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class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M15.5 8C15.5 8.29 15.38 8.56 15.16 8.75L7.16 15.75L5.84 14.24L11.84 8.99H0.5V6.99H11.84L5.84 1.76L7.16 0.25L15.16 7.25C15.38 7.44 15.5 7.71 15.5 8Z" data-type="fill"></path> </svg></span> </div></a> </div> <h1 data-rg-n="HeadingText" class="basetext_module_text__61099e5e basetext_module_block__61099e5e headingtext_module_heading__00ee2f90 headingtext_module_size1__00ee2f90">Amazon SageMaker</h1> <h4 data-rg-n="SubheadingText" class="basetext_module_text__61099e5e basetext_module_block__61099e5e subheadingtext_module_subheading__99e66897 hero_module_heroSubheading__77503c7f subheadingtext_module_size1__99e66897">Die nächste Generation von Amazon SageMaker ist das Zentrum für all Ihre Daten, Analytik und KI </h4> <div class="hero_module_heroButtons__77503c7f"> <div class="hero_module_heroButton__77503c7f"> <a role="button" href="https://console.aws.amazon.com/datazone" rel="noopener noreferrer" target="_blank" data-rigel-analytics="{"name":"Button","properties":{"variant":"primary"}}" class="dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 buttonbase_module_buttonBase__efa86cab buttonbase_module_primary__efa86cab button_module_button__f561bac2"><span data-rg-n="UtilityText" class="basetext_module_text__61099e5e basetext_module_center__61099e5e utilitytext_module_utility__9ef276a8 button_module_content__f561bac2 utilitytext_module_size3__9ef276a8">Erste Schritte mit Amazon SageMaker</span></a> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div class="lb-mbox js-mbox" data-lb-comp="mbox" data-lb-comp-ignore="true" data-mbox="en_sagemaker-ignite-summary-test"> </div> <div data-eb-slot="introduction" data-eb-slot-meta="{'version':'1.0','slotId':'introduction','experienceId':'49b9c725-36e2-4908-86d9-b64cc9f56589','allowBlank':false,'hasAltExp':false,'isRTR':false,'filters':{'limit':1,'query':'id \u003d \'sagemaker-northstar-overview\''}}"> <div data-eb-tpl-n="awsm-rt/rt-text-media-collection" data-eb-tpl-v="1.2.0" data-eb-ce="" data-eb-c-scope="introduction" data-eb-d-scope="DIRECTORIES" data-eb-locale="de-DE" data-eb-7170ec75="" data-eb-ssr-ce="" data-eb-tpl-ns="awsmRT" data-eb-hydrated="pending"> <script type="application/json">{"data":{"items":[{"fields":{"dark":"0","bodyContent":"<p>Amazon SageMaker vereint die weit verbreiteten AWS-Funktionen für Machine Learning und Analytik und bietet ein integriertes Erlebnis für Analytik und KI mit einheitlichem Zugriff auf alle Ihre Daten. 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Greifen Sie auf sämtliche Daten zu, unabhängig davon, ob sie in Data Lakes, Data Warehouses, Drittanbieter- oder Verbunddatenquellen gespeichert sind und sorgen Sie für integrierte Governance, um die Sicherheitsanforderungen des Unternehmens zu erfüllen.</p>","id":"collection-text-media#sagemaker-northstar-overview","heading":"Übersicht","mediaPosition":"right","mediaAltText":"image"},"metadata":{"tags":[]}}]},"metadata":{"auth":{},"testAttributes":{}},"context":{"page":{"pageUrl":"https://aws.amazon.com/de/sagemaker/"},"environment":{"stage":"prod","region":"us-east-1"},"sdkVersion":"1.0.129"},"refMap":{"manifest.js":"47864e0370","rt-text-media-collection.rtl.css":"4a56177a31","rt-text-media-collection.js":"549552b6f3","rt-text-media-collection.css.js":"b7f4f2a16e","rt-text-media-collection.css":"dbf6370bb5","rt-text-media-collection.rtl.css.js":"641e7324ee"},"settings":{"templateMappings":{"hyperlinkText":"hyperlinkText","hyperlinkUrl":"hyperlinkUrl","heading":"heading","mediaAltText":"mediaAltText","mediaPosition":"mediaPosition","mediaUrl":"mediaUrl","subheader":"subheader","bodyContent":"bodyContent","videoOverlayTitle":"videoOverlayTitle","videoThumbnailUrl":"videoThumbnailUrl","videoPlayButtonText":"videoPlayButtonText","dark":"dark"}}}</script> <div data-eb-tpl-root="" data-reactroot=""> <div> <div data-rg-theme="teal" data-rg-mode="light" data-style-count="0"> <div data-rg-lang="de" data-rg-locale="de-DE" lang="de-DE" dir="ltr"> <div data-rg-n="GridStack" class="gridStack_module_gridStack__35667094" style="--rg-gridstack-gap:var(--rg-margin-2)"> <div data-rg-n="TextMediaContent" data-rg-theme="teal" data-rg-mode="light" data-media-position="end" class="textmediacontent_module_textMediaContent__d28b7a4a textmediacontent_module_gridPadding__d28b7a4a grid_module_grid__590284f4 grid_module_fullWidth__590284f4 grid_module_vPadding__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM5__66940a30 col_module_colL5__66940a30 col_module_colXl5__66940a30 col_module_colXxl5__66940a30 textmediacontent_module_headingContainer__d28b7a4a"> <h2 data-rg-n="HeadingText" class="basetext_module_text__61099e5e headingtext_module_heading__00ee2f90 textmediacontent_module_heading__d28b7a4a headingtext_module_size2__00ee2f90">Übersicht</h2> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col1__66940a30 textmediacontent_module_spacer__d28b7a4a"></div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL6__66940a30 col_module_colXl6__66940a30 col_module_colXxl6__66940a30 textmediacontent_module_bodyContainer__d28b7a4a"> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c bodytext_module_size1__ca32720c"> <p>Amazon SageMaker vereint die weit verbreiteten AWS-Funktionen für Machine Learning und Analytik und bietet ein integriertes Erlebnis für Analytik und KI mit einheitlichem Zugriff auf alle Ihre Daten. Kollaborieren und erstellen Sie schneller von einem einheitlichen Studio (Vorschau) aus mit vertrauten AWS-Tools für Modellentwicklung, generative KI, Datenverarbeitung und SQL-Analysen, beschleunigt durch Amazon Q Developer, den leistungsfähigsten generativen KI-Assistenten für die Softwareentwicklung. Greifen Sie auf sämtliche Daten zu, unabhängig davon, ob sie in Data Lakes, Data Warehouses, Drittanbieter- oder Verbunddatenquellen gespeichert sind und sorgen Sie für integrierte Governance, um die Sicherheitsanforderungen des Unternehmens zu erfüllen.</p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div data-eb-slot="benefits-amazon-sagemaker-northstar" data-eb-slot-meta="{'version':'1.0','slotId':'benefits-amazon-sagemaker-northstar','experienceId':'5b0041ec-5bf3-11ee-8c99-0242ac120002','allowBlank':false,'hasAltExp':false,'isRTR':false,'filters':{'limit':10,'query':'(id \u003d \'sagemaker-northstar-benefits-overview\' OR id \u003d \'sagemaker-northstar-benefits-1\' OR id \u003d \'sagemaker-northstar-benefits-2\' OR id \u003d \'sagemaker-northstar-benefits-3\' OR id \u003d \'sagemaker-northstar-benefits-4\')'}}"> <div data-eb-tpl-n="awsm-rt/rt-qa-sampler" data-eb-tpl-v="1.0.0" data-eb-ce="" data-eb-c-scope="benefits-amazon-sagemaker-northstar" data-eb-d-scope="DIRECTORIES" data-eb-locale="de-DE" data-eb-d9d0c036="" data-eb-ssr-ce="" data-eb-tpl-ns="awsmRT" data-eb-hydrated="pending"> <script type="application/json">{"data":{"items":[{"fields":{"patternInlineHeading":"0","benefitTitle":"Schnellere Zusammenarbeit und Entwicklung mit einer einzigen Daten- und KI-Entwicklungsumgebung","id":"product-benefits#sagemaker-northstar-benefits-1","customSortOrder":"1","benefitContent":"Amazon SageMaker Unified Studio (Vorversion) bietet ein integriertes Erlebnis, mit dem Sie all Ihre Daten und Tools für Analytik und KI nutzen können. 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Erstellen Sie Analytik- und KI-Artefakte wie Daten, Modelle und generative KI-Anwendungen und teilen Sie sie sicher, um Datenprodukte schneller auf den Markt zu bringen."},"metadata":{"tags":[]}},{"fields":{"patternInlineHeading":"0","benefitTitle":"KI-Anwendungsfälle mit einer Vielzahl von Tools entwickeln und skalieren","id":"product-benefits#sagemaker-northstar-benefits-2","customSortOrder":"2","benefitContent":"Beschleunigen Sie die KI in Amazon SageMaker mit einer umfassenden Reihe von KI-Entwicklungsfunktionen, die standardmäßig sicher sind. Training, Anpassung und Bereitstellung von ML- und Basismodellen (FMs) auf einer hochleistungsfähigen und kostengünstigen Infrastruktur. Verwenden Sie speziell entwickelte Tools, die den gesamten KI-Lebenszyklus abdecken – von leistungsstarken integrierten Entwicklungsumgebungen (IDEs) und verteilten Trainings bis hin zu Inferenz, KI-Operationen, Governance und Beobachtbarkeit. 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Gewinnen Sie Vertrauen in Ihrem gesamten Unternehmen durch Überwachung und Automatisierung der Datenqualität, Erkennung sensibler Daten sowie Daten- und ML-Herkunft."},"metadata":{"tags":[]}},{"fields":{"patternInlineHeading":"0","patternTitle":"Vorteile","id":"product-benefits#sagemaker-northstar-benefits-overview"},"metadata":{"tags":[{"id":"GLOBAL#pattern#pattern-data","name":"pattern-data","namespaceId":"GLOBAL#pattern","description":"pattern-data","metadata":{}}]}}]},"metadata":{"auth":{},"pagination":{"empty":false,"present":true},"testAttributes":{}},"context":{"page":{"pageUrl":"https://aws.amazon.com/de/sagemaker/"},"environment":{"stage":"prod","region":"us-east-1"},"sdkVersion":"1.0.129"},"refMap":{"manifest.js":"3daf852ae2","rt-qa-sampler.js":"a1a586a2a7","rt-qa-sampler.rtl.css":"bd7152f8b0","rt-qa-sampler.css":"c739e31c0a","rt-qa-sampler.css.js":"f965de4043","rt-qa-sampler.rtl.css.js":"ab040a2e3b"},"settings":{"templateMappings":{"patternHeading":"patternTitle","patternSubheading":"subheading","topic":"benefitTitle","content":"benefitContent"}}}</script> <div data-eb-tpl-root="" data-reactroot=""> <span data-eb-item-id="product-benefits#sagemaker-northstar-benefits-overview"> <div> <div data-rg-lang="de" data-rg-locale="de-DE" lang="de-DE" dir="ltr"> <div data-rg-theme="fuchsia" data-rg-mode="light" data-style-count="0"> <div data-rg-n="GridStack" class="gridStack_module_gridStack__35667094"> <div data-rg-n="Grid" class="qaSampler_module_qaSamplerGrid__b180ba78 grid_module_grid__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM5__66940a30 col_module_colL5__66940a30 col_module_colXl5__66940a30 col_module_colXxl5__66940a30"> <div data-testid="sticky-header" class="stickyHeader_module_stickyHeader__91e4d062" style="top:0px"> <h2 data-rg-n="HeadingText" class="basetext_module_text__61099e5e headingtext_module_heading__00ee2f90 headingtext_module_size2__00ee2f90">Vorteile</h2> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs0__66940a30 col_module_colS0__66940a30 col_module_colM1__66940a30 col_module_colL1__66940a30 col_module_colXl1__66940a30 col_module_colXxl1__66940a30"></div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL6__66940a30 col_module_colXl6__66940a30 col_module_colXxl6__66940a30 qaSampler_module_qaSamplerExpanderCol__b180ba78"> <div class="itemExpander_module_expandableSection__e56d1e98" data-eb-item-id="0"> <div class="itemExpander_module_expandableSectionHeader__e56d1e98 qaSampler_module_qaSamplerExpanderHeader__b180ba78" id="0-trigger" aria-controls="content-0" aria-expanded="false" tabindex="0" role="button" data-rigel-analytics="{"name":"ItemExpander","properties":{"expanded":false}}"> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 qaSampler_module_qaSamplerTitle__b180ba78 titletext_module_size4__e23b0698">Schnellere Zusammenarbeit und Entwicklung mit einer einzigen Daten- und KI-Entwicklungsumgebung</h3> <div class="itemExpander_module_expandableSectionHeaderTrigger__e56d1e98" aria-hidden="true"> <span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M16 9H9V16H7V9H0V7H7V0H9V7H16V9Z" data-type="fill"></path> </svg></span> </div> </div> <div id="content-0" aria-labelledby="0-trigger" class="itemExpander_module_expandableSectionContent__e56d1e98"> <div class="itemExpander_module_expandableSectionContentWrapper__e56d1e98"> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c qaSampler_module_qaSamplerContent__b180ba78 bodytext_module_size1__ca32720c"> Amazon SageMaker Unified Studio (Vorversion) bietet ein integriertes Erlebnis, mit dem Sie all Ihre Daten und Tools für Analytik und KI nutzen können. Entdecken Sie Ihre Daten und nutzen Sie sie mit vertrauten AWS-Tools für Modellentwicklung, generative KI, Datenverarbeitung und SQL-Analytik. Arbeiten Sie mit vereinheitlichten Notebooks über mehrere Rechenressourcen hinweg, entdecken und fragen Sie verschiedene Datenquellen mit einem integrierten SQL-Editor ab, trainieren und implementieren Sie KI-Modelle in großem Maßstab und erstellen Sie schnell benutzerdefinierte generative KI-Anwendungen. Erstellen Sie Analytik- und KI-Artefakte wie Daten, Modelle und generative KI-Anwendungen und teilen Sie sie sicher, um Datenprodukte schneller auf den Markt zu bringen. </div> </div> </div> </div> <div class="itemExpander_module_expandableSection__e56d1e98" data-eb-item-id="1"> <div class="itemExpander_module_expandableSectionHeader__e56d1e98 qaSampler_module_qaSamplerExpanderHeader__b180ba78" id="1-trigger" aria-controls="content-1" aria-expanded="false" tabindex="0" role="button" data-rigel-analytics="{"name":"ItemExpander","properties":{"expanded":false}}"> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 qaSampler_module_qaSamplerTitle__b180ba78 titletext_module_size4__e23b0698">KI-Anwendungsfälle mit einer Vielzahl von Tools entwickeln und skalieren</h3> <div class="itemExpander_module_expandableSectionHeaderTrigger__e56d1e98" aria-hidden="true"> <span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M16 9H9V16H7V9H0V7H7V0H9V7H16V9Z" data-type="fill"></path> </svg></span> </div> </div> <div id="content-1" aria-labelledby="1-trigger" class="itemExpander_module_expandableSectionContent__e56d1e98"> <div class="itemExpander_module_expandableSectionContentWrapper__e56d1e98"> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c qaSampler_module_qaSamplerContent__b180ba78 bodytext_module_size1__ca32720c"> Beschleunigen Sie die KI in Amazon SageMaker mit einer umfassenden Reihe von KI-Entwicklungsfunktionen, die standardmäßig sicher sind. Training, Anpassung und Bereitstellung von ML- und Basismodellen (FMs) auf einer hochleistungsfähigen und kostengünstigen Infrastruktur. Verwenden Sie speziell entwickelte Tools, die den gesamten KI-Lebenszyklus abdecken – von leistungsstarken integrierten Entwicklungsumgebungen (IDEs) und verteilten Trainings bis hin zu Inferenz, KI-Operationen, Governance und Beobachtbarkeit. Erstellen Sie schnell generative KI-Anwendungen, die auf Ihr Unternehmen zugeschnitten sind, mit modernsten Modellen und Ihren firmeneigenen Daten. Beschleunigen Sie die KI-Entwicklung mit Amazon Q Developer, damit Sie Daten einfacher finden, ML-Modelle erstellen und trainieren, SQL-Abfragen generieren und Daten-Pipeline-Aufträge erstellen und ausführen können – alles in natürlicher Sprache. </div> </div> </div> </div> <div class="itemExpander_module_expandableSection__e56d1e98" data-eb-item-id="2"> <div class="itemExpander_module_expandableSectionHeader__e56d1e98 qaSampler_module_qaSamplerExpanderHeader__b180ba78" id="2-trigger" aria-controls="content-2" aria-expanded="false" tabindex="0" role="button" data-rigel-analytics="{"name":"ItemExpander","properties":{"expanded":false}}"> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 qaSampler_module_qaSamplerTitle__b180ba78 titletext_module_size4__e23b0698">Datensilos mit einem offenen Lakehouse reduzieren, um all Ihre Daten zu vereinheitlichen</h3> <div class="itemExpander_module_expandableSectionHeaderTrigger__e56d1e98" aria-hidden="true"> <span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M16 9H9V16H7V9H0V7H7V0H9V7H16V9Z" data-type="fill"></path> </svg></span> </div> </div> <div id="content-2" aria-labelledby="2-trigger" class="itemExpander_module_expandableSectionContent__e56d1e98"> <div class="itemExpander_module_expandableSectionContentWrapper__e56d1e98"> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c qaSampler_module_qaSamplerContent__b180ba78 bodytext_module_size1__ca32720c"> Vereinheitlichen Sie all Ihre Daten in Amazon Simple Storage Service (Amazon S3) Data Lakes und Amazon Redshift Data Warehouses mit Amazon SageMaker Lakehouse. Verschaffen Sie sich die Flexibilität, auf Ihre Daten mit allen Apache-Iceberg-kompatiblen Tools und Engines in einer einzigen Kopie der Analytikdaten zuzugreifen und diese abzufragen. Schützen Sie Ihre Daten, indem Sie detaillierte Berechtigungen definieren, die auf Ihre Analytik- und KI-Tools im Lakehouse angewendet werden. Bringen Sie Daten aus Betriebsdatenbanken und Anwendungen durch Null-ETL-Integrationen nahezu in Echtzeit in Ihr Lakehouse. Darüber hinaus können Sie mit Verbundabfragefunktionen aus Datenquellen von Drittanbietern direkt auf Daten zugreifen und diese abfragen. </div> </div> </div> </div> <div class="itemExpander_module_expandableSection__e56d1e98" data-eb-item-id="3"> <div class="itemExpander_module_expandableSectionHeader__e56d1e98 qaSampler_module_qaSamplerExpanderHeader__b180ba78" id="3-trigger" aria-controls="content-3" aria-expanded="false" tabindex="0" role="button" data-rigel-analytics="{"name":"ItemExpander","properties":{"expanded":false}}"> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 qaSampler_module_qaSamplerTitle__b180ba78 titletext_module_size4__e23b0698">Die Sicherheitsanforderungen Ihres Unternehmens mit durchgängiger Daten- und KI-Governance erfüllen</h3> <div class="itemExpander_module_expandableSectionHeaderTrigger__e56d1e98" aria-hidden="true"> <span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M16 9H9V16H7V9H0V7H7V0H9V7H16V9Z" data-type="fill"></path> </svg></span> </div> </div> <div id="content-3" aria-labelledby="3-trigger" class="itemExpander_module_expandableSectionContent__e56d1e98"> <div class="itemExpander_module_expandableSectionContentWrapper__e56d1e98"> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c qaSampler_module_qaSamplerContent__b180ba78 bodytext_module_size1__ca32720c"> Sorgen Sie für Unternehmenssicherheit mit integrierter Governance für den gesamten Daten- und KI-Lebenszyklus. Amazon SageMaker ermöglicht es Ihnen, den Zugriff auf die richtigen Daten, Modelle und Entwicklungsartefakte durch den richtigen Benutzer für den richtigen Zweck zu kontrollieren. Definieren und setzen Sie Zugriffsrichtlinien konsistent mithilfe eines einzigen Berechtigungsmodells mit differenzierten Zugriffskontrollen mit dem Amazon-SageMaker-Katalog durch. Sichern und schützen Sie Ihre KI-Modelle mit Datenklassifizierung, Toxizitätserkennung, Integritätsschutz und verantwortungsvollen KI-Richtlinien. Gewinnen Sie Vertrauen in Ihrem gesamten Unternehmen durch Überwachung und Automatisierung der Datenqualität, Erkennung sensibler Daten sowie Daten- und ML-Herkunft. </div> </div> </div> </div> </div> </div> </div> </div> </div> </div></span> </div> </div> </div> <div class="data-attr-wrapper lb-tiny-pad lb-none-v-margin lb-grid" style="padding-top:20px; padding-bottom:20px;" data-da-type="so" data-da-so-category="monitoring" data-da-so-language="de" data-da-so-name="how-it-works" data-da-so-type="viewport" data-da-so-version="3" data-da-so-url="/redshift"> <div class="lb-row lb-row-max-large lb-snap"> <div class="lb-col lb-tiny-24 lb-mid-24"> <h1 id="Meet_the_next_generation_of_SageMaker" class="lb-txt-bold lb-txt-none lb-txt-40 lb-none-v-margin lb-h1 lb-title" style="color:#232F3E; margin-bottom:20px;"> Lernen Sie die nächste Generation von SageMaker</h1> <figure class="lb-img"> <div> <img src="https://d1.awsstatic.com/reInvent/reinvent-2024/amazon-sagemaker/sagemaker_marketecture_final.1284e8075b373120403f8758cfbee2ad507973c1.jpg" alt="" title="" class="cq-dd-image"> </div> </figure> </div> </div> </div> <div data-eb-slot="device-a-classic-cards" data-eb-slot-meta="{'version':'1.0','slotId':'device-a-classic-cards','experienceId':'bd7a2788-9948-11ee-b9d1-0242ac120002','allowBlank':true,'hasAltExp':false,'isRTR':false,'filters':{'limit':10,'query':'(id \u003d \'sagemaker-northstar-capabilities-overview\' OR id \u003d \'sagemaker-northstar-capabilities-1\' OR id \u003d \'sagemaker-northstar-capabilities-2\' OR id \u003d \'sagemaker-northstar-capabilities-3\' OR id \u003d \'sagemaker-northstar-capabilities-4\' OR id \u003d \'sagemaker-northstar-capabilities-5\' OR id \u003d \'sagemaker-northstar-capabilities-6\' OR id \u003d \'sagemaker-northstar-capabilities-7\')'}}"> <div data-eb-tpl-n="awsm-rt/rt-da-classic-card-collection" data-eb-tpl-v="1.0.0" data-eb-ce="" 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<div data-eb-tpl-root="" data-reactroot=""> <div> <div data-rg-lang="de" data-rg-locale="de-DE" lang="de-DE" dir="ltr"> <div data-rg-theme="purple" data-rg-mode="light" data-style-count="0"> <div data-rg-n="GridStack" class="templatecontainer_module_templateContainer__dd3d201a gridStack_module_gridStack__35667094"> <div data-rg-n="Grid" class="grid_module_grid__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col12__66940a30"> <div class="templateHeader_module_templateHeader__b496fe91"> <div data-rg-n="Grid" class="grid_module_grid__590284f4 grid_module_noPadding__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS10__66940a30 col_module_colM8__66940a30 col_module_colL8__66940a30 col_module_colXl8__66940a30 col_module_colXxl8__66940a30"> <h2 data-rg-n="HeadingText" class="basetext_module_text__61099e5e headingtext_module_heading__00ee2f90 headingtext_module_size2__00ee2f90">Funktionsmöglichkeiten</h2> </div> </div> </div> </div> </div> <div data-rg-n="Grid" class="grid_module_grid__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL4__66940a30 col_module_colXl4__66940a30 col_module_colXxl4__66940a30"> <div data-eb-item-id="awt-content-topics#sagemaker-northstar-capabilities-1"> <a data-rg-n="ClassicCard" href="https://aws.amazon.com/sagemaker/unified-studio" data-rigel-analytics="{"name":"Link","properties":{"size":1}}" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c link_module_link__f23c9474 dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 classicCard_module_classicCard__777015e3 classicCard_module_fullHeight__777015e3 bodytext_module_size1__ca32720c bodytext_module_link__ca32720c"> <div> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 classicCard_module_title__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp3__5996b84c titletext_module_size3__e23b0698">Unified Studio (Vorversion)</h3> </div><p data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c classicCard_module_body__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp5__5996b84c bodytext_module_size2__ca32720c">Mit Amazon SageMaker Unified Studio mit all Ihren Daten und Tools für Analytik und KI in einer einzigen Entwicklungsumgebung entwickeln</p> <div class="classicCard_module_footer__777015e3"> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_link__777015e3 utilitytext_module_size3__9ef276a8">Weitere Informationen</span> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_arrow__777015e3 utilitytext_module_size3__9ef276a8"><span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M15.5 8C15.5 8.29 15.38 8.56 15.16 8.75L7.16 15.75L5.84 14.24L11.84 8.99H0.5V6.99H11.84L5.84 1.76L7.16 0.25L15.16 7.25C15.38 7.44 15.5 7.71 15.5 8Z" data-type="fill"></path> </svg></span></span> </div></a> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL4__66940a30 col_module_colXl4__66940a30 col_module_colXxl4__66940a30"> <div data-eb-item-id="awt-content-topics#sagemaker-northstar-capabilities-2"> <a data-rg-n="ClassicCard" href="https://aws.amazon.com/sagemaker/lakehouse" data-rigel-analytics="{"name":"Link","properties":{"size":1}}" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c link_module_link__f23c9474 dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 classicCard_module_classicCard__777015e3 classicCard_module_fullHeight__777015e3 bodytext_module_size1__ca32720c bodytext_module_link__ca32720c"> <div> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 classicCard_module_title__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp3__5996b84c titletext_module_size3__e23b0698">Lakehouse</h3> </div><p data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c classicCard_module_body__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp5__5996b84c bodytext_module_size2__ca32720c">Mit SageMaker Lakehouse den Datenzugriff über Data Lakes von Amazon S3, Amazon Redshift Data Warehouses und Drittanbieter- und Verbunddatenquellen hinweg vereinheitlichen</p> <div class="classicCard_module_footer__777015e3"> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_link__777015e3 utilitytext_module_size3__9ef276a8">Weitere Informationen</span> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_arrow__777015e3 utilitytext_module_size3__9ef276a8"><span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M15.5 8C15.5 8.29 15.38 8.56 15.16 8.75L7.16 15.75L5.84 14.24L11.84 8.99H0.5V6.99H11.84L5.84 1.76L7.16 0.25L15.16 7.25C15.38 7.44 15.5 7.71 15.5 8Z" data-type="fill"></path> </svg></span></span> </div></a> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL4__66940a30 col_module_colXl4__66940a30 col_module_colXxl4__66940a30"> <div data-eb-item-id="awt-content-topics#sagemaker-northstar-capabilities-3"> <a data-rg-n="ClassicCard" href="https://aws.amazon.com/sagemaker/data-ai-governance" data-rigel-analytics="{"name":"Link","properties":{"size":1}}" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c link_module_link__f23c9474 dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 classicCard_module_classicCard__777015e3 classicCard_module_fullHeight__777015e3 bodytext_module_size1__ca32720c bodytext_module_link__ca32720c"> <div> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 classicCard_module_title__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp3__5996b84c titletext_module_size3__e23b0698">Daten- und KI-Governance</h3> </div><p data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c classicCard_module_body__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp5__5996b84c bodytext_module_size2__ca32720c">Mit dem Amazon-SageMaker-Katalog, der auf Amazon DataZone basiert, können Daten und KI sicher entdeckt, verwaltet und gemeinsam genutzt werden</p> <div class="classicCard_module_footer__777015e3"> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_link__777015e3 utilitytext_module_size3__9ef276a8">Weitere Informationen</span> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_arrow__777015e3 utilitytext_module_size3__9ef276a8"><span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M15.5 8C15.5 8.29 15.38 8.56 15.16 8.75L7.16 15.75L5.84 14.24L11.84 8.99H0.5V6.99H11.84L5.84 1.76L7.16 0.25L15.16 7.25C15.38 7.44 15.5 7.71 15.5 8Z" data-type="fill"></path> </svg></span></span> </div></a> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL4__66940a30 col_module_colXl4__66940a30 col_module_colXxl4__66940a30"> <div data-eb-item-id="awt-content-topics#sagemaker-northstar-capabilities-4"> <a data-rg-n="ClassicCard" href="https://aws.amazon.com/sagemaker-ai/" data-rigel-analytics="{"name":"Link","properties":{"size":1}}" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c link_module_link__f23c9474 dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 classicCard_module_classicCard__777015e3 classicCard_module_fullHeight__777015e3 bodytext_module_size1__ca32720c bodytext_module_link__ca32720c"> <div> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 classicCard_module_title__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp3__5996b84c titletext_module_size3__e23b0698">Modellentwicklung</h3> </div><p data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c classicCard_module_body__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp5__5996b84c bodytext_module_size2__ca32720c">Mit Amazon SageMaker AI ML und FMs mit einer vollständig verwalteten Infrastruktur, Tools und Workflows erstellen, trainieren und implementieren</p> <div class="classicCard_module_footer__777015e3"> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_link__777015e3 utilitytext_module_size3__9ef276a8">Weitere 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data-rigel-analytics="{"name":"Link","properties":{"size":1}}" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c link_module_link__f23c9474 dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 classicCard_module_classicCard__777015e3 classicCard_module_fullHeight__777015e3 bodytext_module_size1__ca32720c bodytext_module_link__ca32720c"> <div> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 classicCard_module_title__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp3__5996b84c titletext_module_size3__e23b0698">Generative KI-Anwendungsentwicklung</h3> </div><p data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c classicCard_module_body__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp5__5996b84c bodytext_module_size2__ca32720c">Generative KI-Anwendungen mit Amazon Bedrock erstellen und skalieren</p> <div class="classicCard_module_footer__777015e3"> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_link__777015e3 utilitytext_module_size3__9ef276a8">Weitere Informationen</span> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_arrow__777015e3 utilitytext_module_size3__9ef276a8"><span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M15.5 8C15.5 8.29 15.38 8.56 15.16 8.75L7.16 15.75L5.84 14.24L11.84 8.99H0.5V6.99H11.84L5.84 1.76L7.16 0.25L15.16 7.25C15.38 7.44 15.5 7.71 15.5 8Z" data-type="fill"></path> </svg></span></span> </div></a> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL4__66940a30 col_module_colXl4__66940a30 col_module_colXxl4__66940a30"> <div data-eb-item-id="awt-content-topics#sagemaker-northstar-capabilities-6"> <a data-rg-n="ClassicCard" href="https://aws.amazon.com/redshift/" data-rigel-analytics="{"name":"Link","properties":{"size":1}}" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c link_module_link__f23c9474 dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 classicCard_module_classicCard__777015e3 classicCard_module_fullHeight__777015e3 bodytext_module_size1__ca32720c bodytext_module_link__ca32720c"> <div> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 classicCard_module_title__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp3__5996b84c titletext_module_size3__e23b0698">SQL-Analytik</h3> </div><p data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c classicCard_module_body__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp5__5996b84c bodytext_module_size2__ca32720c">Mit Amazon Redshift, der preisgünstigsten SQL-Engine, Einblicke gewinnen</p> <div class="classicCard_module_footer__777015e3"> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_link__777015e3 utilitytext_module_size3__9ef276a8">Weitere Informationen</span> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_arrow__777015e3 utilitytext_module_size3__9ef276a8"><span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M15.5 8C15.5 8.29 15.38 8.56 15.16 8.75L7.16 15.75L5.84 14.24L11.84 8.99H0.5V6.99H11.84L5.84 1.76L7.16 0.25L15.16 7.25C15.38 7.44 15.5 7.71 15.5 8Z" data-type="fill"></path> </svg></span></span> </div></a> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL4__66940a30 col_module_colXl4__66940a30 col_module_colXxl4__66940a30"> <div data-eb-item-id="awt-content-topics#sagemaker-northstar-capabilities-7"> <a data-rg-n="ClassicCard" href="https://aws.amazon.com/sagemaker/data-processing" data-rigel-analytics="{"name":"Link","properties":{"size":1}}" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c link_module_link__f23c9474 dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 classicCard_module_classicCard__777015e3 classicCard_module_fullHeight__777015e3 bodytext_module_size1__ca32720c bodytext_module_link__ca32720c"> <div> <h3 data-rg-n="TitleText" class="basetext_module_text__61099e5e titletext_module_title__e23b0698 classicCard_module_title__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp3__5996b84c titletext_module_size3__e23b0698">Datenverarbeitung</h3> </div><p data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c classicCard_module_body__777015e3 lineclamp_module_lineClamp__5996b84c lineclamp_module_lineClamp5__5996b84c bodytext_module_size2__ca32720c">Analyse, Vorbereitung und Integration von Daten für Analytik und KI mithilfe von Open-Source-Frameworks in Amazon Athena, Amazon EMR und AWS Glue</p> <div class="classicCard_module_footer__777015e3"> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_link__777015e3 utilitytext_module_size3__9ef276a8">Weitere Informationen</span> <span data-rg-n="UtilityText" class="basetext_module_text__61099e5e utilitytext_module_utility__9ef276a8 classicCard_module_arrow__777015e3 utilitytext_module_size3__9ef276a8"><span class="icon_module_icon__31e1c712 icon_module_sizeS__31e1c712"> <svg role="presentation" xmlns="http://www.w3.org/2000/svg" viewbox="0 0 16 16"> <path d="M15.5 8C15.5 8.29 15.38 8.56 15.16 8.75L7.16 15.75L5.84 14.24L11.84 8.99H0.5V6.99H11.84L5.84 1.76L7.16 0.25L15.16 7.25C15.38 7.44 15.5 7.71 15.5 8Z" data-type="fill"></path> </svg></span></span> </div></a> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div data-eb-slot="device-a-text-media-tabs" data-eb-slot-meta="{'version':'1.0','slotId':'device-a-text-media-tabs','experienceId':'bd7a3c6e-9948-11ee-b9d1-0242ac120002','allowBlank':false,'hasAltExp':false,'isRTR':false,'filters':{'limit':10,'query':'(id \u003d \'sagemaker-northstar-customers\' OR id \u003d \'sagemaker-northstar-customers-1\' OR id \u003d \'sagemaker-northstar-customers-2\' OR id \u003d \'sagemaker-northstar-customers-3\' OR id \u003d \'sagemaker-northstar-customers-4\' OR id \u003d \'sagemaker-northstar-customers-5\')'}}"> <div data-eb-tpl-n="awsm-rt/rt-text-media-tabs" data-eb-tpl-v="1.0.0" data-eb-ce="" data-eb-c-scope="device-a-text-media-tabs" data-eb-d-scope="DIRECTORIES" data-eb-locale="de-DE" data-eb-369baad2="" data-eb-ssr-ce="" data-eb-tpl-ns="awsmRT" data-eb-hydrated="pending"> <script type="application/json">{"data":{"items":[{"fields":{"patternBoolean2":"0","patternBoolean3":"0","itemCustomSortOrder":"1","itemLongLoc":"<p><em>„Zur Bewältigung von isolierten Datensätzen, die in unseren Automobilbetrieben verteilt sind, untersuchen wir Amazon SageMaker, um Daten aus unseren vernetzten Auto-, Vertriebs-, Fertigungs- und Lieferketteneinheiten zu vereinheitlichen und zu verwalten. Dieser Ansatz ermöglicht es uns, Daten mühelos zu suchen, zu entdecken und auszutauschen und so die Grundlage dafür zu schaffen,<strong> </strong>Qualitätsprobleme vorzubeugen, die Sicherheit und Zufriedenheit unserer Kunden zu erhöhen und die Entwicklung generativer KI-Anwendungen zu beschleunigen.“</em></p> \n<p>– <strong>Kamal Distell, VP of Data, Analytics, Platforms, und Data Science, TMNA</strong></p>","itemOption":"right","itemMediaAltText":"image","itemMediaURL":"https://d1.awsstatic.com/customer-references-case-studies-logos/customer-pages_logos/Toyota_Logo@2x.347c668ecbb4d303a8cb17a9f31293a93f1bdce3.png","itemHeading":"Toyota","id":"awt-content-topics#sagemaker-northstar-customers-1","itemTextLoc3":"Toyota","itemBoolean":"0","patternBoolean":"0"},"metadata":{"tags":[]}},{"fields":{"patternBoolean2":"0","patternBoolean3":"0","itemCustomSortOrder":"2","itemLongLoc":"<p><em>„Unser Datenplattform-Engineering-Team hat mehrere Endbenutzertools für Data-Engineering-, ML-, SQL- und GenKI-Aufgaben eingesetzt. Da wir versuchen, die Prozesse in der gesamten Bank zu vereinfachen, haben wir uns mit der Optimierung der Benutzerauthentifizierung und der Datenzugriffsautorisierung befasst. Amazon SageMaker bietet ein vorgefertigtes Benutzererlebnis, das uns hilft, eine einzige Umgebung im gesamten Unternehmen bereitzustellen. Dadurch wird die Zeit, die unsere Datennutzer für den Zugriff auf neue Tools benötigen, um etwa 50 % reduziert.“</em></p> \n<p><strong>– Zachery Anderson, CDAO, NatWest Group</strong></p>","itemMediaAltText":"image","itemOption":"right","itemMediaURL":"https://d1.awsstatic.com/natwest.6c3c44e62d604c4ccdb084465cd1a8d557dc3c26.png","itemHeading":"NatWest Group","id":"awt-content-topics#sagemaker-northstar-customers-2","itemTextLoc3":"NatWest Group","itemBoolean":"0","patternBoolean":"0"},"metadata":{"tags":[]}},{"fields":{"patternBoolean2":"0","patternBoolean3":"0","itemCustomSortOrder":"3","itemLongLoc":"<p><em>„Wir haben Amazon Redshift verwendet, um Erkenntnisse aus strukturierten und halbstrukturierten Daten in all unseren Daten-Repositorys zu gewinnen. Das neue Amazon SageMaker Lakehouse begeistert mich mit seinem Potenzial, den Zugriff auf Data Lake und andere Datenquellen mit Services wie Amazon Redshift, Glue-Datenkatalog und Lake Formation zu verbessern und zu vereinheitlichen. Diese Innovation wird es unseren Daten- und Entwicklungsteams ermöglichen, den Datenzugriff zu vereinfachen und die Interoperabilität zwischen Daten-, Analytik- und Anwendungs-Workloads zu fördern. Ich rechne mit einer deutlichen Verringerung von Datenfehlern durch weniger Datenkopien, eine Verringerung der Verarbeitungszeit um 40 %, ein schnelleres Write-Back von Analytikdaten in Transaktionssysteme zur Verbesserung der Entscheidungsfindung und die Möglichkeit für unsere Teams, sich auf die Schaffung von Geschäftswerten zu konzentrieren.“</em></p> \n<p><strong>– Yannick Misteli, Head of Engineering, Global Product Strategy, Roche</strong></p>","itemMediaAltText":"image","itemOption":"right","itemMediaURL":"https://d1.awsstatic.com/customer-references-case-studies-logos/customer-pages_logos/Roche_Logo.2e7e63eadfaf9e037e90903b8478cbdb085041ab.png","itemHeading":"Roche","id":"awt-content-topics#sagemaker-northstar-customers-3","itemTextLoc3":"Roche","itemBoolean":"0","patternBoolean":"0"},"metadata":{"tags":[]}},{"fields":{"itemCustomSortOrder":"4","itemLongLoc":"<p><em>„Wir haben die letzten 18 Monate damit verbracht, mit AWS zusammenzuarbeiten, um unsere Datenbasis so zu transformieren, dass wir erstklassige Lösungen verwenden können, die auch kostengünstig sind. Mit Fortschritten wie Amazon SageMaker Unified Studio und Amazon SageMaker Lakehouse gehen wir davon aus, dass wir unsere Liefergeschwindigkeit durch den nahtlosen Zugriff auf Daten und Services beschleunigen werden, sodass unsere Ingenieure, Analysten und Wissenschaftler Einblicke gewinnen können, die für unser Unternehmen von erheblichem Wert sind.“</em></p> \n<p><strong>– Lee Slezak, SVP of Data and Analytic, Lennar</strong></p>","itemMediaAltText":"image","itemOption":"right","itemMediaURL":"https://d1.awsstatic.com/customer-references-case-studies-logos/customer-pages_logos/Lennar_Logo@2x.aaf32b90b24e71ebdb16237f1b8c85bd2d27a781.png","itemHeading":"Lennar","id":"awt-content-topics#sagemaker-northstar-customers-4","itemTextLoc3":"Lennar"},"metadata":{"tags":[]}},{"fields":{"patternBoolean2":"0","patternBoolean3":"0","itemCustomSortOrder":"5","itemLongLoc":"<p><em>„Unser Unternehmen nutzt Amazon DataZone, Amazon SageMaker AI, Amazon Athena und Amazon Redshift, um unsere klinischen und genomischen Daten zu verwalten und zu analysieren. Wir freuen uns über die nun vereinheitlichte Governance des Amazon-SageMaker-Katalogs, die unsere Datenermittlung und den Datenzugriff optimieren wird und es unserem Team ermöglicht, relevante Daten in unserem gesamten Bereich schnell zu analysieren. Diese Integration wird uns dabei helfen, maßgeschneiderte Datensätze zu erstellen, die Zeit bis zur Gewinnung von Erkenntnissen möglicherweise zu verkürzen und letztlich die Patientenergebnisse zu verbessern, während wir unserem Ziel näher kommen, personalisierte Gentests zu einem Standard in der Versorgung zu machen.“</em></p> \n<p><strong>– Mirko Buholzer, VP of Software Engineering, Natera, Inc.</strong></p>","itemMediaAltText":"image","itemOption":"right","itemMediaURL":"https://d1.awsstatic.com/datazone-assets/Natera_logo.5fe40615947a1160135582bb046731676bbcd4bb.png","itemHeading":"Natera, Inc","id":"awt-content-topics#sagemaker-northstar-customers-5","itemTextLoc3":"Natera, 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<div data-eb-tpl-root="" data-reactroot=""> <span data-eb-item-id="awt-content-topics#sagemaker-northstar-customers"> <div data-rg-lang="de" data-rg-locale="de-DE" lang="de-DE" dir="ltr"> <div data-rg-theme="teal" data-rg-mode="light" data-style-count="0"> <div data-rg-n="GridStack" class="templatecontainer_module_templateContainer__dd3d201a gridStack_module_gridStack__35667094"> <div data-rg-n="Grid" class="grid_module_grid__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col12__66940a30"> <div class="templateHeader_module_templateHeader__b496fe91"> <div data-rg-n="Grid" class="grid_module_grid__590284f4 grid_module_noPadding__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS10__66940a30 col_module_colM8__66940a30 col_module_colL8__66940a30 col_module_colXl8__66940a30 col_module_colXxl8__66940a30"> <h2 data-rg-n="HeadingText" class="basetext_module_text__61099e5e headingtext_module_heading__00ee2f90 headingtext_module_size2__00ee2f90">Kunden</h2> </div> </div> </div> </div> </div> <div data-rg-n="Grid" class="grid_module_grid__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col12__66940a30"> <div data-rg-n="Grid" class="tabs_module_tabs__05d921ca grid_module_grid__590284f4 grid_module_noPadding__590284f4" style="--panel-width:100%;--scroller-offset:0;--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col12__66940a30 tabs_module_wrapper__05d921ca"> <div class="tabs_module_tabsViewport__05d921ca"> <div> <div data-rg-theme="teal" data-rg-mode="light" data-style-count="0"> <div class="tablist_module_tabList__515d0ebb"> <div role="presentation" aria-hidden="true" style="--tab-indicator-x:0px;--tab-indicator-width:0px" class="backgroundGradient_module_backgroundGradient__7e2959cb backgroundGradient_module_variantA__7e2959cb tablist_module_indicator__515d0ebb"></div> <ul role="tablist"> <li class="tablist_module_tab__515d0ebb" role="none presentation"><button role="tab" tabindex="0" aria-selected="true" id="tab-undefined-awt-content-topics#sagemaker-northstar-customers-1" aria-controls="tabpanel-undefined-awt-content-topics#sagemaker-northstar-customers-1" type="button" class="dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 dropShadow_module_disabled__0e93b107 buttonbase_module_buttonBase__efa86cab buttonbase_module_tertiary__efa86cab button_module_button__f561bac2"><span data-rg-n="UtilityText" class="basetext_module_text__61099e5e basetext_module_center__61099e5e utilitytext_module_utility__9ef276a8 button_module_content__f561bac2 utilitytext_module_size3__9ef276a8">Toyota</span></button></li> <li 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id="tab-undefined-awt-content-topics#sagemaker-northstar-customers-3" aria-controls="tabpanel-undefined-awt-content-topics#sagemaker-northstar-customers-3" type="button" class="dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 dropShadow_module_disabled__0e93b107 buttonbase_module_buttonBase__efa86cab buttonbase_module_tertiary__efa86cab button_module_button__f561bac2"><span data-rg-n="UtilityText" class="basetext_module_text__61099e5e basetext_module_center__61099e5e utilitytext_module_utility__9ef276a8 button_module_content__f561bac2 utilitytext_module_size3__9ef276a8">Roche</span></button></li> <li class="tablist_module_tab__515d0ebb" role="none presentation"><button role="tab" tabindex="-1" aria-selected="false" id="tab-undefined-awt-content-topics#sagemaker-northstar-customers-4" aria-controls="tabpanel-undefined-awt-content-topics#sagemaker-northstar-customers-4" type="button" class="dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 dropShadow_module_disabled__0e93b107 buttonbase_module_buttonBase__efa86cab buttonbase_module_tertiary__efa86cab button_module_button__f561bac2"><span data-rg-n="UtilityText" class="basetext_module_text__61099e5e basetext_module_center__61099e5e utilitytext_module_utility__9ef276a8 button_module_content__f561bac2 utilitytext_module_size3__9ef276a8">Lennar</span></button></li> <li class="tablist_module_tab__515d0ebb" role="none presentation"><button role="tab" tabindex="-1" aria-selected="false" id="tab-undefined-awt-content-topics#sagemaker-northstar-customers-5" aria-controls="tabpanel-undefined-awt-content-topics#sagemaker-northstar-customers-5" type="button" class="dropShadow_module_shadow__0e93b107 dropShadow_module_themed__0e93b107 dropShadow_module_onHover__0e93b107 dropShadow_module_pressable__0e93b107 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grid_module_fullWidth__590284f4 grid_module_noPadding__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" data-text-form="long" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL6__66940a30 col_module_colXl6__66940a30 col_module_colXxl6__66940a30 textmediacontent_module_textContainer__d28b7a4a"> <h3 data-rg-n="HeadingText" class="basetext_module_text__61099e5e headingtext_module_heading__00ee2f90 textmediacontent_module_heading__d28b7a4a headingtext_module_size3__00ee2f90">Toyota</h3> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c bodytext_module_size2__ca32720c"> <p><em>„Zur Bewältigung von isolierten Datensätzen, die in unseren Automobilbetrieben verteilt sind, untersuchen wir Amazon SageMaker, um Daten aus unseren vernetzten Auto-, Vertriebs-, Fertigungs- und Lieferketteneinheiten zu vereinheitlichen und zu verwalten. Dieser Ansatz ermöglicht es uns, Daten mühelos zu suchen, zu entdecken und auszutauschen und so die Grundlage dafür zu schaffen,<strong> </strong>Qualitätsprobleme vorzubeugen, die Sicherheit und Zufriedenheit unserer Kunden zu erhöhen und die Entwicklung generativer KI-Anwendungen zu beschleunigen.“</em></p> <p>– <strong>Kamal Distell, VP of Data, Analytics, Platforms, und Data Science, TMNA</strong></p> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col1__66940a30 textmediacontent_module_spacer__d28b7a4a"></div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM5__66940a30 col_module_colL5__66940a30 col_module_colXl5__66940a30 col_module_colXxl5__66940a30 textmediacontent_module_mediaContainer__d28b7a4a"> <img class="image_module_image__0914b1c0" src="https://d1.awsstatic.com/customer-references-case-studies-logos/customer-pages_logos/Toyota_Logo@2x.347c668ecbb4d303a8cb17a9f31293a93f1bdce3.png" alt="image" loading="lazy"> </div> </div> </div> <div class="tabs_module_tabPanel__05d921ca" role="tabpanel" id="tabpanel-undefined-awt-content-topics#sagemaker-northstar-customers-2" tabindex="-1" aria-labelledby="tab-undefined-awt-content-topics#sagemaker-northstar-customers-2"> <div data-rg-n="TextMediaContent" data-media-position="end" class="textmediacontent_module_textMediaContent__d28b7a4a grid_module_grid__590284f4 grid_module_fullWidth__590284f4 grid_module_noPadding__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" data-text-form="long" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL6__66940a30 col_module_colXl6__66940a30 col_module_colXxl6__66940a30 textmediacontent_module_textContainer__d28b7a4a"> <h3 data-rg-n="HeadingText" class="basetext_module_text__61099e5e headingtext_module_heading__00ee2f90 textmediacontent_module_heading__d28b7a4a headingtext_module_size3__00ee2f90">NatWest Group</h3> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c bodytext_module_size2__ca32720c"> <p><em>„Unser Datenplattform-Engineering-Team hat mehrere Endbenutzertools für Data-Engineering-, ML-, SQL- und GenKI-Aufgaben eingesetzt. Da wir versuchen, die Prozesse in der gesamten Bank zu vereinfachen, haben wir uns mit der Optimierung der Benutzerauthentifizierung und der Datenzugriffsautorisierung befasst. Amazon SageMaker bietet ein vorgefertigtes Benutzererlebnis, das uns hilft, eine einzige Umgebung im gesamten Unternehmen bereitzustellen. Dadurch wird die Zeit, die unsere Datennutzer für den Zugriff auf neue Tools benötigen, um etwa 50 % reduziert.“</em></p> <p><strong>– Zachery Anderson, CDAO, NatWest Group</strong></p> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col1__66940a30 textmediacontent_module_spacer__d28b7a4a"></div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM5__66940a30 col_module_colL5__66940a30 col_module_colXl5__66940a30 col_module_colXxl5__66940a30 textmediacontent_module_mediaContainer__d28b7a4a"> <img class="image_module_image__0914b1c0" src="https://d1.awsstatic.com/natwest.6c3c44e62d604c4ccdb084465cd1a8d557dc3c26.png" alt="image" loading="lazy"> </div> </div> </div> <div class="tabs_module_tabPanel__05d921ca" role="tabpanel" id="tabpanel-undefined-awt-content-topics#sagemaker-northstar-customers-3" tabindex="-1" aria-labelledby="tab-undefined-awt-content-topics#sagemaker-northstar-customers-3"> <div data-rg-n="TextMediaContent" data-media-position="end" class="textmediacontent_module_textMediaContent__d28b7a4a grid_module_grid__590284f4 grid_module_fullWidth__590284f4 grid_module_noPadding__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" data-text-form="long" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL6__66940a30 col_module_colXl6__66940a30 col_module_colXxl6__66940a30 textmediacontent_module_textContainer__d28b7a4a"> <h3 data-rg-n="HeadingText" class="basetext_module_text__61099e5e headingtext_module_heading__00ee2f90 textmediacontent_module_heading__d28b7a4a headingtext_module_size3__00ee2f90">Roche</h3> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c bodytext_module_size2__ca32720c"> <p><em>„Wir haben Amazon Redshift verwendet, um Erkenntnisse aus strukturierten und halbstrukturierten Daten in all unseren Daten-Repositorys zu gewinnen. Das neue Amazon SageMaker Lakehouse begeistert mich mit seinem Potenzial, den Zugriff auf Data Lake und andere Datenquellen mit Services wie Amazon Redshift, Glue-Datenkatalog und Lake Formation zu verbessern und zu vereinheitlichen. Diese Innovation wird es unseren Daten- und Entwicklungsteams ermöglichen, den Datenzugriff zu vereinfachen und die Interoperabilität zwischen Daten-, Analytik- und Anwendungs-Workloads zu fördern. Ich rechne mit einer deutlichen Verringerung von Datenfehlern durch weniger Datenkopien, eine Verringerung der Verarbeitungszeit um 40 %, ein schnelleres Write-Back von Analytikdaten in Transaktionssysteme zur Verbesserung der Entscheidungsfindung und die Möglichkeit für unsere Teams, sich auf die Schaffung von Geschäftswerten zu konzentrieren.“</em></p> <p><strong>– Yannick Misteli, Head of Engineering, Global Product Strategy, Roche</strong></p> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col1__66940a30 textmediacontent_module_spacer__d28b7a4a"></div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM5__66940a30 col_module_colL5__66940a30 col_module_colXl5__66940a30 col_module_colXxl5__66940a30 textmediacontent_module_mediaContainer__d28b7a4a"> <img class="image_module_image__0914b1c0" src="https://d1.awsstatic.com/customer-references-case-studies-logos/customer-pages_logos/Roche_Logo.2e7e63eadfaf9e037e90903b8478cbdb085041ab.png" alt="image" loading="lazy"> </div> </div> </div> <div class="tabs_module_tabPanel__05d921ca" role="tabpanel" id="tabpanel-undefined-awt-content-topics#sagemaker-northstar-customers-4" tabindex="-1" aria-labelledby="tab-undefined-awt-content-topics#sagemaker-northstar-customers-4"> <div data-rg-n="TextMediaContent" data-media-position="end" class="textmediacontent_module_textMediaContent__d28b7a4a grid_module_grid__590284f4 grid_module_fullWidth__590284f4 grid_module_noPadding__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" data-text-form="long" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL6__66940a30 col_module_colXl6__66940a30 col_module_colXxl6__66940a30 textmediacontent_module_textContainer__d28b7a4a"> <h3 data-rg-n="HeadingText" class="basetext_module_text__61099e5e headingtext_module_heading__00ee2f90 textmediacontent_module_heading__d28b7a4a headingtext_module_size3__00ee2f90">Lennar</h3> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c bodytext_module_size2__ca32720c"> <p><em>„Wir haben die letzten 18 Monate damit verbracht, mit AWS zusammenzuarbeiten, um unsere Datenbasis so zu transformieren, dass wir erstklassige Lösungen verwenden können, die auch kostengünstig sind. Mit Fortschritten wie Amazon SageMaker Unified Studio und Amazon SageMaker Lakehouse gehen wir davon aus, dass wir unsere Liefergeschwindigkeit durch den nahtlosen Zugriff auf Daten und Services beschleunigen werden, sodass unsere Ingenieure, Analysten und Wissenschaftler Einblicke gewinnen können, die für unser Unternehmen von erheblichem Wert sind.“</em></p> <p><strong>– Lee Slezak, SVP of Data and Analytic, Lennar</strong></p> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col1__66940a30 textmediacontent_module_spacer__d28b7a4a"></div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM5__66940a30 col_module_colL5__66940a30 col_module_colXl5__66940a30 col_module_colXxl5__66940a30 textmediacontent_module_mediaContainer__d28b7a4a"> <img class="image_module_image__0914b1c0" src="https://d1.awsstatic.com/customer-references-case-studies-logos/customer-pages_logos/Lennar_Logo@2x.aaf32b90b24e71ebdb16237f1b8c85bd2d27a781.png" alt="image" loading="lazy"> </div> </div> </div> <div class="tabs_module_tabPanel__05d921ca" role="tabpanel" id="tabpanel-undefined-awt-content-topics#sagemaker-northstar-customers-5" tabindex="-1" aria-labelledby="tab-undefined-awt-content-topics#sagemaker-northstar-customers-5"> <div data-rg-n="TextMediaContent" data-media-position="end" class="textmediacontent_module_textMediaContent__d28b7a4a grid_module_grid__590284f4 grid_module_fullWidth__590284f4 grid_module_noPadding__590284f4" style="--rg-grid-gap:var(--rg-margin-3)"> <div data-rg-n="Col" data-text-form="long" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM6__66940a30 col_module_colL6__66940a30 col_module_colXl6__66940a30 col_module_colXxl6__66940a30 textmediacontent_module_textContainer__d28b7a4a"> <h3 data-rg-n="HeadingText" class="basetext_module_text__61099e5e headingtext_module_heading__00ee2f90 textmediacontent_module_heading__d28b7a4a headingtext_module_size3__00ee2f90">Natera, Inc</h3> <div data-rg-n="BodyText" class="basetext_module_text__61099e5e bodytext_module_body__ca32720c bodytext_module_size2__ca32720c"> <p><em>„Unser Unternehmen nutzt Amazon DataZone, Amazon SageMaker AI, Amazon Athena und Amazon Redshift, um unsere klinischen und genomischen Daten zu verwalten und zu analysieren. Wir freuen uns über die nun vereinheitlichte Governance des Amazon-SageMaker-Katalogs, die unsere Datenermittlung und den Datenzugriff optimieren wird und es unserem Team ermöglicht, relevante Daten in unserem gesamten Bereich schnell zu analysieren. Diese Integration wird uns dabei helfen, maßgeschneiderte Datensätze zu erstellen, die Zeit bis zur Gewinnung von Erkenntnissen möglicherweise zu verkürzen und letztlich die Patientenergebnisse zu verbessern, während wir unserem Ziel näher kommen, personalisierte Gentests zu einem Standard in der Versorgung zu machen.“</em></p> <p><strong>– Mirko Buholzer, VP of Software Engineering, Natera, Inc.</strong></p> </div> </div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_col1__66940a30 textmediacontent_module_spacer__d28b7a4a"></div> <div data-rg-n="Col" class="col_module_col__66940a30 col_module_colXs12__66940a30 col_module_colS12__66940a30 col_module_colM5__66940a30 col_module_colL5__66940a30 col_module_colXl5__66940a30 col_module_colXxl5__66940a30 textmediacontent_module_mediaContainer__d28b7a4a"> <img class="image_module_image__0914b1c0" src="https://d1.awsstatic.com/datazone-assets/Natera_logo.5fe40615947a1160135582bb046731676bbcd4bb.png" alt="image" loading="lazy"> 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