{"id":476690,"date":"2023-08-09T07:31:20","date_gmt":"2023-08-09T07:31:20","guid":{"rendered":""},"modified":"2023-09-05T11:13:13","modified_gmt":"2023-09-05T11:13:13","slug":"data-profiling","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/tr\/wiki\/data-profiling\/","title":{"rendered":"Veri profili olu\u015fturma"},"content":{"rendered":"<p>Veri profili olu\u015fturma, veri y\u00f6netimi alan\u0131nda, yap\u0131s\u0131na, kalitesine ve i\u00e7eri\u011fine dair i\u00e7g\u00f6r\u00fc elde etmek i\u00e7in verilerin incelenmesini, analiz edilmesini ve \u00f6zetlenmesini i\u00e7eren \u00e7ok \u00f6nemli bir s\u00fcre\u00e7tir. Veri haz\u0131rlama, veri y\u00f6neti\u015fimi ve veri entegrasyonunda temel bir rol oynayarak verilerin daha sonraki i\u015flemler ve karar alma s\u00fcre\u00e7leri i\u00e7in do\u011fru, eksiksiz ve g\u00fcvenilir olmas\u0131n\u0131 sa\u011flar.<\/p>\n<h2>Veri profillemenin k\u00f6keninin tarihi ve bundan ilk s\u00f6z<\/h2>\n<p>Veri profili olu\u015fturman\u0131n k\u00f6kleri, i\u015fletmelerin veri kalitesinin \u00f6nemini fark etmeye ba\u015flad\u0131\u011f\u0131 veri y\u00f6netiminin ilk g\u00fcnlerine kadar uzanabilir. Ancak \u201cveri profili olu\u015fturma\u201d terimi, 1990&#039;lar\u0131n sonu ve 2000&#039;lerin ba\u015f\u0131nda veri ambar\u0131 ve veri madencili\u011fi teknolojilerinin ortaya \u00e7\u0131k\u0131\u015f\u0131yla \u00f6nem kazand\u0131. Veri hacimleri katlanarak artt\u0131k\u00e7a kurulu\u015flar, veri varl\u0131klar\u0131n\u0131n karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 anlama konusunda zorluklarla kar\u015f\u0131la\u015ft\u0131. Bu, kurulu\u015flar\u0131n verileriyle ilgili daha iyi i\u00e7g\u00f6r\u00fcler kazanmas\u0131na yard\u0131mc\u0131 olabilecek veri profili olu\u015fturma ara\u00e7lar\u0131n\u0131n ve tekniklerinin ortaya \u00e7\u0131kmas\u0131na yol a\u00e7t\u0131.<\/p>\n<h2>Veri profili olu\u015fturma hakk\u0131nda ayr\u0131nt\u0131l\u0131 bilgi. Veri profili olu\u015fturma konusunu geni\u015fletiyoruz.<\/h2>\n<p>Veri profili olu\u015fturma, kal\u0131plar\u0131, anormallikleri ve tutars\u0131zl\u0131klar\u0131 belirlemek i\u00e7in yap\u0131land\u0131r\u0131lm\u0131\u015f ve yap\u0131land\u0131r\u0131lmam\u0131\u015f veriler de dahil olmak \u00fczere veri setlerinin kapsaml\u0131 bir analizini i\u00e7erir. S\u00fcre\u00e7, verilerle ilgili a\u015fa\u011f\u0131dakiler gibi \u00f6nemli sorular\u0131 yan\u0131tlamay\u0131 ama\u00e7lamaktad\u0131r:<\/p>\n<ul>\n<li>Veri k\u00fcmesinde bulunan veri t\u00fcrleri ve formatlar\u0131 nelerdir?<\/li>\n<li>Eksik de\u011ferler, kopyalar veya ayk\u0131r\u0131 de\u011ferler var m\u0131?<\/li>\n<li>Verilerin ortalama, medyan ve standart sapma gibi istatistiksel \u00f6zellikleri nelerdir?<\/li>\n<li>Herhangi bir referans b\u00fct\u00fcnl\u00fc\u011f\u00fc k\u0131s\u0131tlamas\u0131 veya veri ba\u011f\u0131ml\u0131l\u0131\u011f\u0131 var m\u0131?<\/li>\n<li>Veriler \u00f6nceden tan\u0131mlanm\u0131\u015f i\u015f kurallar\u0131na ve veri kalitesi standartlar\u0131na ne kadar iyi uyuyor?<\/li>\n<\/ul>\n<p>Veri profili olu\u015fturma s\u00fcreci genellikle veri ke\u015ffi, veri yap\u0131s\u0131 analizi, veri i\u00e7eri\u011fi analizi ve veri kalitesi de\u011ferlendirmesi dahil olmak \u00fczere birka\u00e7 a\u015famada ger\u00e7ekle\u015ftirilir. Verilerden anlaml\u0131 i\u00e7g\u00f6r\u00fcler elde etmek i\u00e7in veri profili olu\u015fturma yaz\u0131l\u0131m\u0131, istatistiksel analiz ve veri g\u00f6rselle\u015ftirme gibi \u00e7e\u015fitli veri profili olu\u015fturma teknikleri ve ara\u00e7lar\u0131 kullan\u0131l\u0131r.<\/p>\n<h2>Veri profili olu\u015fturman\u0131n i\u00e7 yap\u0131s\u0131. Veri profili olu\u015fturma nas\u0131l \u00e7al\u0131\u015f\u0131r?<\/h2>\n<p>Veri profili olu\u015fturma ara\u00e7lar\u0131, profil olu\u015fturma s\u00fcrecini etkili bir \u015fekilde y\u00fcr\u00fctmek i\u00e7in uyumlu bir \u015fekilde \u00e7al\u0131\u015fan \u00e7e\u015fitli bile\u015fenlerden olu\u015fur:<\/p>\n<ol>\n<li>Veri Ke\u015ffi: Bu ilk a\u015fama, veritabanlar\u0131, d\u00fcz dosyalar, veri ambarlar\u0131 veya API&#039;ler olabilen veri kaynaklar\u0131n\u0131n bulunmas\u0131n\u0131 ve tan\u0131mlanmas\u0131n\u0131 i\u00e7erir.<\/li>\n<li>Veri Profili Olu\u015fturma Motoru: Veri profili olu\u015fturma arac\u0131n\u0131n temeli olan bu motor, verileri analiz etmek, \u00f6zetler olu\u015fturmak ve veri modellerini tan\u0131mlamak i\u00e7in algoritmalar ve istatistiksel y\u00f6ntemler kullan\u0131r.<\/li>\n<li>Meta Veri Havuzu: Veri tan\u0131mlar\u0131, veri k\u00f6keni ve veri \u00f6\u011feleri aras\u0131ndaki ili\u015fkiler de dahil olmak \u00fczere verilerle ilgili meta verileri depolar.<\/li>\n<li>Veri G\u00f6rselle\u015ftirme: Veri profili olu\u015fturma sonu\u00e7lar\u0131n\u0131 daha sezgisel ve anla\u015f\u0131l\u0131r bir \u015fekilde sunmak i\u00e7in grafikler, \u00e7izelgeler ve g\u00f6sterge tablolar\u0131ndan yararlan\u0131r.<\/li>\n<\/ol>\n<h2>Veri profili olu\u015fturman\u0131n temel \u00f6zelliklerinin analizi.<\/h2>\n<p>Veri profili olu\u015fturma, onu verilerle ilgilenen her kurulu\u015f i\u00e7in paha bi\u00e7ilmez bir varl\u0131k haline getiren \u00e7ok say\u0131da temel \u00f6zellik sunar:<\/p>\n<ul>\n<li>Veri Kalitesi De\u011ferlendirmesi: Veri kalitesi sorunlar\u0131n\u0131 tan\u0131mlay\u0131p \u00f6l\u00e7erek kurulu\u015flar\u0131n veri anormalliklerini ele almas\u0131na ve genel veri kalitesini iyile\u015ftirmesine olanak tan\u0131r.<\/li>\n<li>Veri \u015eemas\u0131 Ke\u015ffi: Verilerin temel yap\u0131s\u0131n\u0131n anla\u015f\u0131lmas\u0131na yard\u0131mc\u0131 olarak veri entegrasyonunu ve veri ta\u015f\u0131ma s\u00fcre\u00e7lerini kolayla\u015ft\u0131r\u0131r.<\/li>\n<li>Veri K\u00f6keni: \u00c7e\u015fitli sistemlerdeki verilerin k\u00f6kenini ve hareketini takip ederek veri y\u00f6netimini ve uyumlulu\u011fu sa\u011flar.<\/li>\n<li>\u0130li\u015fki Ke\u015ffi: Farkl\u0131 veri \u00f6\u011feleri aras\u0131ndaki ili\u015fkileri ortaya \u00e7\u0131kararak veri modelleme ve analize yard\u0131mc\u0131 olur.<\/li>\n<\/ul>\n<h2>Veri profili olu\u015fturma t\u00fcrleri<\/h2>\n<p>Analizin do\u011fas\u0131na ba\u011fl\u0131 olarak \u00e7e\u015fitli veri profili olu\u015fturma t\u00fcrleri vard\u0131r. \u0130\u015fte baz\u0131 yayg\u0131n t\u00fcrler:<\/p>\n<table>\n<thead>\n<tr>\n<th>Tip<\/th>\n<th>Tan\u0131m<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>S\u00fctun Profili Olu\u015fturma<\/td>\n<td>Bireysel veri s\u00fctunlar\u0131na, veri t\u00fcrlerini, de\u011fer da\u011f\u0131l\u0131mlar\u0131n\u0131 ve istatistiksel \u00f6zellikleri analiz etmeye odaklan\u0131r.<\/td>\n<\/tr>\n<tr>\n<td>S\u00fctunlar Aras\u0131 Profil Olu\u015fturma<\/td>\n<td>Ba\u011f\u0131ml\u0131l\u0131klar\u0131 ve kal\u0131plar\u0131 belirleyerek farkl\u0131 veri s\u00fctunlar\u0131 aras\u0131ndaki ili\u015fkiyi inceler.<\/td>\n<\/tr>\n<tr>\n<td>De\u011fer Da\u011f\u0131t\u0131m Profili Olu\u015fturma<\/td>\n<td>Bir s\u00fctun i\u00e7indeki veri de\u011ferlerinin da\u011f\u0131l\u0131m\u0131n\u0131 analiz ederek anormallikleri ve ayk\u0131r\u0131 de\u011ferleri tespit eder.<\/td>\n<\/tr>\n<tr>\n<td>Desen Tabanl\u0131 Profil Olu\u015fturma<\/td>\n<td>Verilerdeki telefon numaralar\u0131, e-posta adresleri veya kredi kart\u0131 numaralar\u0131 gibi belirli kal\u0131plar\u0131 veya bi\u00e7imleri tan\u0131mlar.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Kullan\u0131m yollar\u0131 Veri profili olu\u015fturma, sorunlar ve kullan\u0131mla ilgili \u00e7\u00f6z\u00fcmleri.<\/h2>\n<p>Veri profili olu\u015fturma, a\u015fa\u011f\u0131dakiler de dahil olmak \u00fczere \u00e7e\u015fitli ama\u00e7lara hizmet eder:<\/p>\n<ul>\n<li>Veri Kalitesi De\u011ferlendirmesi: Veri do\u011frulu\u011funun ve g\u00fcvenilirli\u011finin sa\u011flanmas\u0131.<\/li>\n<li>Veri Entegrasyonu: \u00c7e\u015fitli kaynaklardan gelen verilerin kusursuz entegrasyonunu kolayla\u015ft\u0131rmak.<\/li>\n<li>Veri Ta\u015f\u0131ma: Sistemler aras\u0131nda sorunsuz veri aktar\u0131m\u0131n\u0131 destekler.<\/li>\n<li>Veri Y\u00f6neti\u015fimi: Veri politikalar\u0131n\u0131n ve uyumlulu\u011fun uygulanmas\u0131.<\/li>\n<li>\u0130\u015f Zekas\u0131: Daha iyi karar verme i\u00e7in i\u00e7g\u00f6r\u00fcler sa\u011flamak.<\/li>\n<\/ul>\n<p>Ancak veri profili olu\u015fturma s\u00fcrecinde a\u015fa\u011f\u0131daki gibi baz\u0131 zorluklar ortaya \u00e7\u0131kabilir:<\/p>\n<ul>\n<li>B\u00fcy\u00fck Veriyi Ele Alma: Veri hacimleri b\u00fcy\u00fcd\u00fck\u00e7e geleneksel veri profili olu\u015fturma teknikleri yetersiz hale gelebilir. \u00c7\u00f6z\u00fcmler aras\u0131nda da\u011f\u0131t\u0131lm\u0131\u015f veri profili olu\u015fturma ara\u00e7lar\u0131n\u0131n veya \u00f6rnekleme tekniklerinin kullan\u0131lmas\u0131 yer al\u0131r.<\/li>\n<li>Yap\u0131land\u0131r\u0131lmam\u0131\u015f Verilerle Ba\u015fa \u00c7\u0131kmak: G\u00f6r\u00fcnt\u00fcler veya metin gibi yap\u0131land\u0131r\u0131lmam\u0131\u015f verilerin profilini \u00e7\u0131karmak, do\u011fal dil i\u015fleme ve makine \u00f6\u011frenimi algoritmalar\u0131 dahil olmak \u00fczere geli\u015fmi\u015f teknikler gerektirir.<\/li>\n<li>Veri Gizlili\u011fi Kayg\u0131lar\u0131: Veri profili olu\u015fturma hassas bilgileri a\u00e7\u0131\u011fa \u00e7\u0131karabilir. Anonimle\u015ftirme ve veri maskeleme teknikleri gizlilik sorunlar\u0131n\u0131 \u00e7\u00f6zebilir.<\/li>\n<\/ul>\n<h2>Ana \u00f6zellikler ve benzer terimlerle di\u011fer kar\u015f\u0131la\u015ft\u0131rmalar tablo ve liste \u015feklinde.<\/h2>\n<table>\n<thead>\n<tr>\n<th>karakteristik<\/th>\n<th>Veri Profili Olu\u015fturma<\/th>\n<th>Veri madencili\u011fi<\/th>\n<th>Veri do\u011frulama<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Ama\u00e7<\/td>\n<td>Veri kalitesini, yap\u0131s\u0131n\u0131 ve i\u00e7eri\u011fini anlay\u0131n.<\/td>\n<td>Verilerden de\u011ferli bilgileri ve kal\u0131plar\u0131 \u00e7\u0131kar\u0131n.<\/td>\n<td>Verilerin \u00f6nceden tan\u0131mlanm\u0131\u015f kurallar\u0131 ve standartlar\u0131 kar\u015f\u0131lad\u0131\u011f\u0131ndan emin olun.<\/td>\n<\/tr>\n<tr>\n<td>Odak<\/td>\n<td>Veri ara\u015ft\u0131rmas\u0131 ve analizi.<\/td>\n<td>\u00d6r\u00fcnt\u00fc tan\u0131ma ve tahmine dayal\u0131 modelleme.<\/td>\n<td>Veri kural\u0131n\u0131n uygulanmas\u0131 ve hata tespiti.<\/td>\n<\/tr>\n<tr>\n<td>Kullan\u0131m<\/td>\n<td>Veri haz\u0131rlama ve veri y\u00f6netimi.<\/td>\n<td>\u0130\u015f zekas\u0131 ve karar verme.<\/td>\n<td>Veri giri\u015fi ve veri i\u015fleme.<\/td>\n<\/tr>\n<tr>\n<td>Teknikler<\/td>\n<td>\u0130statistiksel analiz, veri g\u00f6rselle\u015ftirme.<\/td>\n<td>Makine \u00f6\u011frenimi, k\u00fcmeleme ve s\u0131n\u0131fland\u0131rma.<\/td>\n<td>Kural tabanl\u0131 do\u011frulama, k\u0131s\u0131tlama kontrolleri.<\/td>\n<\/tr>\n<tr>\n<td>Sonu\u00e7<\/td>\n<td>Veri kalitesi \u00f6ng\u00f6r\u00fcleri ve veri profili olu\u015fturma raporlar\u0131.<\/td>\n<td>Tahmine dayal\u0131 modeller ve eyleme ge\u00e7irilebilir bilgiler.<\/td>\n<td>Veri do\u011frulama raporlar\u0131 ve hata g\u00fcnl\u00fckleri.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Veri profili olu\u015fturmayla ilgili gelece\u011fin perspektifleri ve teknolojileri.<\/h2>\n<p>Veriler b\u00fcy\u00fcmeye ve geli\u015fmeye devam ettik\u00e7e, veri profillemenin gelece\u011fi \u00e7e\u015fitli alanlarda ilerlemelere tan\u0131k olacakt\u0131r:<\/p>\n<ul>\n<li>Yapay Zeka Odakl\u0131 Veri Profili Olu\u015fturma: Yapay zeka ve makine \u00f6\u011frenimi, veri profili olu\u015fturma ara\u00e7lar\u0131na daha fazla entegre edilecek, analiz s\u00fcreci otomatikle\u015ftirilecek ve ger\u00e7ek zamanl\u0131 bilgiler sa\u011flanacak.<\/li>\n<li>Geli\u015ftirilmi\u015f Yap\u0131land\u0131r\u0131lmam\u0131\u015f Veri Profili Olu\u015fturma: Do\u011fal dil i\u015fleme ve g\u00f6r\u00fcnt\u00fc tan\u0131ma gibi yap\u0131land\u0131r\u0131lmam\u0131\u015f verileri analiz etme teknikleri daha karma\u015f\u0131k ve do\u011fru hale gelecektir.<\/li>\n<li>Gizlili\u011fi Koruyan Veri Profili Olu\u015fturma: Gizlilik endi\u015feleri, hassas bilgilerden \u00f6d\u00fcn vermeden veri kalitesini de\u011ferlendirebilen veri profili olu\u015fturma y\u00f6ntemlerinin geli\u015ftirilmesine y\u00f6n verecektir.<\/li>\n<\/ul>\n<h2>Proxy sunucular\u0131 nas\u0131l kullan\u0131labilir veya Veri profili olu\u015fturmayla nas\u0131l ili\u015fkilendirilebilir?<\/h2>\n<p>Proxy sunucular\u0131, \u00f6zellikle web verileriyle u\u011fra\u015f\u0131rken veri profili olu\u015fturmada \u00f6nemli bir rol oynayabilir. Web tabanl\u0131 veri kaynaklar\u0131nda veri profili olu\u015ftururken proxy sunucular \u015fu ama\u00e7larla kullan\u0131labilir:<\/p>\n<ol>\n<li>Veri \u0130steklerini Anonim Hale Getirin: Proxy sunucular\u0131, veri profili olu\u015fturma arac\u0131n\u0131n ger\u00e7ek IP adresini gizleyerek veri kayna\u011f\u0131n\u0131n profil olu\u015fturma giri\u015fimlerini tan\u0131mlamas\u0131n\u0131 ve engellemesini \u00f6nleyebilir.<\/li>\n<li>\u0130\u015f Y\u00fck\u00fcn\u00fc Da\u011f\u0131t\u0131n: B\u00fcy\u00fck \u00f6l\u00e7ekli veri profili olu\u015fturma g\u00f6revlerini y\u00fcr\u00fct\u00fcrken, proxy sunucular istekleri birden fazla IP&#039;ye da\u011f\u0131tarak tek bir kaynaktaki y\u00fck\u00fc azaltabilir ve verilerin sorunsuz bir \u015fekilde al\u0131nmas\u0131n\u0131 sa\u011flayabilir.<\/li>\n<li>Co\u011frafi K\u0131s\u0131tl\u0131 Verilere Eri\u015fim: \u00c7e\u015fitli co\u011frafi konumlara sahip proxy sunucular, farkl\u0131 b\u00f6lgelerden veri profili olu\u015fturmaya olanak tan\u0131yarak kurulu\u015flar\u0131n belirli alanlara \u00f6zg\u00fc verileri analiz etmesine olanak tan\u0131r.<\/li>\n<\/ol>\n<h2>\u0130lgili Ba\u011flant\u0131lar<\/h2>\n<p>Veri profili olu\u015fturma hakk\u0131nda daha fazla bilgi i\u00e7in a\u015fa\u011f\u0131daki kaynaklar\u0131 inceleyebilirsiniz:<\/p>\n<ol>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_profiling\" target=\"_new\" rel=\"noopener nofollow\">Veri Profili Olu\u015fturma - Vikipedi<\/a><\/li>\n<li><a href=\"https:\/\/www.ibm.com\/cloud\/learn\/data-profiling-explained\" target=\"_new\" rel=\"noopener nofollow\">Veri Profili Olu\u015fturma A\u00e7\u0131klamas\u0131 \u2013 IBM<\/a><\/li>\n<li><a href=\"https:\/\/www.sas.com\/en_us\/insights\/data-management\/what-is-data-profiling.html\" target=\"_new\" rel=\"noopener nofollow\">Veri Kalitesi Y\u00f6netiminde Veri Profil Olu\u015fturman\u0131n Rol\u00fc - SAS<\/a><\/li>\n<li><a href=\"https:\/\/www.talend.com\/resources\/data-profiling\/\" target=\"_new\" rel=\"noopener nofollow\">Veri Profil Olu\u015fturma Teknikleri ve En \u0130yi Uygulamalar \u2013 Talend<\/a><\/li>\n<li><a href=\"https:\/\/blogs.informatica.com\/2016\/02\/09\/data-profiling-vs-data-quality-whats-the-difference\/\" target=\"_new\" rel=\"noopener nofollow\">Veri Profili Olu\u015fturma ve Veri Kalitesi: Fark Nedir? \u2013 Bili\u015fim<\/a><\/li>\n<\/ol>","protected":false},"featured_media":476691,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-476690","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Data Profiling: Unveiling the Secrets of Data<\/mark>","faq_items":[{"question":"What is data profiling?","answer":"<p>Data profiling is a crucial process in data management that involves examining, analyzing, and summarizing data to gain insights into its structure, quality, and content. It helps organizations understand their data better, ensuring accuracy and reliability for decision-making.<\/p>"},{"question":"How did data profiling originate?","answer":"<p>Data profiling's roots can be traced back to the early days of data management, but the term gained prominence in the late 1990s and early 2000s with the rise of data warehousing and data mining technologies.<\/p>"},{"question":"What does the data profiling process entail?","answer":"<p>The data profiling process includes data discovery, data structure analysis, data content analysis, and data quality assessment. It uses techniques like statistical analysis and data visualization to understand the data comprehensively.<\/p>"},{"question":"What are the key features of data profiling?","answer":"<p>Data profiling offers essential features such as data quality assessment, data schema discovery, data lineage tracking, and relationship discovery between data elements.<\/p>"},{"question":"What are the different types of data profiling?","answer":"<p>Data profiling can be categorized into various types, including column profiling, cross-column profiling, value distribution profiling, and pattern-based profiling.<\/p>"},{"question":"How can data profiling be used?","answer":"<p>Data profiling serves various purposes, including data quality assessment, data integration, data migration, data governance, and business intelligence.<\/p>"},{"question":"What challenges can arise during data profiling?","answer":"<p>Challenges in data profiling may include handling big data, dealing with unstructured data, and addressing data privacy concerns. Solutions involve using advanced techniques and data masking.<\/p>"},{"question":"How does the future of data profiling look?","answer":"<p>The future of data profiling holds promising advancements in AI-driven profiling, improved analysis of unstructured data, and privacy-preserving techniques.<\/p>"},{"question":"How are proxy servers associated with data profiling?","answer":"<p>Proxy servers play a significant role in web-based data profiling by anonymizing data requests, distributing workload, and accessing geo-restricted data sources.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476690","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476690\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media\/476691"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media?parent=476690"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}