{"id":29989,"date":"2025-09-22T15:40:15","date_gmt":"2025-09-22T12:40:15","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/?p=29989"},"modified":"2025-09-22T17:02:48","modified_gmt":"2025-09-22T14:02:48","slug":"e-ticaret-trendlerinin-buyuk-veri-big-data-ile-analizi","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/e-ticaret-trendlerinin-buyuk-veri-big-data-ile-analizi\/","title":{"rendered":"E-Ticaret Trendlerinin B\u00fcy\u00fck Veri (Big Data) ile Analizi"},"content":{"rendered":"<div class=\"ead-preview\"><div class=\"ead-document\" style=\"position: relative;width: 100%;height: 100%;border: none;min-height: 500px;\" data-pdf-src=\"https:\/\/fatihsoysal.com\/blog\/wp-content\/uploads\/2025\/09\/E-Ticaret-Trendlerinin-Buyuk-Veri-Big-Data-ile-Analizi.pdf\" data-viewer=\"browser\"><div class=\"ead-iframe-wrapper\"><iframe src=\"\/\/docs.google.com\/viewer?url=https%3A%2F%2Ffatihsoysal.com%2Fblog%2Fwp-content%2Fuploads%2F2025%2F09%2FE-Ticaret-Trendlerinin-Buyuk-Veri-Big-Data-ile-Analizi.pdf&amp;embedded=true&amp;hl=en\" title=\"Embedded Document\" class=\"ead-iframe\" style=\"width: 100%;height: 100%;border: none;min-height: 500px;visibility: hidden;\"><\/iframe><\/div>\t\t\t<div class=\"ead-document-loading\" style=\"width:100%;height:100%;position:absolute;left:0;top:0;z-index:10;\">\n\t\t\t\t<div class=\"ead-loading-wrap\">\n\t\t\t\t\t<div class=\"ead-loading-main\">\n\t\t\t\t\t\t<div class=\"ead-loading\">\n\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/fatihsoysal.com\/blog\/wp-content\/plugins\/embed-any-document\/images\/loading.svg\" width=\"55\" height=\"55\" alt=\"Loader\">\n\t\t\t\t\t\t\t<span>Loading...<\/span>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"ead-loading-foot\">\n\t\t\t\t\t\t<div class=\"ead-loading-foot-title\">\n\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/fatihsoysal.com\/blog\/wp-content\/plugins\/embed-any-document\/images\/EAD-logo.svg\" alt=\"EAD Logo\" width=\"36\" height=\"23\"\/>\n\t\t\t\t\t\t\t<span>Taking too long?<\/span>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<p>\n\t\t\t\t\t\t\t<div class=\"ead-document-btn ead-reload-btn\" role=\"button\">\n\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/fatihsoysal.com\/blog\/wp-content\/plugins\/embed-any-document\/images\/reload.svg\" alt=\"Reload\" width=\"12\" height=\"12\"\/> Reload document\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<span>|<\/span>\n\t\t\t\t\t\t\t<a href=\"#\" class=\"ead-document-btn\" target=\"_blank\">\n\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/fatihsoysal.com\/blog\/wp-content\/plugins\/embed-any-document\/images\/open.svg\" alt=\"Open\" width=\"12\" height=\"12\"\/> Open in new tab\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div><\/div>\n<h3>\u00d6zet<\/h3>\n<p class=\"ds-markdown-paragraph\">B\u00fcy\u00fck veri, d\u00fcnya ekonomisini ve toplumsal de\u011fi\u015fimleri y\u00f6nlendiren yeni bir itici g\u00fc\u00e7t\u00fcr. D\u00fcnyadaki veri birikimi, karar verme, sa\u011fl\u0131k y\u00f6netimi, \u015fehir planlama, finans ve e\u011fitim alanlar\u0131nda yeni yakla\u015f\u0131mlar getirebilecek b\u00fcy\u00fck teknolojik d\u00f6n\u00fc\u015f\u00fcmler i\u00e7in bir d\u00f6n\u00fcm noktas\u0131na ula\u015fmaktad\u0131r. Verinin hacmi, \u00e7e\u015fitlili\u011fi, h\u0131z\u0131 ve do\u011frulu\u011fu gibi karma\u015f\u0131kl\u0131klar artsa da, as\u0131l etki B\u00fcy\u00fck Veri Analiti\u011fi teknolojileri arac\u0131l\u0131\u011f\u0131yla verideki &#8216;de\u011feri&#8217; ortaya \u00e7\u0131karma yetene\u011fimize ba\u011fl\u0131d\u0131r. B\u00fcy\u00fck Veri Analiti\u011fi, farkl\u0131, karma\u015f\u0131k ve b\u00fcy\u00fck \u00f6l\u00e7ekli veri k\u00fcmelerinden de\u011fer elde etmek i\u00e7in y\u00fcksek \u00f6l\u00e7eklenebilir algoritmalar\u0131n ve sistemlerin tasar\u0131m\u0131nda b\u00fcy\u00fck bir zorluk te\u015fkil etmektedir.<\/p>\n<p class=\"ds-markdown-paragraph\"><strong>Anahtar Kelimeler:<\/strong>\u00a0Analitik, Algoritmalar, Veri Depolama, Bulut Bili\u015fim, Nesnelerin \u0130nterneti (IoT), B\u00fcy\u00fck Veri \u0130\u015fleme<\/p>\n<h3>Giri\u015f<\/h3>\n<p class=\"ds-markdown-paragraph\">Veri depolaman\u0131n olmad\u0131\u011f\u0131 bir d\u00fcnya d\u00fc\u015f\u00fcn\u00fcn: bir ki\u015fi veya kurulu\u015fla ilgili her detay, ger\u00e7ekle\u015ftirilen her i\u015flem veya belgelenebilecek her unsur, kullan\u0131mdan hemen sonra kaybolsun. Bu durumda kurulu\u015flar, de\u011ferli bilgi ve bilgiyi \u00e7\u0131karma, ayr\u0131nt\u0131l\u0131 analizler yapma ve yeni f\u0131rsatlar ile avantajlar sa\u011flama yeteneklerini kaybederler. M\u00fc\u015fteri adlar\u0131 ve adreslerinden, mevcut \u00fcr\u00fcnlere, yap\u0131lan sat\u0131n al\u0131mlardan, i\u015fe al\u0131nan \u00e7al\u0131\u015fanlara kadar her \u015fey, g\u00fcnl\u00fck i\u015fleyi\u015fin s\u00fcreklili\u011fi i\u00e7in hayati \u00f6nem ta\u015f\u0131r. Veri, her kurulu\u015fun geli\u015fiminin temel yap\u0131 ta\u015f\u0131d\u0131r. G\u00fcn\u00fcm\u00fczde teknolojideki ve internet alan\u0131ndaki geli\u015fmelerle birlikte sa\u011flanan veri ve bilgi miktar\u0131ndaki patlama d\u00fc\u015f\u00fcn\u00fcld\u00fc\u011f\u00fcnde, depolama kapasitelerinin ve veri toplama y\u00f6ntemlerinin artmas\u0131yla b\u00fcy\u00fck miktarda veri kolayca eri\u015filebilir hale gelmi\u015ftir. Her saniye daha fazla veri \u00fcretilmekte ve de\u011fer elde etmek i\u00e7in depolanmas\u0131 ve analiz edilmesi gerekmektedir. Ayr\u0131ca, veriyi depolaman\u0131n maliyeti d\u00fc\u015ft\u00fc\u011f\u00fc i\u00e7in kurulu\u015flar\u0131n depolanan b\u00fcy\u00fck miktardaki veriden olabildi\u011fince fazla de\u011fer elde etmesi gerekmektedir. Bu t\u00fcr verilerin boyutu, \u00e7e\u015fitlili\u011fi ve h\u0131zl\u0131 de\u011fi\u015fimi, yeni bir b\u00fcy\u00fck veri analiti\u011fi t\u00fcr\u00fcn\u00fcn yan\u0131 s\u0131ra farkl\u0131 depolama ve analiz y\u00f6ntemlerini de gerektirir. Bu kadar b\u00fcy\u00fck miktardaki verinin uygun \u015fekilde analiz edilmesi ve ilgili bilginin \u00e7\u0131kar\u0131lmas\u0131 gerekir. Bu makalenin katk\u0131s\u0131, b\u00fcy\u00fck veri analiti\u011fi konusundaki mevcut literat\u00fcr\u00fcn bir analizini sunmakt\u0131r. Bu ba\u011flamda, uygulanabilecek \u00e7e\u015fitli b\u00fcy\u00fck veri ara\u00e7lar\u0131, y\u00f6ntemleri ve teknolilerinden baz\u0131lar\u0131 tart\u0131\u015f\u0131lmakta ve bunlar\u0131n \u00e7e\u015fitli karar alanlar\u0131ndaki uygulamalar\u0131 ve sa\u011flad\u0131\u011f\u0131 f\u0131rsatlar betimlenmektedir.<\/p>\n<hr \/>\n<h3>B\u00fcy\u00fck Veri \u0130\u015fleme Ara\u00e7lar\u0131<\/h3>\n<p class=\"ds-markdown-paragraph\">B\u00fcy\u00fck veriyi i\u015flemek i\u00e7in \u00e7ok say\u0131da ara\u00e7 mevcuttur. Bu b\u00f6l\u00fcmde, b\u00fcy\u00fck veriyi analiz etmek i\u00e7in g\u00fcncel teknikler, \u00f6zellikle \u00fc\u00e7 \u00f6nemli yeni ara\u00e7 olan MapReduce, Apache Spark ve Storm vurgulanarak ele al\u0131nmaktad\u0131r. Mevcut ara\u00e7lar\u0131n \u00e7o\u011fu toplu i\u015flem, ak\u0131\u015f i\u015fleme ve etkile\u015fimli analize odaklan\u0131r. Toplu i\u015flem ara\u00e7lar\u0131n\u0131n \u00e7o\u011fu, Mahout ve Dryad gibi Apache Hadoop altyap\u0131s\u0131na dayanmaktad\u0131r.<\/p>\n<ol start=\"1\">\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>Apache Hadoop ve MapReduce:<\/strong>\u00a0B\u00fcy\u00fck veri analizi i\u00e7in en yerle\u015fik yaz\u0131l\u0131m platformu Apache Hadoop ve MapReduce&#8217;dur. Hadoop \u00e7ekirde\u011fi, MapReduce, Hadoop Da\u011f\u0131t\u0131lm\u0131\u015f Dosya Sistemi (HDFS) ve Apache Hive gibi bile\u015fenlerden olu\u015fur.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>Apache Mahout:<\/strong>\u00a0Apache Mahout, b\u00fcy\u00fck \u00f6l\u00e7ekli ve ak\u0131ll\u0131 veri analizi uygulamalar\u0131 i\u00e7in \u00f6l\u00e7eklenebilir ve ticari makine \u00f6\u011frenimi teknikleri sa\u011flamay\u0131 ama\u00e7lar. Mahout&#8217;un k\u00fcmeleme, s\u0131n\u0131fland\u0131rma, \u00f6r\u00fcnt\u00fc madencili\u011fi, regresyon, boyutsall\u0131\u011f\u0131 azaltma, evrimsel algoritmalar ve toplu temelli i\u015fbirlik\u00e7i filtreleme gibi temel algoritmalar\u0131, MapReduce \u00e7er\u00e7evesi arac\u0131l\u0131\u011f\u0131yla Hadoop platformu \u00fczerinde \u00e7al\u0131\u015f\u0131r.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>Apache Spark:<\/strong>\u00a0Apache Spark, h\u0131zl\u0131 i\u015fleme ve sofistike analizler i\u00e7in olu\u015fturulmu\u015f a\u00e7\u0131k kaynakl\u0131 bir b\u00fcy\u00fck veri i\u015fleme \u00e7er\u00e7evesidir. Kullan\u0131m\u0131 kolayd\u0131r ve orijinal olarak 2009&#8217;da UC Berkeley&#8217;deki AMP Lab&#8217;da geli\u015ftirilmi\u015ftir. 2010&#8217;da bir Apache projesi olarak a\u00e7\u0131k kaynakl\u0131 hale getirilmi\u015ftir. Spark, Java, Scala veya Python&#8217;da h\u0131zl\u0131 bir \u015fekilde uygulama yazman\u0131za olanak tan\u0131r. MapReduce i\u015flemlerine ek olarak SQL sorgular\u0131n\u0131, ak\u0131\u015f verilerini, makine \u00f6\u011frenimini ve grafik veri i\u015flemeyi destekler. Spark, mevcut HDFS altyap\u0131s\u0131 \u00fczerinde \u00e7al\u0131\u015farak geli\u015fmi\u015f ve ek i\u015flevsellik sa\u011flar.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>Dryad:<\/strong>\u00a0B\u00fcy\u00fck veri k\u00fcmelerini i\u015flemek i\u00e7in paralel ve da\u011f\u0131t\u0131k programlar\u0131 uygulamak \u00fczere veri ak\u0131\u015f grafi\u011fine dayal\u0131 pop\u00fcler bir programlama modelidir. Bir bilgisayar k\u00fcmesi kaynaklar\u0131n\u0131 kullanarak programlar\u0131 da\u011f\u0131t\u0131k bir \u015fekilde \u00e7al\u0131\u015ft\u0131rmay\u0131 sa\u011flar.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>Storm:<\/strong>\u00a0Storm, b\u00fcy\u00fck ak\u0131\u015f verilerini i\u015flemek i\u00e7in da\u011f\u0131t\u0131k ve hata toleransl\u0131 bir ger\u00e7ek zamanl\u0131 hesaplama sistemidir. Toplu i\u015flem i\u00e7in olan Hadoop&#8217;un aksine, \u00f6zellikle ger\u00e7ek zamanl\u0131 i\u015flem i\u00e7in tasarlanm\u0131\u015ft\u0131r.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>Apache Drill:<\/strong>\u00a0Apache Drill, b\u00fcy\u00fck verinin etkile\u015fimli analizi i\u00e7in ba\u015fka bir da\u011f\u0131t\u0131k sistemdir. Bir\u00e7ok sorgu dili, veri format\u0131 ve veri kayna\u011f\u0131n\u0131 destekleme konusunda daha fazla esnekli\u011fe sahiptir.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>JasperSoft:<\/strong>\u00a0JasperSoft paketi, veritaban\u0131 s\u00fctunlar\u0131ndan rapor \u00fcreten a\u00e7\u0131k kaynakl\u0131 bir yaz\u0131l\u0131md\u0131r. \u00d6l\u00e7eklenebilir bir b\u00fcy\u00fck veri analitik platformudur ve MongoDB, Cassandra, Redis gibi pop\u00fcler depolama platformlar\u0131nda h\u0131zl\u0131 veri g\u00f6rselle\u015ftirme yetene\u011fine sahiptir. JasperSoft&#8217;un \u00f6nemli bir \u00f6zelli\u011fi, veriyi \u00e7\u0131karma, d\u00f6n\u00fc\u015ft\u00fcrme ve y\u00fckleme (ETL) olmadan b\u00fcy\u00fck veriyi h\u0131zla ke\u015ffedebilmesidir.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>Splunk:<\/strong>\u00a0Son y\u0131llarda i\u015f d\u00fcnyas\u0131nda makineler arac\u0131l\u0131\u011f\u0131yla \u00e7ok fazla veri \u00fcretilmektedir. Splunk, makine taraf\u0131ndan \u00fcretilen b\u00fcy\u00fck veriyi de\u011ferlendirmek i\u00e7in geli\u015ftirilmi\u015f ger\u00e7ek zamanl\u0131 ve ak\u0131ll\u0131 bir platformdur. En g\u00fcncel bulut teknolojileri ve b\u00fcy\u00fck veriyi birle\u015ftirir.<\/p>\n<\/li>\n<\/ol>\n<hr \/>\n<h3>IoT ve B\u00fcy\u00fck Veri Analiti\u011fi<\/h3>\n<p class=\"ds-markdown-paragraph\">Cihazlar taraf\u0131ndan toplanan verilerin ilgili ve faydal\u0131 hale getirilmesi i\u00e7in filtrelenmesi gerekir. IoT altyap\u0131s\u0131n\u0131n do\u011fas\u0131 gere\u011fi, toplanan veride fazlal\u0131k yayg\u0131nd\u0131r. Veri s\u00fcrekli oldu\u011fu i\u00e7in de\u011ferli bilginin \u00e7\u0131kar\u0131lmas\u0131 kolay de\u011fildir. Bu da, verinin hem g\u00fcvende hem de anlaml\u0131 olmas\u0131n\u0131 sa\u011flayacak iyi bir protokol ve yaz\u0131l\u0131m mekanizmas\u0131 gerektirir.<\/p>\n<hr \/>\n<h3>B\u00fcy\u00fck Veri i\u00e7in Bulut Bili\u015fim<\/h3>\n<p class=\"ds-markdown-paragraph\">Bulut bili\u015fim, sunucular, depolama, veritabanlar\u0131, a\u011f, yaz\u0131l\u0131m, analiz vb. bili\u015fim hizmetlerinin esnek kaynaklar, daha h\u0131zl\u0131 inovasyon ve \u00f6l\u00e7ek ekonomisi sa\u011flama amac\u0131yla internet (&#8220;bulut&#8221;) \u00fczerinden sunulmas\u0131d\u0131r. Bulut bili\u015fim, bili\u015fim altyap\u0131s\u0131n\u0131n soyutlanma ve kullan\u0131lma \u015feklini k\u00f6kten de\u011fi\u015ftirmi\u015ftir.<\/p>\n<hr \/>\n<h3>Sorunlar ve Zorluklar<\/h3>\n<p class=\"ds-markdown-paragraph\">B\u00fcy\u00fck verideki zorluklar genel olarak \u00fc\u00e7 t\u00fcre ayr\u0131labilir: veri zorluklar\u0131, i\u015flem zorluklar\u0131 ve y\u00f6netim zorluklar\u0131. Veri zorluklar\u0131, b\u00fcy\u00fck verinin karakteristik \u00f6zellikleriyle ili\u015fkilidir. \u0130\u015flem zorluklar\u0131, verinin i\u015flenmesi s\u0131ras\u0131nda kar\u015f\u0131la\u015f\u0131lan zorluklarken; y\u00f6netim zorluklar\u0131, g\u00fcvenlik sa\u011flama gibi veriyi ele alma ile ilgilidir.<\/p>\n<ul>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>Hacim Zorluklar\u0131:<\/strong>\u00a0\u0130\u00e7 ve d\u0131\u015f kaynaklardan gelen verideki benzeri g\u00f6r\u00fclmemi\u015f art\u0131\u015f, \u00e7ok b\u00fcy\u00fck miktarda veriyle sonu\u00e7lanm\u0131\u015ft\u0131r. Bu durum, verinin depolanmas\u0131 gibi geleneksel ara\u00e7larla \u00e7\u00f6z\u00fclemeyen zorluklar getirir.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>\u00c7e\u015fitlilik Zorluklar\u0131:<\/strong>\u00a0Verinin yap\u0131land\u0131r\u0131lm\u0131\u015f, yar\u0131 yap\u0131land\u0131r\u0131lm\u0131\u015f ve yap\u0131land\u0131r\u0131lmam\u0131\u015f formlarda bulunmas\u0131yla ili\u015fkilidir. Ara\u015ft\u0131rmalar, verinin %95&#8217;inin yap\u0131land\u0131r\u0131lmam\u0131\u015f formda oldu\u011funu g\u00f6stermektedir. Analiz yap\u0131labilmesi i\u00e7in uygun forma d\u00f6n\u00fc\u015ft\u00fcr\u00fclmesi b\u00fcy\u00fck bir zorluktur.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\"><strong>H\u0131z Zorluklar\u0131:<\/strong>\u00a0H\u0131z, cihazlar taraf\u0131ndan \u00fcretilen verinin ak\u0131\u015f s\u00fcratini ifade eder. Veri toplu i\u015fleme veya ger\u00e7ek zamanl\u0131 i\u015fleme yoluyla i\u015flenebilir. \u00c7evrimi\u00e7i al\u0131\u015fveri\u015f gibi alanlarda m\u00fc\u015fteri i\u00e7in de\u011fer yaratmak i\u00e7in ger\u00e7ek zamanl\u0131 i\u015fleme gerekir.<\/p>\n<\/li>\n<\/ul>\n<hr \/>\n<h3>Gelecek \u00c7al\u0131\u015fmalar i\u00e7in \u00d6neriler<\/h3>\n<p class=\"ds-markdown-paragraph\">Pek \u00e7ok b\u00fcy\u00fck \u015firket bu trendleri tamamen benimsemi\u015f veya benimseme e\u015fi\u011fine gelmi\u015f olsa da, b\u00fcy\u00fck veri analiti\u011finin gelece\u011fi art\u0131k y\u00fcksek maliyet duvarlar\u0131n\u0131n ard\u0131na kilitli de\u011fildir. Veri m\u00fchendisleri ve bilimcileri, Fortune 500 b\u00fct\u00e7esi gerektirmeden veri y\u0131\u011f\u0131n\u0131n\u0131n alt\u0131nda gizli i\u00e7g\u00f6r\u00fcleri ortaya \u00e7\u0131karmak i\u00e7in yenilik\u00e7i yollar geli\u015ftirmektedir. \u00d6n\u00fcm\u00fczdeki d\u00f6nemde, k\u00fc\u00e7\u00fck ve orta \u00f6l\u00e7ekli \u015firketlerin de i\u015f stratejilerine b\u00fcy\u00fck veri analiti\u011fini dahil etmeleri beklenmektedir.<\/p>\n<hr \/>\n<h3>Y\u00f6ntem<\/h3>\n<p class=\"ds-markdown-paragraph\">B\u00fcy\u00fck veri analiti\u011fi, gerekli bilgiyi ke\u015ffetmek amac\u0131yla veriyi toplama, d\u00f6n\u00fc\u015ft\u00fcrme, temizleme ve modelleme s\u00fcrecidir. Bir ara\u015ft\u0131rmada, e-ticaret web sitelerinden \u00fcr\u00fcn sat\u0131n alan kullan\u0131c\u0131ya ili\u015fkin sonu\u00e7lara ula\u015fmada ara\u015ft\u0131rmac\u0131y\u0131 destekler.<\/p>\n<hr \/>\n<h3>Sonu\u00e7<\/h3>\n<p class=\"ds-markdown-paragraph\">B\u00fcy\u00fck Veri&#8217;nin bulunabilirli\u011fi, d\u00fc\u015f\u00fck maliyetli donan\u0131mlar ve yeni bilgi y\u00f6netimi ve analitik yaz\u0131l\u0131mlar, veri analizi tarihinde benzersiz bir an yaratm\u0131\u015ft\u0131r. Bu trendlerin birle\u015fimi, tarihte ilk kez, \u015fa\u015f\u0131rt\u0131c\u0131 derecede b\u00fcy\u00fck veri k\u00fcmelerini h\u0131zl\u0131 ve uygun maliyetli bir \u015fekilde analiz etme kapasitesine sahip oldu\u011fumuz anlam\u0131na gelir. Bu yetenekler ne teorik ne de \u00f6nemsizdir. Verimlilik, \u00fcretkenlik, gelir ve karl\u0131l\u0131k a\u00e7\u0131s\u0131ndan muazzam kazan\u0131mlar elde etmek i\u00e7in ger\u00e7ek bir s\u0131\u00e7rama ve net bir f\u0131rsat temsil ederler. B\u00fcy\u00fck Veri \u00c7a\u011f\u0131 buradad\u0131r ve hem i\u015f hem de teknoloji profesyonelleri birlikte \u00e7al\u0131\u015fmaya ve vaadi yerine getirmeye devam ettikleri s\u00fcrece, bunlar ger\u00e7ekten devrimci zamanlard\u0131r.<\/p>\n<hr \/>\n<h3>Kaynak\u00e7a<\/h3>\n<ol start=\"1\">\n<li>\n<p class=\"ds-markdown-paragraph\">Demirkan, H., Delen, D. (2013). Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud.\u00a0<em>Decision Support Systems<\/em>, 55, 412\u2013421.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Barton, D., Court, D. (2012). Making Advanced Analytics Work For You.\u00a0<em>Harvard Business Review<\/em>, 90(10), 79\u201383.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">McAfee, A., Brynjolfsson, E. (2012). Big data: the management revolution.\u00a0<em>Harvard Business Review<\/em>, 90(10), 60\u201368.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Wu, X., et al. (2014). Data mining with big data.\u00a0<em>IEEE Transactions on Knowledge and Data Engineering<\/em>, 28, 97\u2013106.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">P\u00e4\u00e4kk\u00f6nen, P., Pakkala, D. (2015). Reference Architecture and Classification of Technologies, Products and Services for Big Data Systems.\u00a0<em>Big Data Research<\/em>, 2, 166\u2013186.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Thusoo, A., et al. (2010). Data warehousing and analytics infrastructure at Facebook.\u00a0<em>Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data<\/em>.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Kreps, J., Narkhede, N., Rao, J. (2011). Kafka: a distributed messaging system for log processing.\u00a0<em>Proceedings of the 6th International Workshop on Networking Meets Databases<\/em>.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Wu, L., et al. (2012). Avatar: OLAP for web-scale analytics products.\u00a0<em>Proceedings of the 38th International Conference on Very Large Databases<\/em>.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Mishne, G. (2013). Fast data in the era of big data: Twitter\u2019s real-time related query suggestion architecture.\u00a0<em>Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data<\/em>.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Lin, J., Ryaboy, D. (2013). Scaling big data mining infrastructure: the Twitter experience.\u00a0<em>ACM SIGKDD Explorations Newsletter<\/em>, 14, 6\u201319.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Lee, G. L., et al. (2012). The unified logging infrastructure for data analytics at Twitter.\u00a0<em>Proceedings of the 38th International Conference on Very Large Databases<\/em>.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Busch, M., et al. (2012). EarlyBird: real-time search at Twitter.\u00a0<em>Proceedings of the 2012 IEEE 28th International Conference on Data Engineering<\/em>.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Amatriain, X. (2013). Big &amp; Personal: data and models behind Netflix recommendations.\u00a0<em>Proceedings of the 2nd International Workshop on Big Data, Streams and Heterogeneous Source Mining<\/em>.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Amatriain, X., Basilico, J. (2013). System architectures for personalized recommendations.\u00a0<em>Netflix Tech Blog<\/em>.<\/p>\n<\/li>\n<li>\n<p class=\"ds-markdown-paragraph\">Boulon, J., Konwinski, A., Qi, R. (2008). Chukwa: a large-scale monitoring system.\u00a0<em>Proceedings of the Cloud Computing and Its Applications Workshop<\/em>.<\/p>\n<\/li>\n<\/ol>\n<p class=\"ds-markdown-paragraph\"><strong><a href=\"https:\/\/fatihsoysal.com\/blog\/wp-content\/uploads\/2025\/09\/E-Ticaret-Trendlerinin-Buyuk-Veri-Big-Data-ile-Analizi.pdf\">Makalenin PDF s\u00fcr\u00fcm\u00fcne buradan ula\u015fabilirsiniz: E-Ticaret Trendlerinin B\u00fcy\u00fck Veri (Big Data) ile Analizi<\/a><\/strong><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"\u00d6zet B\u00fcy\u00fck veri, d\u00fcnya ekonomisini ve toplumsal de\u011fi\u015fimleri y\u00f6nlendiren yeni bir itici g\u00fc\u00e7t\u00fcr. D\u00fcnyadaki veri birikimi, karar verme,&hellip;","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_page_header_type":"","csco_page_load_nextpost":"","csco_page_subscribe_form":"","csco_page_contact_form":"","footnotes":""},"categories":[1470],"tags":[1472,1471,1398,1475,1474,1473],"class_list":{"0":"post-29989","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-akademik-ve-bilimsel","7":"tag-algoritmalar","8":"tag-analitik","9":"tag-bulut-bilisim","10":"tag-buyuk-veri-isleme","11":"tag-nesnelerin-interneti-iot","12":"tag-veri-depolama","13":"cs-entry","14":"cs-video-wrap"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.5 (Yoast SEO v25.3.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>E-Ticaret Trendlerinin B\u00fcy\u00fck Veri (Big Data) ile Analizi - Kodlar\u0131n Gizemli D\u00fcnyas\u0131<\/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:\/\/fatihsoysal.com\/blog\/e-ticaret-trendlerinin-buyuk-veri-big-data-ile-analizi\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"E-Ticaret Trendlerinin B\u00fcy\u00fck Veri (Big Data) ile Analizi\" \/>\n<meta property=\"og:description\" content=\"\u00d6zet B\u00fcy\u00fck veri, d\u00fcnya ekonomisini ve toplumsal de\u011fi\u015fimleri y\u00f6nlendiren yeni bir itici g\u00fc\u00e7t\u00fcr. 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