{"id":30036,"date":"2026-02-09T05:01:56","date_gmt":"2026-02-09T05:01:56","guid":{"rendered":"https:\/\/nekudos.com\/sap-ai-use-case-secimi\/"},"modified":"2026-02-09T05:02:10","modified_gmt":"2026-02-09T05:02:10","slug":"sap-ai-use-case-secimi","status":"publish","type":"post","link":"https:\/\/nekudos.com\/en\/sap-ai-use-case-secimi\/","title":{"rendered":"SAP AI Use Case Seciminde Dogru Veri ve Is Hedefi Uyumu"},"content":{"rendered":"

H1: SAP AI Use Case Nas\u0131l Se\u00e7ilir<\/strong><\/h3>\n
\n

Giri\u015f<\/strong><\/h3>\n

SAP ortam\u0131nda do\u011fru AI use case<\/strong> se\u00e7imi, yapay zekan\u0131n stratejik olarak de\u011fer yaratmas\u0131n\u0131 sa\u011flar. Bir\u00e7ok kurum AI yat\u0131r\u0131m\u0131 yaparken hangi s\u00fcrecin otomasyon, tahmin veya karar destek a\u00e7\u0131s\u0131ndan en fazla fayda getirece\u011fini belirlemekte zorlan\u0131r. Bu yaz\u0131, SAP ekosisteminde etkili bir sap ai use case<\/strong> se\u00e7imi i\u00e7in teknik ve karar verici d\u00fczeyde bir \u00e7er\u00e7eve sunar.<\/p>\n

\n

H2: SAP AI Use Case Nas\u0131l Se\u00e7ilir tan\u0131m\u0131<\/strong><\/h3>\n

SAP AI use case<\/strong>, SAP sistemlerinde (\u00f6rne\u011fin S\/4HANA, SuccessFactors, BTP) yapay zekan\u0131n belirli bir i\u015f s\u00fcrecine entegre edilmesi anlam\u0131na gelir. Bu bir chatbot, tahminleme modeli, anomali tespiti veya s\u00fcre\u00e7 otomasyonu olabilir. Ama\u00e7, i\u015f kararlar\u0131n\u0131 veri temelli hale getirmek ve operasyonel verimlili\u011fi art\u0131rmakt\u0131r.<\/p>\n

\n

H2: sap ai use case nas\u0131l \u00e7al\u0131\u015f\u0131r<\/strong><\/h3>\n

Bir sap ai use case<\/strong>, i\u015f s\u00fcrecinin veri ak\u0131\u015f\u0131n\u0131 analiz eder, ilgili SAP mod\u00fcl\u00fcnden gelen verileri i\u015fler ve sonu\u00e7lar\u0131 tekrar ERP sistemine geri yazar. Burada temel yap\u0131 ta\u015flar\u0131 veri kayna\u011f\u0131, model tasar\u0131m\u0131, entegrasyon katman\u0131 ve izleme mekanizmas\u0131d\u0131r.<\/p>\n

Temel parametreler ve ayarlar<\/strong><\/h4>\n
    \n
  • Veri seti se\u00e7imi:<\/strong> AI modelinin ba\u015far\u0131s\u0131, do\u011fru SAP tablolar\u0131ndan \u00e7ekilen kaliteli veriye ba\u011fl\u0131d\u0131r. <\/li>\n
  • Model tipi:<\/strong> Regresyon, s\u0131n\u0131fland\u0131rma veya NLP; s\u00fcrecin do\u011fas\u0131na g\u00f6re belirlenir. <\/li>\n
  • BTP servis konfig\u00fcrasyonu:<\/strong> SAP AI Core, AI Launchpad gibi servislerde API eri\u015fimi, g\u00fcvenlik tokenleri ve performans parametreleri do\u011fru ayarlanmal\u0131d\u0131r.<\/li>\n<\/ul>\n

    S\u0131k yap\u0131lan hatalar ve ka\u00e7\u0131nma y\u00f6ntemleri<\/strong><\/h4>\n
      \n
    • Veri kalitesini ihmal etmek:<\/strong> Eksik veya tutars\u0131z SAP verileri tahmin do\u011frulu\u011funu d\u00fc\u015f\u00fcr\u00fcr. <\/li>\n
    • Yanl\u0131\u015f KPI belirlemek:<\/strong> Use case se\u00e7iminde sadece teknik metriklere de\u011fil, i\u015f etkisine de odaklanmak gerekir. <\/li>\n
    • Modeli sistemden ba\u011f\u0131ms\u0131z d\u00fc\u015f\u00fcnmek:<\/strong> AI \u00e7\u00f6z\u00fcm\u00fc SAP s\u00fcre\u00e7lerine entegre edilmedi\u011finde operasyonel etki zay\u0131f olur.<\/li>\n<\/ul>\n

      Ger\u00e7ek sistemlerde uygulama \u00f6rnekleri<\/strong><\/h4>\n

      \u00d6rne\u011fin, SAP MM mod\u00fcl\u00fcnde tedarik\u00e7i teslimat s\u00fcrelerinin tahmini i\u00e7in AI modeli kullan\u0131l\u0131r. Model, ge\u00e7mi\u015f sevkiyat verilerini analiz edip gecikme olas\u0131l\u0131\u011f\u0131n\u0131 \u00f6ng\u00f6r\u00fcr. Sonu\u00e7lar, sat\u0131n alma s\u00fcre\u00e7lerinde otomatik uyar\u0131 ve alternatif planlama \u00f6nerileri \u00fcretir.<\/p>\n

      \n

      H2: Teknik a\u00e7\u0131klama (derin seviye)<\/strong><\/h3>\n

      Bir sap ai use case<\/strong> tasar\u0131m s\u00fcreci genellikle \u015fu ad\u0131mlarla ilerler:<\/p>\n

        \n
      1. Veri ak\u0131\u015f\u0131 modellemesi:<\/strong> SAP BTP Data Intelligence \u00fczerinden kaynak veriler toplan\u0131r. <\/li>\n
      2. Model e\u011fitimi:<\/strong> Python, TensorFlow veya SAP AI Core ortam\u0131nda yap\u0131l\u0131r. <\/li>\n
      3. Entegrasyon:<\/strong> REST API veya OData servisleriyle SAP ERP\u2019ye sonu\u00e7 aktar\u0131m\u0131. <\/li>\n
      4. \u0130zleme ve geri bildirim:<\/strong> Modeller SAP AI Launchpad \u00fczerinden performans a\u00e7\u0131s\u0131ndan izlenir.<\/li>\n<\/ol>\n

        Teknik olarak, model \u00e7\u0131kt\u0131lar\u0131 SAP Workflow Management ile otomatik s\u00fcre\u00e7 tetiklemeye ba\u011flanabilir. Bu yap\u0131, AI modelinin ger\u00e7ek zamanl\u0131 karar deste\u011fi vermesini sa\u011flar. AI strategy yakla\u015f\u0131m\u0131 burada \u00f6nemlidir; ama\u00e7 y\u0131ll\u0131k hedefleri bireysel use case\u2019lere d\u00f6n\u00fc\u015ft\u00fcrmektir.<\/p>\n

        \n

        H2: \u0130\u015fletmeler i\u00e7in neden kritiktir<\/strong><\/h3>\n
          \n
        • Performans iyile\u015ftirmesi: S\u00fcre\u00e7 d\u00f6ng\u00fcleri k\u0131sal\u0131r. <\/li>\n
        • G\u00fcvenilirlik: Tahmin hatalar\u0131 azal\u0131r, risk analizi g\u00fc\u00e7lenir. <\/li>\n
        • Maliyet optimizasyonu: Gereksiz kaynak kullan\u0131m\u0131 \u00f6nlenir. <\/li>\n
        • \u00d6l\u00e7ekleme esnekli\u011fi: Yeni SAP mod\u00fclleri i\u00e7in kolay geni\u015fleme sa\u011flan\u0131r. <\/li>\n
        • Otomasyon: Tekrarlayan i\u015flemler AI ile y\u00fcr\u00fct\u00fcl\u00fcr. <\/li>\n
        • Karar alma: Ger\u00e7ek zamanl\u0131 verilere dayal\u0131 karar s\u00fcre\u00e7leri h\u0131zlan\u0131r. <\/li>\n
        • Operasyonel verimlilik: \u0130nsan m\u00fcdahalesi azal\u0131r, sistem tutarl\u0131l\u0131\u011f\u0131 artar.<\/li>\n<\/ul>\n
          \n

          H2: Bu kavram NeKuDos Teknoloji i\u00e7inde nas\u0131l uygulan\u0131r<\/strong><\/h3>\n

          NeKuDos Teknoloji projelerinde sap ai use case<\/strong> se\u00e7imi, veri eri\u015fimi ve entegrasyon mimarisi \u00fczerinden y\u00fcr\u00fct\u00fcl\u00fcr. SAP BTP \u00fczerinde AI Core ve Data Intelligence servislerinin birlikte kullan\u0131ld\u0131\u011f\u0131 mimariler tercih edilir. \u00d6rne\u011fin, \u00fcretim hatalar\u0131nda anomali tespiti i\u00e7in ge\u00e7mi\u015f sens\u00f6r verileri analiz edilir, model \u00e7\u0131kt\u0131lar\u0131 otomatik bak\u0131m s\u00fcrecine entegre edilir. B\u00f6ylece AI strategy verimlili\u011fi i\u015f hedefleriyle hizalan\u0131r.<\/p>\n

          \n

          H2: SAP dan\u0131\u015fmanlar\u0131, IT y\u00f6neticileri, CTOlar i\u00e7in ger\u00e7ek bir senaryo<\/strong><\/h3>\n
            \n
          1. Sorun:<\/strong> Stok y\u00f6netiminde s\u00fcrekli fazla sipari\u015fler meydana geliyor. <\/li>\n
          2. Ba\u011flam:<\/strong> SAP S\/4HANA kullan\u0131m\u0131 mevcut, ancak hangi kalemlerin fazla sipari\u015f edildi\u011fi anl\u0131k izlenemiyor. <\/li>\n
          3. Kavram\u0131n uygulanmas\u0131:<\/strong> Bir sap ai use case<\/strong> olu\u015fturularak ge\u00e7mi\u015f sat\u0131n alma hareketleri analiz ediliyor, AI modeli talep tahminini optimize ediyor. <\/li>\n
          4. Sonu\u00e7:<\/strong> Fazla sipari\u015f oran\u0131 %20 azal\u0131yor, ERP otomatik stok uyar\u0131lar\u0131 veriyor. <\/li>\n
          5. \u0130\u015f etkisi:<\/strong> Maliyet d\u00fc\u015f\u00fcyor, tedarik zinciri dengeleniyor, karar s\u00fcreci h\u0131zlan\u0131yor.<\/li>\n<\/ol>\n
            \n

            H2: S\u0131k yap\u0131lan hatalar ve en iyi uygulamalar<\/strong><\/h3>\n

            Hatalar:<\/strong><\/p>\n

              \n
            • Veriyi AI sistemine aktarmadan \u00f6nce SAP eri\u015fim izinlerini g\u00f6z ard\u0131 etmek. <\/li>\n
            • Use case\u2019i sadece IT bak\u0131\u015f\u0131yla de\u011ferlendirmek, i\u015f birimlerinin katk\u0131s\u0131n\u0131 d\u0131\u015flamak. <\/li>\n
            • Deneme modellerini canl\u0131 ortamda yeterli test olmadan yay\u0131nlamak.<\/li>\n<\/ul>\n

              En iyi uygulamalar:<\/strong><\/p>\n

                \n
              • Use case se\u00e7iminde hem teknik hem i\u015f KPI\u2019lar\u0131n\u0131 tan\u0131mlamak. <\/li>\n
              • SAP BTP ortam\u0131nda mod\u00fcler mimariyle ilerlemek. <\/li>\n
              • S\u00fcrekli model izleme ve yeniden e\u011fitim mekanizmas\u0131 kullanmak. <\/li>\n
              • AI strategy dok\u00fcman\u0131n\u0131 \u015firket hedefleriyle uyumlu tutmak.<\/li>\n<\/ul>\n
                \n

                Sonu\u00e7<\/strong><\/h3>\n

                Do\u011fru sap ai use case<\/strong> se\u00e7imi, SAP ekosisteminde yapay zekay\u0131 \u00f6l\u00e7eklenebilir ve somut de\u011fer \u00fcreten bir unsura d\u00f6n\u00fc\u015ft\u00fcr\u00fcr. S\u00fcre\u00e7 se\u00e7iminde veri kalitesi, entegrasyon kabiliyeti ve i\u015f hedefleri uyumu temel belirleyicilerdir. NeKuDos Teknoloji\u2019nin yakla\u015f\u0131m\u0131 bu kriterleri teknik mimariyle birle\u015ftirerek AI yat\u0131r\u0131mlar\u0131n\u0131n s\u00fcrd\u00fcr\u00fclebilir ba\u015far\u0131s\u0131n\u0131 sa\u011flar.<\/p>","protected":false},"excerpt":{"rendered":"

                H1: SAP AI Use Case Nas\u0131l Se\u00e7ilir Giri\u015f SAP ortam\u0131nda do\u011fru AI use case se\u00e7imi, yapay zekan\u0131n stratejik olarak de\u011fer yaratmas\u0131n\u0131 sa\u011flar. Bir\u00e7ok kurum AI yat\u0131r\u0131m\u0131 yaparken hangi s\u00fcrecin otomasyon, tahmin veya karar destek a\u00e7\u0131s\u0131ndan en fazla fayda getirece\u011fini belirlemekte zorlan\u0131r. Bu yaz\u0131, SAP ekosisteminde etkili bir sap ai use case se\u00e7imi i\u00e7in teknik ve…<\/p>","protected":false},"author":2,"featured_media":30037,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_sitemap_exclude":false,"_sitemap_priority":"","_sitemap_frequency":"","footnotes":""},"categories":[122],"tags":[],"class_list":["post-30036","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sap","category-122","description-off"],"yoast_head":"\nSAP AI Use Case Seciminde Dogru Veri ve Is Hedefi Uyumu - NeKuDos Teknoloji<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/nekudos.com\/en\/sap-ai-use-case-secimi\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"SAP AI Use Case Seciminde Dogru Veri ve Is Hedefi Uyumu - NeKuDos Teknoloji\" \/>\n<meta property=\"og:description\" content=\"H1: SAP AI Use Case Nas\u0131l Se\u00e7ilir Giri\u015f SAP ortam\u0131nda do\u011fru AI use case se\u00e7imi, yapay zekan\u0131n stratejik olarak de\u011fer yaratmas\u0131n\u0131 sa\u011flar. Bir\u00e7ok kurum AI yat\u0131r\u0131m\u0131 yaparken hangi s\u00fcrecin otomasyon, tahmin veya karar destek a\u00e7\u0131s\u0131ndan en fazla fayda getirece\u011fini belirlemekte zorlan\u0131r. 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Bir\u00e7ok kurum AI yat\u0131r\u0131m\u0131 yaparken hangi s\u00fcrecin otomasyon, tahmin veya karar destek a\u00e7\u0131s\u0131ndan en fazla fayda getirece\u011fini belirlemekte zorlan\u0131r. Bu yaz\u0131, SAP ekosisteminde etkili bir sap ai use case se\u00e7imi i\u00e7in teknik ve…","og_url":"https:\/\/nekudos.com\/en\/sap-ai-use-case-secimi\/","og_site_name":"NeKuDos Teknoloji","article_published_time":"2026-02-09T05:01:56+00:00","article_modified_time":"2026-02-09T05:02:10+00:00","author":"Serkan \u00d6zcan","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Serkan \u00d6zcan","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/nekudos.com\/sap-ai-use-case-secimi\/#article","isPartOf":{"@id":"https:\/\/nekudos.com\/sap-ai-use-case-secimi\/"},"author":{"name":"Serkan \u00d6zcan","@id":"https:\/\/nekudos.com\/#\/schema\/person\/31af2943257c01e139ab0726e852be63"},"headline":"SAP AI Use Case Seciminde Dogru Veri ve Is Hedefi Uyumu","datePublished":"2026-02-09T05:01:56+00:00","dateModified":"2026-02-09T05:02:10+00:00","mainEntityOfPage":{"@id":"https:\/\/nekudos.com\/sap-ai-use-case-secimi\/"},"wordCount":939,"publisher":{"@id":"https:\/\/nekudos.com\/#organization"},"image":{"@id":"https:\/\/nekudos.com\/sap-ai-use-case-secimi\/#primaryimage"},"thumbnailUrl":"https:\/\/nekudos.com\/wp-content\/uploads\/2026\/02\/cover-image-30036.jpg","articleSection":["SAP"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/nekudos.com\/sap-ai-use-case-secimi\/","url":"https:\/\/nekudos.com\/sap-ai-use-case-secimi\/","name":"SAP AI Use Case Seciminde Dogru Veri ve Is Hedefi Uyumu - 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