{"id":476729,"date":"2023-08-09T07:35:16","date_gmt":"2023-08-09T07:35:16","guid":{"rendered":""},"modified":"2023-09-05T11:13:19","modified_gmt":"2023-09-05T11:13:19","slug":"data-warehouse","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/tr\/wiki\/data-warehouse\/","title":{"rendered":"Veri deposu"},"content":{"rendered":"

Veri ambar\u0131, bir veri ambar\u0131n\u0131n olu\u015fturulmas\u0131 ve kullan\u0131lmas\u0131 s\u00fcrecini ifade eder. Veri ambar\u0131, raporlama ve veri analizi i\u00e7in kullan\u0131lan ve genellikle bir kurulu\u015fta karar almay\u0131 desteklemek amac\u0131yla farkl\u0131 kaynaklardan gelen verileri birle\u015ftirmek i\u00e7in kullan\u0131lan bir sistemdir. \u0130\u015fletmelerin i\u00e7g\u00f6r\u00fc elde etmek, operasyonlar\u0131 optimize etmek ve bilin\u00e7li stratejik kararlar almak i\u00e7in verilerini incelemesine ve analiz etmesine olanak tan\u0131yarak i\u015f zekas\u0131nda \u00f6nemli bir rol oynar.<\/p>\n

Veri Depolaman\u0131n Do\u011fu\u015fu<\/h2>\n

Veri ambar\u0131 kavram\u0131 ilk olarak 1970'lerde Bill Inmon taraf\u0131ndan \u00f6nerildi. Inmon, yayg\u0131n olarak "veri ambar\u0131n\u0131n babas\u0131" olarak tan\u0131n\u0131r ve veri ambar\u0131n\u0131, y\u00f6netimin karar verme s\u00fcrecini destekleyen, konu odakl\u0131, entegre, zamanla de\u011fi\u015fen ve kal\u0131c\u0131 bir veri koleksiyonu olarak tan\u0131mlad\u0131. Bir \u201cveri ambar\u0131\u201dndan ilk kez Barry Devlin ve Paul Murphy taraf\u0131ndan, bilgi sistemlerinin kalbinde yer alan bir veri ambar\u0131n\u0131n mimarisinin ana hatlar\u0131n\u0131 \u00e7izdikleri 1988 tarihli bir makalede bahsedilmi\u015ftir.<\/p>\n

Veri Ambarlamay\u0131 Ayr\u0131nt\u0131l\u0131 Olarak Ke\u015ffetmek<\/h2>\n

Bir veri ambar\u0131 \u00f6ncelikle farkl\u0131 kaynaklardan gelen verileri sorgulama ve analiz i\u00e7in elveri\u015fli bir formatta depolamak i\u00e7in kullan\u0131l\u0131r. Bir veri ambar\u0131 sistemine giren veriler, ERP, CRM veya di\u011fer ticari i\u015flem uygulamalar\u0131 gibi \u00e7e\u015fitli operasyonel sistemlerden gelir. Bu veriler daha sonra i\u015flenir, d\u00f6n\u00fc\u015ft\u00fcr\u00fcl\u00fcr ve i\u015f zekas\u0131 amac\u0131yla analiz edilip kullan\u0131labilece\u011fi veri ambar\u0131na y\u00fcklenir.<\/p>\n

Veri ambar\u0131, veri temizleme, veri entegrasyonu ve veri birle\u015ftirme s\u00fcre\u00e7lerini i\u00e7erir. Bu i\u015flemler ham veriyi analitik sorgulama ve raporlama i\u00e7in kullan\u0131labilecek formata d\u00f6n\u00fc\u015ft\u00fcrmek i\u00e7in kullan\u0131l\u0131r. Depo ayn\u0131 zamanda ge\u00e7mi\u015f verileri de saklar, b\u00f6ylece i\u015fletmeler farkl\u0131 zaman dilimlerini ve e\u011filimleri analiz ederek gelece\u011fe y\u00f6nelik tahminlerde bulunabilir.<\/p>\n

Veri Ambar\u0131n\u0131n \u0130\u00e7 Yap\u0131s\u0131 ve \u0130\u015fleyi\u015fi<\/h2>\n

Bir veri ambar\u0131n\u0131n yap\u0131s\u0131 birka\u00e7 temel bile\u015fenden olu\u015fur:<\/p>\n

    \n
  1. \n

    Kaynak Sistemleri<\/strong>: Veri ambar\u0131nda kullan\u0131lmak \u00fczere verilerin \u00e7\u0131kar\u0131ld\u0131\u011f\u0131 veritabanlar\u0131d\u0131r.<\/p>\n<\/li>\n

  2. \n

    Veri Haz\u0131rlama Alan\u0131<\/strong>: \u00c7\u0131kar\u0131lan verilerin temizlenerek veri ambar\u0131na y\u00fcklenebilecek formata d\u00f6n\u00fc\u015ft\u00fcr\u00fcld\u00fc\u011f\u00fc yerdir.<\/p>\n<\/li>\n

  3. \n

    Veri depolama<\/strong>: Verilerin temizlendikten, d\u00f6n\u00fc\u015ft\u00fcr\u00fcld\u00fckten ve entegre edildikten sonra depoland\u0131\u011f\u0131 yerdir.<\/p>\n<\/li>\n

  4. \n

    Veri Pazar\u0131<\/strong>: Sat\u0131\u015f, finans veya pazarlama gibi belirli bir i\u015f alan\u0131yla ilgilenen veri ambar\u0131n\u0131n bir alt k\u00fcmesi.<\/p>\n<\/li>\n

  5. \n

    Son Kullan\u0131c\u0131 Ara\u00e7lar\u0131<\/strong>: Verileri sorgulamak ve raporlar olu\u015fturmak i\u00e7in kullan\u0131lan i\u015f zekas\u0131 ara\u00e7lar\u0131 gibi yaz\u0131l\u0131m uygulamalar\u0131.<\/p>\n<\/li>\n<\/ol>\n

    Bir veri ambar\u0131, farkl\u0131 kaynak sistemlerden veri \u00e7\u0131kararak, temizleyerek ve d\u00f6n\u00fc\u015ft\u00fcrerek ve ard\u0131ndan sorgulan\u0131p analiz edilebilecek \u015fekilde depoya y\u00fckleyerek \u00e7al\u0131\u015f\u0131r.<\/p>\n

    Veri Depolaman\u0131n Temel \u00d6zellikleri<\/h2>\n

    Veri ambar\u0131n\u0131n temel \u00f6zellikleri \u015funlar\u0131 i\u00e7erir:<\/p>\n

      \n
    1. \n

      Konu Odakl\u0131<\/strong>: M\u00fc\u015fteriler, \u00fcr\u00fcnler, sat\u0131\u015flar vb. gibi belirli konular etraf\u0131nda bir veri ambar\u0131 d\u00fczenlenir.<\/p>\n<\/li>\n

    2. \n

      Birle\u015fik<\/strong>: Veri ambar\u0131, farkl\u0131 kaynaklardan gelen verileri birle\u015fik bir yap\u0131da birle\u015ftirir.<\/p>\n<\/li>\n

    3. \n

      U\u00e7ucu Olmayan<\/strong>: Veriler veri ambar\u0131na al\u0131nd\u0131ktan sonra de\u011fi\u015ftirilemez.<\/p>\n<\/li>\n

    4. \n

      Zaman De\u011fi\u015fkeni<\/strong>: Bir veri ambar\u0131 ge\u00e7mi\u015f verileri saklayarak kullan\u0131c\u0131lar\u0131n farkl\u0131 zaman dilimlerini analiz etmesine olanak tan\u0131r.<\/p>\n<\/li>\n<\/ol>\n

      Veri Ambar\u0131 T\u00fcrleri<\/h2>\n

      Temel olarak \u00fc\u00e7 t\u00fcr veri ambar\u0131 vard\u0131r:<\/p>\n

        \n
      1. \n

        Kurumsal Veri Ambarlar\u0131 (EDW)<\/strong>: Bunlar, t\u00fcm kurulu\u015fun verileri i\u00e7in merkezi bir depo sa\u011flar.<\/p>\n<\/li>\n

      2. \n

        Operasyonel Veri Depolar\u0131 (ODS)<\/strong>: Bunlar analiz edilecek operasyonel veriler i\u00e7in bir havuz sa\u011flar.<\/p>\n<\/li>\n

      3. \n

        Veri Pazarlar\u0131<\/strong>: Bunlar genellikle i\u015fin belirli bir alan\u0131yla ilgilenen daha k\u00fc\u00e7\u00fck, daha odakl\u0131 veri ambarlar\u0131d\u0131r.<\/p>\n<\/li>\n<\/ol>\n\n\n\n\n\n\n\n
        Tip<\/th>\n\u00d6zellikler<\/th>\n<\/tr>\n<\/thead>\n
        Kurumsal Veri Ambarlar\u0131<\/td>\nMerkezile\u015ftirilmi\u015ftir, b\u00fcy\u00fck kurulu\u015flar taraf\u0131ndan kullan\u0131lan her t\u00fcrl\u00fc veriyi y\u00f6netir<\/td>\n<\/tr>\n
        Operasyonel Veri Depolar\u0131<\/td>\nRutin faaliyetler i\u00e7in kullan\u0131lan ger\u00e7ek zamanl\u0131 operasyonel veriler<\/td>\n<\/tr>\n
        Veri Pazarlar\u0131<\/td>\nBelirli i\u015f alanlar\u0131na odakl\u0131, daha h\u0131zl\u0131, daha ucuz<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Veri Ambarlamada Uygulamalar, Sorunlar ve \u00c7\u00f6z\u00fcmler<\/h2>\n

        Veri ambarlar\u0131 bankac\u0131l\u0131k, perakende, e-ticaret, sa\u011fl\u0131k vb. \u00e7e\u015fitli sekt\u00f6rlerde raporlama, trend tespiti ve i\u015f karar deste\u011fi amac\u0131yla kullan\u0131lmaktad\u0131r.<\/p>\n

        Ancak veri ambarlaman\u0131n kendine has zorluklar\u0131 vard\u0131r:<\/p>\n

          \n
        1. \n

          Veri Entegrasyonu<\/strong>: Farkl\u0131 kaynaklardan gelen verileri entegre etme s\u00fcreci karma\u015f\u0131k ve zaman al\u0131c\u0131 olabilir.<\/p>\n<\/li>\n

        2. \n

          Veri kalitesi<\/strong>: Veri kalitesinin d\u00fc\u015f\u00fck olmas\u0131 hatal\u0131 raporlama ve analizlere yol a\u00e7abilir.<\/p>\n<\/li>\n

        3. \n

          \u00d6l\u00e7eklenebilirlik ve Performans<\/strong>: Veri hacimleri artt\u0131k\u00e7a performans\u0131 korumak zor olabilir.<\/p>\n<\/li>\n<\/ol>\n

          \u00c7\u00f6z\u00fcmler aras\u0131nda veri entegrasyon ara\u00e7lar\u0131n\u0131n, veri temizleme ara\u00e7lar\u0131n\u0131n kullan\u0131m\u0131 ve y\u00fcksek performansl\u0131 donan\u0131ma yat\u0131r\u0131m yap\u0131lmas\u0131 yer al\u0131r.<\/p>\n

          Veri Ambar\u0131 \u00d6zellikleri ve Benzer Terimlerle Kar\u015f\u0131la\u015ft\u0131rma<\/h2>\n\n\n\n\n\n\n\n
          Terim<\/th>\nTan\u0131m<\/th>\nTemel \u00f6zellikler<\/th>\n<\/tr>\n<\/thead>\n
          Veri deposu<\/td>\nRaporlama ve veri analizi i\u00e7in kullan\u0131lan sistem<\/td>\nEntegre, kal\u0131c\u0131, zamanla de\u011fi\u015fen, konu odakl\u0131<\/td>\n<\/tr>\n
          Veri taban\u0131<\/td>\nD\u00fczenli bir veri koleksiyonu<\/td>\nG\u00fcnl\u00fck i\u015flemlerde kullan\u0131lan CRUD i\u015flemlerini destekler<\/td>\n<\/tr>\n
          Veri G\u00f6l\u00fc<\/td>\nHam, i\u015flenmemi\u015f verileri depolayan bir sistem veya depo<\/td>\n\u015eemas\u0131z, ham verileri depolar, b\u00fcy\u00fck veri analiti\u011fine uygundur<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

          Veri Ambarlamada Gelecek Perspektifleri ve Teknolojiler<\/h2>\n

          Veri ambar\u0131n\u0131n gelece\u011fi, teknolojinin ve i\u015f ihtiya\u00e7lar\u0131n\u0131n geli\u015fiminden etkilenmektedir. Bu, ger\u00e7ek zamanl\u0131 veri ambar\u0131n\u0131n b\u00fcy\u00fcmesini, veri y\u00f6netimi i\u00e7in yapay zeka ve makine \u00f6\u011freniminin artan kullan\u0131m\u0131n\u0131 ve \u00f6l\u00e7eklenebilirlik, azalt\u0131lm\u0131\u015f maliyet ve iyile\u015ftirilmi\u015f performans sunan bulut tabanl\u0131 veri ambarlar\u0131na ge\u00e7i\u015fi i\u00e7erir.<\/p>\n

          Proxy Sunucular\u0131 ve Veri Depolaman\u0131n Kesi\u015fimi<\/h2>\n

          Proxy sunucular\u0131, di\u011fer sunuculardan kaynak arayan istemcilerden gelen isteklere arac\u0131l\u0131k ederek veri ambar\u0131nda rol oynayabilir. \u0130stemcinin IP adresini maskeleyerek g\u00fcvenli\u011fi art\u0131rabilirler ve veri ambarlar\u0131na giden y\u00fcksek trafi\u011fi y\u00f6netmek i\u00e7in y\u00fcklerin dengelenmesine yard\u0131mc\u0131 olabilirler. Ayr\u0131ca proxy sunucular, bir veri ambar\u0131 i\u00e7in \u00e7e\u015fitli kaynaklardan veri toplamak amac\u0131yla veri kaz\u0131ma faaliyetlerinde faydal\u0131 olabilir.<\/p>\n

          \u0130lgili Ba\u011flant\u0131lar<\/h2>\n
            \n
          1. Veri Ambar\u0131 Konseptleri \u2013 Oracle<\/a><\/li>\n
          2. Veri Ambar\u0131 Nedir ve Nas\u0131l Test Edebilirim? \u2013 Bili\u015fim<\/a><\/li>\n
          3. Bill Inmon, Ralph Kimball'a Kar\u015f\u0131 \u2013 Farkl\u0131<\/a><\/li>\n
          4. Veri Ambar\u0131 K\u0131lavuzu \u2013 Microsoft Azure<\/a><\/li>\n
          5. Veri Ambar\u0131 \u2013 IBM<\/a><\/li>\n
          6. Veri Ambar\u0131 ve Veritaban\u0131n\u0131n Kar\u015f\u0131la\u015ft\u0131rmal\u0131 Bir \u00c7al\u0131\u015fmas\u0131 \u2013 Uluslararas\u0131 M\u00fchendislik ve \u0130leri Teknoloji Dergisi<\/a><\/li>\n<\/ol>","protected":false},"featured_media":468158,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-476729","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Data Warehouse: A Detailed Overview<\/mark>","faq_items":[{"question":"What is a data warehouse?","answer":"

            A data warehouse is a system used for reporting and data analysis, often consolidating data from various sources to support decision-making within an organization. It plays a crucial role in business intelligence.<\/p>"},{"question":"Who first proposed the concept of a data warehouse?","answer":"

            The concept of a data warehouse was first proposed by Bill Inmon in the 1970s. He defined a data warehouse as a subject-oriented, integrated, time-variant, and non-volatile collection of data that supports management's decision-making process.<\/p>"},{"question":"What are the main components of a data warehouse?","answer":"

            The main components of a data warehouse are source systems, data staging area, data storage, data marts, and end-user tools.<\/p>"},{"question":"What are the key features of a data warehouse?","answer":"

            The key features of a data warehouse include being subject-oriented, integrated, non-volatile, and time-variant.<\/p>"},{"question":"What are the types of data warehouses?","answer":"

            The primary types of data warehouses are Enterprise Data Warehouses (EDW), Operational Data Stores (ODS), and Data Marts.<\/p>"},{"question":"What are some applications of data warehousing?","answer":"

            Data warehouses are used in various industries like banking, retail, e-commerce, healthcare, etc., for reporting, trend detection, and business decision support.<\/p>"},{"question":"What challenges are associated with data warehousing and how can they be resolved?","answer":"

            Some challenges associated with data warehousing include data integration, data quality, and scalability and performance. Solutions include the use of data integration tools, data cleaning tools, and investing in high-performance hardware.<\/p>"},{"question":"How do data warehouses compare with databases and data lakes?","answer":"

            While all three are used for storing data, data warehouses are used for reporting and data analysis, databases support CRUD operations for day-to-day operations, and data lakes store raw, unprocessed data ideal for big data analytics.<\/p>"},{"question":"What are some future trends in data warehousing?","answer":"

            The future of data warehousing includes the growth of real-time data warehousing, increased use of AI and machine learning for data management, and the shift towards cloud-based data warehouses.<\/p>"},{"question":"How can proxy servers be associated with data warehousing?","answer":"

            Proxy servers can enhance security and manage high traffic to data warehouses by acting as intermediaries for requests from clients. They can also be useful in data scraping activities to gather data from various sources for a data warehouse.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476729","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\/476729\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media\/468158"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media?parent=476729"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}