{"id":476718,"date":"2023-08-09T07:35:16","date_gmt":"2023-08-09T07:35:16","guid":{"rendered":""},"modified":"2023-09-05T11:13:18","modified_gmt":"2023-09-05T11:13:18","slug":"data-transformation","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/tr\/wiki\/data-transformation\/","title":{"rendered":"Veri d\u00f6n\u00fc\u015f\u00fcm\u00fc"},"content":{"rendered":"<p>Veri d\u00f6n\u00fc\u015f\u00fcm\u00fc, verileri bir formattan veya yap\u0131dan di\u011ferine d\u00f6n\u00fc\u015ft\u00fcrmeyi i\u00e7eren bir s\u00fcre\u00e7tir. Uygulama, veri y\u00f6netiminin \u00f6nemli bir par\u00e7as\u0131d\u0131r ve genellikle veri entegrasyonu, veri ge\u00e7i\u015fi, veri ambar\u0131 ve \u00e7e\u015fitli veri i\u015fleme g\u00f6revleri s\u0131ras\u0131nda ger\u00e7ekle\u015fir. Temel amac\u0131, \u00f6zellikle veri analizi ve karar verme ba\u011flam\u0131nda, farkl\u0131 uygulamalar i\u00e7in veri kalitesini, uyumlulu\u011funu ve kullan\u0131\u015fl\u0131l\u0131\u011f\u0131n\u0131 geli\u015ftirmektir.<\/p>\n<h2>Veri D\u00f6n\u00fc\u015f\u00fcm\u00fcn\u00fcn Tarihsel Ba\u011flam\u0131<\/h2>\n<p>Veri d\u00f6n\u00fc\u015f\u00fcm\u00fcn\u00fcn k\u00f6kenleri bilgisayarlar\u0131n ve dijital veri depolaman\u0131n ortaya \u00e7\u0131k\u0131\u015f\u0131na kadar uzanabilir. Ancak kavram, 1970&#039;lerde veritaban\u0131 y\u00f6netim sistemlerinin (DBMS) y\u00fckseli\u015finin ard\u0131ndan \u00f6nem kazand\u0131. Veri d\u00f6n\u00fc\u015f\u00fcm\u00fcn\u00fcn mevcut anlay\u0131\u015f\u0131yla ilk s\u00f6z\u00fc, verilerin operasyonel veritabanlar\u0131ndan karar destek veritabanlar\u0131na ta\u015f\u0131nmas\u0131nda hayati \u00f6neme sahip olan \u00c7\u0131karma, D\u00f6n\u00fc\u015ft\u00fcrme, Y\u00fckleme (ETL) s\u00fcre\u00e7leri alan\u0131nda ortaya \u00e7\u0131km\u0131\u015ft\u0131r.<\/p>\n<h2>Veri D\u00f6n\u00fc\u015f\u00fcm\u00fcn\u00fc Anlamak<\/h2>\n<p>Veri d\u00f6n\u00fc\u015f\u00fcm\u00fc \u00e7e\u015fitli faaliyetleri i\u00e7erir. \u00d6z\u00fcnde, verileri daha ileri analiz veya i\u015fleme i\u00e7in uygun bir forma d\u00f6n\u00fc\u015ft\u00fcr\u00fcr. Bu s\u00fcre\u00e7te yer alan ad\u0131mlar, verileri temizleme (hatalar\u0131 veya tutars\u0131zl\u0131klar\u0131 giderme), birle\u015ftirme (verileri \u00f6zetleme veya grupland\u0131rma) ve normalle\u015ftirmeyi (veri \u00f6l\u00e7e\u011fini de\u011fi\u015ftirme) i\u00e7erebilir.<\/p>\n<p>D\u00f6n\u00fc\u015f\u00fcm\u00fcn kesin do\u011fas\u0131 uygulamaya ve hem kaynak hem de hedef verilerin yap\u0131lar\u0131na ba\u011fl\u0131d\u0131r. Baz\u0131 durumlarda, tam say\u0131lar\u0131 ger\u00e7ek say\u0131lara d\u00f6n\u00fc\u015ft\u00fcrmek gibi veri t\u00fcrleri aras\u0131nda basit bir d\u00f6n\u00fc\u015ft\u00fcrmeyi i\u00e7erebilir. Di\u011fer durumlarda metin madencili\u011fi veya duygu analizi gibi karma\u015f\u0131k prosed\u00fcrleri i\u00e7erebilir.<\/p>\n<h2>Veri D\u00f6n\u00fc\u015f\u00fcm\u00fcn\u00fcn \u0130\u00e7 Yap\u0131s\u0131<\/h2>\n<p>Veri d\u00f6n\u00fc\u015ft\u00fcrmenin i\u015fleyi\u015fi, verinin \u00f6zelliklerine ve kullan\u0131lan ara\u00e7lara ba\u011fl\u0131d\u0131r. Genellikle s\u00fcre\u00e7, komut dosyalar\u0131 veya yaz\u0131l\u0131m ara\u00e7lar\u0131 kullan\u0131larak otomatikle\u015ftirilir ve bir dizi ad\u0131m\u0131 takip eder:<\/p>\n<ol>\n<li><strong>Veri Ke\u015ffi:<\/strong> Bu, kaynak verilerin yap\u0131s\u0131n\u0131, format\u0131n\u0131 ve kalitesini anlamay\u0131 i\u00e7erir.<\/li>\n<li><strong>Veri haritalama:<\/strong> Bu ad\u0131m, bireysel veri alanlar\u0131n\u0131n veya niteliklerinin kaynaktan hedefe nas\u0131l d\u00f6n\u00fc\u015ft\u00fcr\u00fcld\u00fc\u011f\u00fcn\u00fc veya e\u015fle\u015ftirildi\u011fini tan\u0131mlamay\u0131 i\u00e7erir.<\/li>\n<li><strong>Kod Olu\u015fturma:<\/strong> Veri e\u015flemede tan\u0131mlanan d\u00f6n\u00fc\u015ft\u00fcrme mant\u0131\u011f\u0131, y\u00fcr\u00fct\u00fclebilir komut dosyalar\u0131 veya talimatlar olu\u015fturmak i\u00e7in kullan\u0131l\u0131r.<\/li>\n<li><strong>Uygulamak:<\/strong> Olu\u015fturulan kod, d\u00f6n\u00fc\u015f\u00fcmler verilere uygulanarak \u00e7al\u0131\u015ft\u0131r\u0131l\u0131r.<\/li>\n<li><strong>\u0130nceleme ve Revizyon:<\/strong> D\u00f6n\u00fc\u015ft\u00fcr\u00fclen veriler, gerekti\u011finde d\u00f6n\u00fc\u015ft\u00fcrme s\u00fcrecinde ayarlamalar yap\u0131larak kalite ve do\u011fruluk a\u00e7\u0131s\u0131ndan incelenir.<\/li>\n<\/ol>\n<h2>Veri D\u00f6n\u00fc\u015f\u00fcm\u00fcn\u00fcn Temel \u00d6zellikleri<\/h2>\n<ul>\n<li><strong>Veri Temizleme:<\/strong> Veri kalitesini art\u0131rmak i\u00e7in tutars\u0131zl\u0131klar\u0131, kopyalar\u0131 veya hatalar\u0131 ortadan kald\u0131r\u0131r.<\/li>\n<li><strong>Veri Standardizasyonu:<\/strong> Uyumlulu\u011fu ve entegrasyonu kolayla\u015ft\u0131rmak i\u00e7in \u00e7e\u015fitli verileri birle\u015fik, standart bir forma getirir.<\/li>\n<li><strong>Veri toplama:<\/strong> Analizi ve raporlamay\u0131 kolayla\u015ft\u0131rmak i\u00e7in verileri \u00f6zetler veya grupland\u0131r\u0131r.<\/li>\n<li><strong>Veri Zenginle\u015ftirme:<\/strong> \u0130lgili bilgileri ekleyerek, ba\u011flam\u0131n\u0131 ve b\u00fct\u00fcnl\u00fc\u011f\u00fcn\u00fc geli\u015ftirerek verileri geli\u015ftirir.<\/li>\n<\/ul>\n<h2>Veri D\u00f6n\u00fc\u015f\u00fcm\u00fc T\u00fcrleri<\/h2>\n<p>Verilerde yap\u0131lan de\u011fi\u015fikliklerin karma\u015f\u0131kl\u0131\u011f\u0131na ve niteli\u011fine g\u00f6re d\u00fczenlenebilecek \u00e7e\u015fitli veri d\u00f6n\u00fc\u015ft\u00fcrme t\u00fcrleri vard\u0131r:<\/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>Basit D\u00f6n\u00fc\u015f\u00fcmler<\/td>\n<td>Alanlar\u0131 yeniden adland\u0131rma, veri t\u00fcrlerini de\u011fi\u015ftirme veya metin dizelerini de\u011fi\u015ftirme gibi verilerde temel de\u011fi\u015fiklikler yap\u0131n.<\/td>\n<\/tr>\n<tr>\n<td>Temizlik D\u00f6n\u00fc\u015f\u00fcmleri<\/td>\n<td>Tekrarlar\u0131n veya tutars\u0131zl\u0131klar\u0131n kald\u0131r\u0131lmas\u0131 gibi veri kalitesinin iyile\u015ftirilmesini i\u00e7erir.<\/td>\n<\/tr>\n<tr>\n<td>Entegrasyon D\u00f6n\u00fc\u015f\u00fcmleri<\/td>\n<td>Farkl\u0131 kaynaklardan veya alanlardan gelen verileri birle\u015ftirmeyi i\u00e7erir.<\/td>\n<\/tr>\n<tr>\n<td>Geli\u015fmi\u015f D\u00f6n\u00fc\u015f\u00fcmler<\/td>\n<td>Metin madencili\u011fi veya duygu analizi gibi verilerde karma\u015f\u0131k de\u011fi\u015fiklikler yap\u0131n.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Veri D\u00f6n\u00fc\u015f\u00fcm\u00fcn\u00fcn Uygulamalar\u0131 ve Zorluklar\u0131<\/h2>\n<p>Veri d\u00f6n\u00fc\u015f\u00fcm\u00fc, veri ambar\u0131, veri entegrasyonu, makine \u00f6\u011frenimi ve i\u015f zekas\u0131 gibi \u00e7e\u015fitli alanlarda kullan\u0131lmaktad\u0131r. Bu alanlar\u0131n her birinde verilerin analiz, raporlama ve karar verme i\u00e7in haz\u0131rlanmas\u0131na yard\u0131mc\u0131 olur.<\/p>\n<p>Ancak s\u00fcre\u00e7 zorluklardan da ar\u0131nm\u0131yor. Yanl\u0131\u015f d\u00f6n\u00fc\u015f\u00fcmler hatal\u0131 sonu\u00e7lara veya veri kayb\u0131na yol a\u00e7abilece\u011finden, veri d\u00f6n\u00fc\u015f\u00fcm\u00fc dikkatli planlama ve y\u00fcr\u00fctme gerektirir. Ayr\u0131ca d\u00f6n\u00fc\u015f\u00fcmler, \u00f6zellikle b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in zaman al\u0131c\u0131 ve hesaplama a\u00e7\u0131s\u0131ndan pahal\u0131 olabilir. Bu sorunlar\u0131n \u00e7\u00f6z\u00fcmleri genellikle sa\u011flam veri d\u00f6n\u00fc\u015ft\u00fcrme ara\u00e7lar\u0131n\u0131n kullan\u0131lmas\u0131n\u0131, uygun planlamay\u0131 ve d\u00f6n\u00fc\u015f\u00fcm s\u00fcre\u00e7lerinin yinelemeli test edilmesini ve revizyonunu i\u00e7erir.<\/p>\n<h2>Kar\u015f\u0131la\u015ft\u0131rmalar ve \u00d6zellikler<\/h2>\n<p>\u0130lgili kavramlara g\u00f6re veri d\u00f6n\u00fc\u015ft\u00fcrmenin baz\u0131 kar\u015f\u0131la\u015ft\u0131rmalar\u0131 ve \u00f6zellikleri a\u015fa\u011f\u0131da verilmi\u015ftir:<\/p>\n<table>\n<thead>\n<tr>\n<th>Konsept<\/th>\n<th>Tan\u0131m<\/th>\n<th>Veri D\u00f6n\u00fc\u015f\u00fcm\u00fc ile \u0130li\u015fki<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Veri Entegrasyonu<\/td>\n<td>Farkl\u0131 kaynaklardan gelen verileri tutarl\u0131 bir veri deposunda birle\u015ftirme<\/td>\n<td>Veri d\u00f6n\u00fc\u015f\u00fcm\u00fc, \u00e7e\u015fitli veri kaynaklar\u0131 aras\u0131nda uyumlulu\u011fu sa\u011flayan veri entegrasyonunda \u00f6nemli bir ad\u0131md\u0131r.<\/td>\n<\/tr>\n<tr>\n<td>ETL (\u00c7\u0131karma, D\u00f6n\u00fc\u015ft\u00fcrme, Y\u00fckleme)<\/td>\n<td>Veri ambar\u0131 i\u00e7in bir veri hatt\u0131 s\u00fcreci<\/td>\n<td>Veri d\u00f6n\u00fc\u015f\u00fcm\u00fc, ETL&#039;deki &quot;T&quot; harfidir ve \u00e7\u0131kar\u0131lan verileri bir veri ambar\u0131na y\u00fcklemek \u00fczere d\u00f6n\u00fc\u015ft\u00fcr\u00fcr.<\/td>\n<\/tr>\n<tr>\n<td>Veri temizleme<\/td>\n<td>Bozuk veya hatal\u0131 kay\u0131tlar\u0131n tespit edilmesi ve d\u00fczeltilmesi s\u00fcreci<\/td>\n<td>Veri temizleme, veri d\u00f6n\u00fc\u015ft\u00fcrmenin bir alt k\u00fcmesi olarak d\u00fc\u015f\u00fcn\u00fclebilir.<\/td>\n<\/tr>\n<tr>\n<td>Veri g\u00f6\u00e7\u00fc<\/td>\n<td>Verileri bir sistemden di\u011ferine ta\u015f\u0131ma i\u015flemi<\/td>\n<td>Kaynak ve hedef sistemlerin yap\u0131lar\u0131n\u0131 e\u015fle\u015ftirmek i\u00e7in veri ge\u00e7i\u015finde genellikle veri d\u00f6n\u00fc\u015f\u00fcm\u00fc gereklidir.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Gelecek Perspektifleri ve Teknolojiler<\/h2>\n<p>Verilerin \u00f6l\u00e7e\u011fi ve karma\u015f\u0131kl\u0131\u011f\u0131 b\u00fcy\u00fcmeye devam ettik\u00e7e veri d\u00f6n\u00fc\u015f\u00fcm\u00fc gelecekte daha da \u00f6nemli hale gelecektir. B\u00fcy\u00fck veri ve makine \u00f6\u011frenimi gibi trendler, y\u00fcksek kaliteli, iyi yap\u0131land\u0131r\u0131lm\u0131\u015f veriler talep ediyor ve etkili veri d\u00f6n\u00fc\u015f\u00fcm\u00fc ihtiyac\u0131n\u0131 vurguluyor.<\/p>\n<p>Ayr\u0131ca, veri d\u00f6n\u00fc\u015ft\u00fcrme s\u00fcrecini otomatikle\u015ftirmek ve optimize etmek i\u00e7in yapay zeka (AI) ve makine \u00f6\u011frenimi algoritmalar\u0131 gibi yeni ortaya \u00e7\u0131kan teknolojiler kullan\u0131l\u0131yor. Bu teknolojiler daha karma\u015f\u0131k d\u00f6n\u00fc\u015f\u00fcmlerin \u00fcstesinden gelebilir, d\u00f6n\u00fc\u015ft\u00fcr\u00fclen verilerin kalitesini art\u0131rabilir ve gereken zaman ve \u00e7abay\u0131 azaltabilir.<\/p>\n<h2>Proxy Sunucular ve Veri D\u00f6n\u00fc\u015f\u00fcm\u00fc<\/h2>\n<p>Proxy sunucular\u0131, \u00f6zellikle web veri \u00e7\u0131karma veya web kaz\u0131ma ba\u011flam\u0131nda, veri d\u00f6n\u00fc\u015ft\u00fcrme s\u00fcrecinde rol oynayabilir. Proxy sunucular\u0131, web sunucular\u0131ndan veri toplayarak, veri nihai var\u0131\u015f noktas\u0131na ula\u015fmadan \u00f6nce veri d\u00f6n\u00fc\u015ft\u00fcrme i\u015flemlerinin ger\u00e7ekle\u015ftirilebilece\u011fi ek bir katman sa\u011flayabilir. Bu, verileri temizlemeyi, yeniden bi\u00e7imlendirmeyi ve hatta ek bilgilerle geni\u015fletmeyi i\u00e7erebilir. Sonu\u00e7 olarak, bu uygulama, \u00f6zellikle OneProxy gibi \u015firketler taraf\u0131ndan sa\u011flanan anonim veya d\u00f6n\u00fc\u015f\u00fcml\u00fc proxy&#039;ler durumunda, veri gizlili\u011finin ve g\u00fcvenli\u011finin sa\u011flanmas\u0131na yard\u0131mc\u0131 olabilir.<\/p>\n<h2>\u0130lgili Ba\u011flant\u0131lar<\/h2>\n<ul>\n<li><a href=\"https:\/\/docs.microsoft.com\/en-us\/sql\/integration-services\/data-flow\/transformations\/data-flow-transformations?view=sql-server-ver15\" target=\"_new\" rel=\"noopener nofollow\">SQL Server&#039;da Veri D\u00f6n\u00fc\u015ft\u00fcrme Hizmetleri<\/a><\/li>\n<li><a href=\"https:\/\/www.datamation.com\/big-data\/data-transformation-tools.html\" target=\"_new\" rel=\"noopener nofollow\">Veri D\u00f6n\u00fc\u015ft\u00fcrme Ara\u00e7lar\u0131 ve Teknikleri<\/a><\/li>\n<li><a href=\"https:\/\/towardsdatascience.com\/data-preprocessing-concepts-fa946d11c825\" target=\"_new\" rel=\"noopener nofollow\">Makine \u00d6\u011freniminde Veri D\u00f6n\u00fc\u015f\u00fcm\u00fc<\/a><\/li>\n<\/ul>","protected":false},"featured_media":468152,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-476718","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Data Transformation: An Overview<\/mark>","faq_items":[{"question":"What is Data Transformation?","answer":"<p>Data transformation is a crucial process in data management that involves converting data from one format or structure into another. Its primary purpose is to improve data quality, compatibility, and usefulness for different applications, especially in data analysis and decision-making contexts.<\/p>"},{"question":"When was Data Transformation first mentioned?","answer":"<p>Data transformation, as we understand it today, was first mentioned in the context of Extract, Transform, Load (ETL) processes in the 1970s. These processes were pivotal in moving data from operational databases to decision support databases.<\/p>"},{"question":"What are the main steps involved in Data Transformation?","answer":"<p>The main steps involved in data transformation are data discovery, data mapping, code generation, execution, and review &amp; revision. These steps may vary based on the data and the transformation tools used.<\/p>"},{"question":"What are some key features of Data Transformation?","answer":"<p>Key features of data transformation include data cleansing (removing errors and inconsistencies), data standardization (making data compatible for integration), data aggregation (summarizing or grouping data), and data enrichment (improving data by adding related information).<\/p>"},{"question":"What are some types of Data Transformation?","answer":"<p>Data transformation types can be categorized into simple transformations, cleaning transformations, integration transformations, and advanced transformations based on the complexity and nature of the changes made to the data.<\/p>"},{"question":"What are some applications and challenges of Data Transformation?","answer":"<p>Data transformation is used in fields like data warehousing, data integration, machine learning, and business intelligence. The challenges of data transformation include the need for careful planning and execution, the time-consuming nature of the process, and the potential for data loss or inaccuracies.<\/p>"},{"question":"How is Data Transformation related to future technologies?","answer":"<p>Data transformation is expected to become even more important as the scale and complexity of data continue to grow. Emerging technologies like artificial intelligence (AI) and machine learning algorithms are beginning to be used to automate and optimize the data transformation process.<\/p>"},{"question":"What is the connection between Proxy Servers and Data Transformation?","answer":"<p>Proxy servers, particularly in the context of web data extraction or web scraping, can provide an additional layer where data transformation operations are performed. They can collect data, reformat, clean, or augment it before the data reaches its final destination. This can also help to ensure data privacy and security.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476718","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\/476718\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media\/468152"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media?parent=476718"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}