Bir Kurumsal Zekâ Teknolojisi Olarak Veri Madenciliği İle Muhasebe Bilgi Sistemi İlişkisi
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Dosyalar
Tarih
2014
Yazarlar
Dergi Başlığı
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Cilt Başlığı
Yayıncı
Selçuk Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Kurumsal kaynak yönetimi ürünlerinin gelişmesi ve yaygınlaşması sonucu, işletmelerin iş süreçlerinden temin ettikleri verilerin karar verme aşamasında anlamlı bilgilere dönüştürülmesinde birçok modelleme aracı tasarlanmıştır. Kurumsal sistemlerce toplanan veriler ile bu verilerin saklanması ve gerekli durumlarda kullanılması ile karar destek sistemlerine bilgi beslemesi yapan işletme hafızası oluşmuş ve bu hafıza “kurumsal zeka” veya “iş zekası” (Buseiness Intelligence) olarak adlandırılmıştır. Kurumsal zekâ; alınacak kararlara destek olmak üzere iş dinamikleri üzerinde kesin ve belirgin bir anlayış geliştirmek üzere kullanılan yöntem ve süreçler bütünüdür. Kurumsal zeka dağıtık veriler kullanılarak stratejik karar alma durumunda olan kişilere bilgi üretmektedir. İşletmenin kurumsal zekâ uygulamalarında, veri madenciliği tekniklerinin kullanıldığını ve kurumsal kaynak planlama verilerine uyarlanması şeklinde bilgi üretimi sağlandığı görülmektedir. Genel olarak, kurumsal zeka, veri madenciliği teknolojisini de kapsayan bir kavram olarak ele alınmaktadır. Günümüzde yaygınlaşan kurumsal kaynak planlamasında, kurumsal zeka uygulamaları kullanılırken sistemlerin tasarımına veri madenciliği teknikleri de entegre edilmektedir. Kurumların karar verme sürecinde etkin bir yöntem olarak karşımıza çıkan veri madenciliği, çok büyük veri tabanlarındaki ya da veri ambarlarındaki veriler arasında bulunan ilişkiler, örüntüler, değişiklikler, sapma ve eğilimler, belirli yapılar gibi ilginç bilgilerin ortaya çıkarılması ve keşfi işlemi olarak ifade edilmektedir. Veri madenciliği teknolojisi işletmelerin kurumsal verilerden, ilgilenilen bilgileri daha hızlı ve daha az uzmanlık bilgisiyle elde edebilmeleri amaçlamaktadır. Kurumlar tarafından toplanan verileri sıralayan ve sınıflandıran sistemlerden biri de Muhasebe Bilgi Sistemidir (Accounting Information System - AIS). Sistem, işletme faaliyetlerinin etkilerini planlamak, değerlendirmek ve teşhis etmek için kullanılabilen finansal bilgiyi ve organizasyonun finansal konumunun belirlenmesini sağlar. Bugün bu sistemlerin büyük miktarda veri topladığı düşünüldüğünde, büyük bir veri tabanından gizli prediktif bilgi çıkarımı sağlayan gelişmiş ve güçlü veri madenciliği teknolojisi yardımı ile veri akıllıca analiz edilebilmektedir. Veri madenciliği tekniğinin kullanımı muhasebe bilgi sisteminde de toplanan verilerin işletme faaliyetlerinde kullanılabilir bilgiye dönüştürülmesinde önemli bir faktör olmuştur. Veri madenciliği ile ulaşılan bilgiler, muhasebe bilgi sisteminin ürettiği ve raporladığı kalıplaşmış bilgilere göre farklılık göstermektedir. Bu çalışmada, bir kurumsal zeka teknolojisi olan veri madenciliği ile muhasebe bilgi sisteminin ilişkisi ve birbirleriyle hangi noktalarda kesiştikleri incelenmektedir. Çalışma veri madenciliğinin tanımı, uygulama alanları ve yöntemlerine ilişkin bilgiler ile muhasebe bilgi sisteminin genel yapısı, veri-bilgi akışı ve raporlamasına yer vermektedir.
As a result of the development and becoming widespread of enterprise resource management products, many modeling tools have been designed in the transformation process of data obtained by enterprises conversion at decision-making process. Storing data collected by enterprise systems and to use these datas if necessary for supply information to decision support systems, company memory formed and it is called "business intelligence". Business intelligence, is the set of methods and processes to support the decisions taken on the dynamics of the business in order to develop an exact and distinct understanding. Business intelligence is generate information to the people who are in the event of a strategic decision-making by using distributed datas. It seems that business intelligence applications of enterprise produce information in the form of using data mining techniques and adapting datas to the enterprise resource planning. In general, business intelligence, is considered as a concept covering data mining technologies. Today, business intelligence applications using data mining techniques are integrated into the design of systems at widespread enterprise resource planning. Data mining which appears as an effective method in the process of decisionmaking of institutions, is expressed as a discovery process and reveal a lot of data in large databases or data warehouses relationships, patterns, changes, deviations and trends, as well as interesting information to reveal specific structures Data mining technology aims to achieve interest information more quickly and less expert knowledge from enterprise data businesses. As the term of “data mining” before used by statisticians, then the data base researchers and information system managers and business communities. Data mining models implemented on information systems established in businesses makes reaching quality information and reporting easy. One of the systems lists and classify the data collected by the corporate is AIS-Accounting Information System. System provides financial information can be used to plan, evaluate and diagnoise of the effects of management activities and to determine organization's financial position. Today if considered these systems collect large amount of data, providing a huge database of extraction of hidden predictive information with the help of advanced and powerful data mining technology, data can be analyzed intelligently. The role of accounting information system has become increasingly important with the rapid change in technology at the creation of new knowledge and changing decisions that create alternatives. Accounting, information systems, provides input to the decision-making process thanks to offered features by data at enterprise resource management. The use of data mining technique has been a major factor conversion of data collected from accounting information system to the usable information in the business activities. Achived informations by data mining vary according to produced and reported stereotypes informations by accounting information system. The accounting information system, as well as bringing different perspectives to the development of data mining and has contributed to the adaptation to the enterprise. For this purpose, data mining models are used such as Classification and Regression, Clustering, Association Rules, Anomaly Detection Models with Decision Trees, Artificial Neural Networks, Genetic Algorithms, K-Nearest Neighbor, Memory Based Reasoning and Naive-Bayes. The accounting information system, as well as bringing different perspectives to the development of data mining and has contributed to the adaptation to the business. In this study, examines data mining which is a business intelligence technology and accounting information system relationship and d the intersection points with each other. Study covers the definition of data mining, applications, and informations concerning the methods, with overall structure of accounting information system, data-information flow and reporting.
As a result of the development and becoming widespread of enterprise resource management products, many modeling tools have been designed in the transformation process of data obtained by enterprises conversion at decision-making process. Storing data collected by enterprise systems and to use these datas if necessary for supply information to decision support systems, company memory formed and it is called "business intelligence". Business intelligence, is the set of methods and processes to support the decisions taken on the dynamics of the business in order to develop an exact and distinct understanding. Business intelligence is generate information to the people who are in the event of a strategic decision-making by using distributed datas. It seems that business intelligence applications of enterprise produce information in the form of using data mining techniques and adapting datas to the enterprise resource planning. In general, business intelligence, is considered as a concept covering data mining technologies. Today, business intelligence applications using data mining techniques are integrated into the design of systems at widespread enterprise resource planning. Data mining which appears as an effective method in the process of decisionmaking of institutions, is expressed as a discovery process and reveal a lot of data in large databases or data warehouses relationships, patterns, changes, deviations and trends, as well as interesting information to reveal specific structures Data mining technology aims to achieve interest information more quickly and less expert knowledge from enterprise data businesses. As the term of “data mining” before used by statisticians, then the data base researchers and information system managers and business communities. Data mining models implemented on information systems established in businesses makes reaching quality information and reporting easy. One of the systems lists and classify the data collected by the corporate is AIS-Accounting Information System. System provides financial information can be used to plan, evaluate and diagnoise of the effects of management activities and to determine organization's financial position. Today if considered these systems collect large amount of data, providing a huge database of extraction of hidden predictive information with the help of advanced and powerful data mining technology, data can be analyzed intelligently. The role of accounting information system has become increasingly important with the rapid change in technology at the creation of new knowledge and changing decisions that create alternatives. Accounting, information systems, provides input to the decision-making process thanks to offered features by data at enterprise resource management. The use of data mining technique has been a major factor conversion of data collected from accounting information system to the usable information in the business activities. Achived informations by data mining vary according to produced and reported stereotypes informations by accounting information system. The accounting information system, as well as bringing different perspectives to the development of data mining and has contributed to the adaptation to the enterprise. For this purpose, data mining models are used such as Classification and Regression, Clustering, Association Rules, Anomaly Detection Models with Decision Trees, Artificial Neural Networks, Genetic Algorithms, K-Nearest Neighbor, Memory Based Reasoning and Naive-Bayes. The accounting information system, as well as bringing different perspectives to the development of data mining and has contributed to the adaptation to the business. In this study, examines data mining which is a business intelligence technology and accounting information system relationship and d the intersection points with each other. Study covers the definition of data mining, applications, and informations concerning the methods, with overall structure of accounting information system, data-information flow and reporting.
Açıklama
Anahtar Kelimeler
Veri Madenciliği, Muhasebe Bilgi Sistemi, Veri, Bilgi, Raporlama, Data Mining, Accounting Information System, Data, Knowledge, Reporting
Kaynak
Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
31.1
Künye
Alagöz, A., Öge, S., Ortakarpuz, M., (2014). Bir Kurumsal Zekâ Teknolojisi Olarak Veri Madenciliği İle Muhasebe Bilgi Sistemi İlişkisi. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 31.1, 1-21.
