{"id":3725,"date":"2023-09-29T09:47:05","date_gmt":"2023-09-29T09:47:05","guid":{"rendered":"https:\/\/www.peopleoma.com\/?p=3725"},"modified":"2023-09-29T09:47:06","modified_gmt":"2023-09-29T09:47:06","slug":"insan-kaynaklari-analitiginde-citayi-yukseltiyoruz-peopleoma-veri-kalitesi-modulu","status":"publish","type":"post","link":"https:\/\/www.peopleoma.com\/tr\/insan-kaynaklari-analitiginde-citayi-yukseltiyoruz-peopleoma-veri-kalitesi-modulu\/","title":{"rendered":"\u0130nsan Kaynaklar\u0131 Analiti\u011finde \u00c7\u0131tay\u0131 Y\u00fckseltiyoruz: Peopleoma Veri Kalitesi Mod\u00fcl\u00fc"},"content":{"rendered":"\n<p>Veri kalitesinin \u0130K analiti\u011fi i\u00e7in \u00f6nemi tart\u0131\u015f\u0131lmaz. E\u011fer veriniz sa\u011fl\u0131kl\u0131 de\u011filse yap\u0131lan analizler kullan\u0131labilir olmayacakt\u0131r. \u0130K analiti\u011finin s\u00fcrekli evrilen d\u00fcnyas\u0131nda veri kalitesinin \u00f6nemi zamanla daha iyi anla\u015f\u0131lmaktad\u0131r. \u0130K profesyonelleri \u00e7al\u0131\u015fan demografilerinden performans metriklerine kadar geni\u015f veri havuzunu y\u00f6netirler ve bu verilerin \u0131\u015f\u0131\u011f\u0131nda kritik karar s\u00fcre\u00e7lerini \u015fekillendirirler. Ancak bu verilerin do\u011frulu\u011fu ve g\u00fcvenilirli\u011fi son derece \u00f6nemlidir. Bu ihtiya\u00e7tan yola \u00e7\u0131kt\u0131k ve veri do\u011frulu\u011fu ve b\u00fct\u00fcnl\u00fc\u011f\u00fcn\u00fc artt\u0131rarak \u0130K analiti\u011finde seviyeyi yukar\u0131 \u00e7ekme gayesiyle Peopleoma Veri Kalitesi Mod\u00fcl\u00fc\u2019n\u00fc hayata ge\u00e7irdik.<\/p>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Veri Kalitesi Nedir?<\/strong><\/p>\n\n\n\n<p>Veri kalitesi bilin\u00e7li kararlar almak i\u00e7in kulland\u0131\u011f\u0131n\u0131z verilerin genel sa\u011fl\u0131\u011f\u0131 ve g\u00fcvenilirli\u011fi anlam\u0131na gelir. Bu, veri do\u011frulu\u011fu, eksiksizlik, tutarl\u0131l\u0131k, g\u00fcncel olma ve ge\u00e7erlilik gibi birka\u00e7 ba\u015fl\u0131\u011f\u0131 i\u00e7erir. \u0130K analiti\u011finde, veri kalitesi t\u00fcm stratejik kararlar\u0131n temelidir. \u0130K liderleri i\u015fe al\u0131m, \u00e7al\u0131\u015fan ba\u011fl\u0131l\u0131\u011f\u0131, e\u011fitim ve daha fazlas\u0131 hakk\u0131nda bilin\u00e7li kararlar almak i\u00e7in verilere g\u00fcvenirler. K\u00f6t\u00fc veri kalitesi yanl\u0131\u015f y\u00f6nlendirmeye yol a\u00e7abilir ve amac\u0131na ula\u015fmayan stratejilerin kurgulanmas\u0131na yol a\u00e7abilir.<\/p>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Peopleoma Veri Kalitesi Mod\u00fcl\u00fc<\/strong><\/p>\n\n\n\n<p>\u015eirketlerin \u0130K veri sa\u011fl\u0131\u011f\u0131n\u0131 g\u00fc\u00e7lendirmek i\u00e7in Peopleoma Veri Kalitesi Mod\u00fcl\u00fcn\u00fc geli\u015ftirdik. Mod\u00fcl\u00fcm\u00fcz iki temel \u00f6zelli\u011fi i\u00e7ermektedir:<\/p>\n\n\n\n<p class=\"has-medium-font-size\"><strong>1- Eksik Veri Analizi:<\/strong><\/p>\n\n\n\n<p>Bu \u00f6zellik, organizasyonunuzun \u00e7al\u0131\u015fan verilerinde eksik de\u011ferleri tan\u0131mlar. \u00c7al\u0131\u015fan kay\u0131tlar\u0131 eksik oldu\u011funda, mod\u00fcl\u00fcm\u00fcz dikkat gerektiren ve doldurulmas\u0131 gereken alanlar\u0131 vurgular.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"3182\" height=\"1268\" src=\"https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-3.png\" alt=\"\" class=\"wp-image-3715\" srcset=\"https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-3.png 3182w, https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-3-300x120.png 300w, https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-3-1024x408.png 1024w\" sizes=\"(max-width: 3182px) 100vw, 3182px\" \/><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p>Baz\u0131 kay\u0131tlar eksik oldu\u011funda mod\u00fcl\u00fcm\u00fcz sadece bo\u015fluklar\u0131 belirtmekle kalmaz, ayn\u0131 zamanda eksik kay\u0131tlar\u0131 nas\u0131l doldurman\u0131z gerekti\u011fini \u00f6nererek size yard\u0131mc\u0131 olur. Tamamlanm\u0131\u015f \u00e7al\u0131\u015fan kay\u0131tlar\u0131na sahip benzer \u00e7al\u0131\u015fanlar\u0131 arayan ak\u0131ll\u0131 bir algoritmam\u0131z eksiksiz \u00e7al\u0131\u015fan kay\u0131tlar\u0131n\u0131 eksik olanlar\u0131 nas\u0131l doldurman\u0131z gerekti\u011fi konusunda bir rehber olarak kullan\u0131r.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"3182\" height=\"1198\" src=\"https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-4.png\" alt=\"\" class=\"wp-image-3717\" srcset=\"https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-4.png 3182w, https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-4-300x113.png 300w, https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-4-1024x386.png 1024w\" sizes=\"(max-width: 3182px) 100vw, 3182px\" \/><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p class=\"has-medium-font-size\"><strong>2- Ayk\u0131r\u0131 Veri Analizi:<\/strong><\/p>\n\n\n\n<p>Ayk\u0131r\u0131 de\u011ferler \u0130K analiti\u011finde hesaplamalar\u0131 yanl\u0131\u015f y\u00f6nlendirmektedir. Mod\u00fcl\u00fcm\u00fcz verilerinizdeki bu anormallikleri tespit eder, bunlar\u0131 h\u0131zla incelemenizi ve ele alman\u0131z\u0131 sa\u011flar. Bu \u015fekilde kararlar\u0131n\u0131z\u0131n g\u00fcvenilir bir veri k\u00fcmesine dayand\u0131\u011f\u0131ndan emin olman\u0131z\u0131 sa\u011flar.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" width=\"3182\" height=\"1268\" src=\"https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-2.png\" alt=\"\" class=\"wp-image-3719\" srcset=\"https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-2.png 3182w, https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-2-300x120.png 300w, https:\/\/www.peopleoma.com\/wp-content\/uploads\/2023\/09\/MicrosoftTeams-image-2-1024x408.png 1024w\" sizes=\"(max-width: 3182px) 100vw, 3182px\" \/><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p>Sonu\u00e7 olarak, veri kalitesi etkili bir \u0130K analiti\u011finin temelidir. Sa\u011fl\u0131kl\u0131 bir veriye sahip olmadan \u0130K stratejinizi sa\u011flam bir zemine oturtamazs\u0131n\u0131z. Veri Kalitesi Mod\u00fcl\u00fcm\u00fcz \u0130K analiti\u011fi \u00e7al\u0131\u015fmalar\u0131n\u0131z\u0131 g\u00fc\u00e7lendirmek i\u00e7in tasarlanm\u0131\u015ft\u0131r ve bilin\u00e7li kararlar alman\u0131z ve olumlu kurumsal sonu\u00e7lar elde etmeniz i\u00e7in gereken g\u00fcvenilir verilere sahip oldu\u011funuzdan emin olman\u0131z\u0131 sa\u011flar. \u0130K analiti\u011finizi Peopleoma Veri Kalitesi Mod\u00fcl\u00fc ile bir \u00fcst seviyeye ta\u015f\u0131y\u0131n ve \u00e7al\u0131\u015fan verinizin ger\u00e7ek potansiyeline ula\u015f\u0131n.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Veri kalitesinin \u0130K analiti\u011fi i\u00e7in \u00f6nemi tart\u0131\u015f\u0131lmaz. E\u011fer veriniz sa\u011fl\u0131kl\u0131 de\u011filse yap\u0131lan analizler kullan\u0131labilir olmayacakt\u0131r. \u0130K analiti\u011finin s\u00fcrekli evrilen d\u00fcnyas\u0131nda veri kalitesinin \u00f6nemi zamanla daha iyi anla\u015f\u0131lmaktad\u0131r. \u0130K profesyonelleri \u00e7al\u0131\u015fan demografilerinden performans metriklerine kadar geni\u015f veri havuzunu y\u00f6netirler ve bu verilerin \u0131\u015f\u0131\u011f\u0131nda kritik karar s\u00fcre\u00e7lerini \u015fekillendirirler. Ancak bu verilerin do\u011frulu\u011fu ve g\u00fcvenilirli\u011fi son derece \u00f6nemlidir. [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[46,48,29,32,47],"class_list":["post-3725","post","type-post","status-publish","format-standard","hentry","category-blog","tag-data-modulu","tag-hr-tech","tag-ik-analitigi","tag-peopleoma","tag-veri-sagligi"],"_links":{"self":[{"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/posts\/3725","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/comments?post=3725"}],"version-history":[{"count":1,"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/posts\/3725\/revisions"}],"predecessor-version":[{"id":3726,"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/posts\/3725\/revisions\/3726"}],"wp:attachment":[{"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/media?parent=3725"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/categories?post=3725"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.peopleoma.com\/tr\/wp-json\/wp\/v2\/tags?post=3725"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}