{"robotsTags":["noindex","nofollow"],"templateName":"demand-gen-landing-page-template","cssClassNames":"page basicpage summit-page","canonicalLink":"https://www.snowflake.com/de/resources/ebook/building-the-interoperable-lakehouse-data-strategies-for-ai-leaders/","allowedRenditionsWidth":["320","480","640","768","960","1200","1440","1920"],"description":"Erfahren Sie, wie Sie ein Lakehouse mit Apache Iceberg aufbauen, Datensilos beseitigen und KI durch Multi-Engine-Zugriff auf Live-Daten skalieren.","language":"de","title":"Interoperables Lakehouse für KI: Datenstrategie-Leitfaden","analyticsPageType":"homepage","analyticsCategory":"general","analyticsSubCategory":"","excludeFromAnalytics":false,":mappedPath":"/de/resources/ebook/building-the-interoperable-lakehouse-data-strategies-for-ai-leaders/",":type":"snowflake-site/components/structure/page",":items":{"root":{"columnCount":12,"gridClassNames":"aem-Grid aem-Grid--12 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!important;font-family:'Texta',sans-serif;font-weight:700 !important;font-size:14px !important;background-image:none !important}div .mktoForm .mktoButtonWrap.mktoSimple .mktoButton:focus,div .mktoForm .mktoButtonWrap.mktoSimple .mktoButton:active,div .mktoForm .mktoButtonWrap.mktoSimple .mktoButton:hover{background-color:var(--ui-02);border-color:var(--ui-02)}",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false},"responsivegrid":{"columnCount":12,"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12","simplified_lead_spac":"aem-GridColumn aem-GridColumn--default--12"},":items":{"simplified_lead_spac":{"id":"simplified-lead-space-8a6cc1c018","title":{"id":"title","type":"display2","lines":["Aufbau eines interoperablen Lakehouse: Datenstrategien für KI-Führungskräfte"],":type":"snowflake-site/components/title"},"image":{"id":"image","height":"403","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--fcadecbf-8567-411f-b545-75a1d3c23bae/default-simplified-lead-space.png?preferwebp=true&quality=85","lazyEnabled":true,"alt":"Long exposure top down view of people walking on a pavement ","isLcpImage":true,"width":"1280",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/simplified-lead-space"},"container":{"layout":"RESPONSIVE_GRID","columnCount":12,"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"marketo_container":"aem-GridColumn aem-GridColumn--default--12"},"id":"container-3cf1a10c0a",":type":"snowflake-site/components/container",":items":{"marketo_container":{"id":"marketo-container-2551edd2e1","marketo_content_container":{"layout":"SIMPLE","id":"container-d8cecfd96a",":type":"snowflake-site/components/marketo-container/marketo-content-container",":items":{"text":{"id":"text-7432cc75d5","text":"\u003Ch4\u003ESchaffen Sie eine Datengrundlage, die Ihnen alle Freiheiten lässt. Beschleunigen Sie Ihre KI-Initiativen mit jeder beliebigen Engine – dank eines Lakehouse, das auf der Interoperabilität von Snowflake basiert.\u003C/h4\u003E\r\n\u003Cp\u003EViele Unternehmen lassen die Phase der KI-Experimente hinter sich und streben den Produktivbetrieb an. Dabei stellen sie oft fest: Die größte Einschränkung sind nicht die KI-Modelle selbst, sondern die zugrunde liegende Datenarchitektur.\u003C/p\u003E\r\n\u003Cp\u003EDas Hauptproblem ist die Fragmentierung, verursacht durch mangelnde Interoperabilität zwischen Engines und Tools. Wenn Teams ihre Daten nicht dort nutzen können, wo sie sich befinden, greifen sie zu teuren und arbeitsintensiven Workarounds. Sie kopieren Daten. Das Ergebnis: eine fragmentierte Tool-Landschaft, isolierte Governance, explodierende Speicherkosten und massiver Engineering-Aufwand.\u003C/p\u003E\r\n\u003Cp\u003EFür KI-Agenten ist diese Datenfragmentierung fatal. Sie zwingt die Agenten dazu, den semantischen Kontext immer wieder neu zu suchen und zu rekonstruieren – das verschwendet Tokens und treibt die „Costs per Thought“ (Kosten pro Gedanke) in die Höhe. Noch gravierender: Sind dieselben Daten an mehreren Orten gespeichert, steigt das Risiko für Halluzinationen und falsche Antworten. Das zerstört das Vertrauen in Ihre Daten und untergräbt wichtige Geschäftsentscheidungen – ein absolutes Ausschlusskriterium für den Unternehmenseinsatz. \u003C/p\u003E\r\n\u003Cp\u003EAber Snowflake weiß: \u003Cb\u003EErfolgreiche KI erfordert vollständige Interoperabilität.\u003C/b\u003E\u003C/p\u003E\r\n\u003Cp\u003EIn unserem neuen E-Book \u003Ci\u003EAufbau eines interoperablen Lakehouse\u003C/i\u003E zeigen wir Ihnen einen besseren Weg. Entdecken Sie, wie Sie eine Lakehouse-Architektur auf Basis von Apache Iceberg™ und Apache Polaris™ entwerfen, die Ihre Datengrundlage KI-fähig macht und gleichzeitig den Engineering-Aufwand und die Kosten drastisch senkt. Dieser praxisorientierte Leitfaden vermittelt Ihnen das nötige Fundament zu offenen Tabellenformaten, zeigt verschiedene Architekturansätze und erklärt, warum es so entscheidend ist, mit jeder Engine auf Ihre Daten zugreifen zu können.\u003C/p\u003E\r\n\u003Cp\u003EDas erwartet Sie in diesem Leitfaden:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EDaten ohne Kompromisse vernetzen:\u003C/b\u003E Erfahren Sie, wie offene Tabellenformate wie Apache Iceberg als zentrales Bindeglied Ihrer Datenlandschaft fungieren. So vermeiden Sie funktionale Lock-ins und bringen Ihre Tools direkt zu den Daten.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EOptimierung für Skalierbarkeit:\u003C/b\u003E Entdecken Sie, wie deklaratives Data Engineering, Zero-Copy Cloning und automatisierte Datenerfassung den Infrastrukturaufwand minimieren und Ihr Team dem ZeroOps-Ziel näherbringen.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EGovernance für das KI-Zeitalter: \u003C/b\u003EVerstehen Sie, wie ein zentraler Ansatz für Governance, Sicherheit und Vertrauen Ihre Datenteams von der reaktiven Fehlerbehebung zum proaktiven Schutz führt.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EArchitekturmuster aus der Praxis: \u003C/b\u003EEntdecken Sie praxiserprobte Architekturmuster, die die Interoperabilität von Snowflake mit führenden Cloud-Anbietern wie AWS, Microsoft Azure und Google Cloud demonstrieren.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EBewährte Business Cases:\u003C/b\u003E Lesen Sie, wie Branchenführer wie \u003Cb\u003EGoldman Sachs, Affirm\u003C/b\u003E und \u003Cb\u003EIndeed\u003C/b\u003E bereits messbaren ROI erzielen, indem sie ihre Datengrundlage mit Snowflake modernisieren.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EEin interoperables Lakehouse ist weit mehr als nur ein Upgrade für Ihren Data Stack – es definiert grundlegend neu, was Ihr Unternehmen mit Daten erreichen kann. Es ersetzt starre, isolierte Systeme durch ein Fundament, das vernetzt, offen und ohne Datenverschiebungen zugänglich ist. Die in diesem E-Book vorgestellten Unternehmen sind keine Ausnahmen – sie sind Vorboten dessen, was möglich ist, wenn die Datenarchitektur nicht länger eine Einschränkung, sondern ein echter Katalysator ist:\u003C/p\u003E\r\n\u003Cp\u003ESchnellerer Zugriff auf hochwertige Daten, universelle Governance und das Ende alltäglicher Reibungsverluste. Das sind keine abstrakten Versprechen, sondern messbare Ergebnisse. Es ist an der Zeit, Ihre KI-Initiativen von der Idee in die Praxis umzusetzen – angetrieben durch Ihre Architektur, nicht ausgebremst von ihr.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular"}},":itemsOrder":["text"]},"marketo_form_container":{"layout":"SIMPLE","id":"container-70d7ad5925",":type":"snowflake-site/components/marketo-container/marketo-form-container",":items":{"marketo_v2":{"id":"marketo-v2-577c46f8a8","marketoForm":{"hidden":null,"formId":"48822","successUrl":"form.onSuccess(function(values, followUpUrl) {\nlocation.href = \"https:\\/\\/www.snowflake.com\\/de\\/resources\\/ebook\\/building-the-interoperable-lakehouse-data-strategies-for-ai-leaders\\/thankyou\\/\";\nreturn false;\n});","edit":false,"script":null,"values":null},"title":{"id":"title","type":"heading3","lines":["Jetzt 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