, z. B. Kund:innen, die nur High-End-Elektronik kaufen oder nur während des Ausverkaufs einkaufen. Sobald die Segmente festgelegt sind, kann der Händler jedem Segment gezielte Marketingmaterialien senden, wie z. B. maßgeschneiderte Produktempfehlungen oder Early Access Sales Alerts.\u003C/p\u003E\n"},{"title":"Was ist der Unterschied zwischen Data Analytics und Datenanalyse?","richText":"\u003Cp\u003EData Analytics ist ein breites, umfassendes Gebiet, dessen zentraler Teil die Datenanalyse ist. Datenanalysen zielen darauf ab, die Vergangenheit und die bisherigen Entwicklungen zu verstehen, verwertbare Erkenntnisse zu gewinnen und datengestützte Entscheidungen zu treffen. Data Analytics nutzt Daten, um künftige Verhaltensweisen vorherzusagen, Maßnahmen vorzuschreiben und ist eine zukunftsorientierte Disziplin. Während Datenanalysen deskriptive Einblicke aus früheren Daten liefern, bauen Datenanalysen auf dieser Grundlage auf, um zukunftsorientierte Strategien zu entwickeln, um Maßnahmen zu ergreifen.\u003C/p\u003E\n"}],":type":"snowflake-site/components/simple-snowflake-accordion","appliedCssClassNames":"snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","simple_snowflake_acc"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"container_copy_copy__480869401":{"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","title_v2":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","layout":"RESPONSIVE_GRID","columnCount":12,"id":"customer",":items":{"title_v2":{"id":"title-v2-8853de0a77","additionalClasses":"headline-decoration","type":"heading2","lines":["Snowflake-Kunden, die Analytics 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bieten.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text"},"layoutStyle":"vertical","title":{"id":"title","type":"heading4","lines":["VideoAmp Saves 90% in Costs and Increases Performance 10x"],":type":"snowflake-site/components/title-v2"},"button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/en/customers/all-customers/case-study/videoamp/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Customer Story lesen (Englisch)"},"image":{"id":"image","alt":"simon data logo","lazyEnabled":true,":type":"snowflake-site/components/image"},"type":"content-card"}},":itemsOrder":["card_v2"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-b8720bd51f",":items":{"card_v2_copy":{"id":"card-v2-109b77fd46","configurationStatus":{"configured":true,"message":""},":type":"snowflake-site/components/card-v2","text":{"id":"text","text":"\u003Cp\u003EMit Snowflake als Herzstück konnte Luminate – Betreiber der kultigen Billboard-Musikcharts und vertrauenswürdigster Datenpartner der Unterhaltungsindustrie – seine Daten vereinheitlichen, um eine innovativere Produktentwicklung und eine perfekte Datenverarbeitung zu 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