건설 데이터 웨어하우스.건설사업관리.데이터 모델링.데이터 마이닝.데이터 마트.Construction Data Warehouse.Construction Project Management.Data Modeling.Data Mining.Data Mart.
초록▼
o 건설산업 관리업무 정형화 - 관리업무 정형화 모델 구축 완료 - CPI 모델 (9개 분야 건설관리 모델링)제시 o 건설 데이터 유형 요구사항 도출 - 건설회사의 실적관련 최종의사결정 데이터 확보와 주요요구사항 분석 - 148개 활용유형 Modeling달성 o Legacy 분석 및 연계기술 개발 - 성공적인 ET&T를 위한 관리부문별 프로토콜 제시 - 건설관리 의사결정 수준, 요소기술 수준, 데이터 상세 수준을 성공적인 ET&T를 위한 관리부문별 프로토콜 제시 o 건설
o 건설산업 관리업무 정형화 - 관리업무 정형화 모델 구축 완료 - CPI 모델 (9개 분야 건설관리 모델링)제시 o 건설 데이터 유형 요구사항 도출 - 건설회사의 실적관련 최종의사결정 데이터 확보와 주요요구사항 분석 - 148개 활용유형 Modeling달성 o Legacy 분석 및 연계기술 개발 - 성공적인 ET&T를 위한 관리부문별 프로토콜 제시 - 건설관리 의사결정 수준, 요소기술 수준, 데이터 상세 수준을 성공적인 ET&T를 위한 관리부문별 프로토콜 제시 o 건설 데이터 웨어하우스 아키텍처 및 프로토타입 개발 - 공정관리, 원가관리, 품질관리, 안전관리 및 성과관리 등 5개 개별 관리부문별 데이터 모델링 완료 -프로젝트 성과를 중심으로 한 전체 총괄 Data Architecture 구축 - 5개 관리부문별 데이터마트 기반의 건설 DW Prototype 구축 o 관리 부문별 OLAP 시스템 개발 - 건설사 실적데이터를 활용한 OLAP 시험모델 제시 - 성과관리, 원가관리, 품질관리, 안전관리, 공정관리 부분 OLAP 시스템 개발
Abstract▼
This report describes the development of a Construction Data Warehouse technology, which has been experimented on at the Construction Engineering and Management Laboratory at Seoul National University, This research was conducted under the National Research Laboratory(NRL) program of the Ministry of
This report describes the development of a Construction Data Warehouse technology, which has been experimented on at the Construction Engineering and Management Laboratory at Seoul National University, This research was conducted under the National Research Laboratory(NRL) program of the Ministry of Science & Technology. The aim of this research is to further develop the construction DW technology, which is capable of integrating numerous data from many work units and independent user applications and offering various functions, such as data cleaning, data storing and data analysis that support various decision-making processes in construction and production processes. These functions can improve add-value and productivity of construction industry in the knowledge-based 21st century, and consequently, it can contribute to building up competitive power in the construction industry. We developed a construction DW system architecture, classified construction data and standardized such data according to various field conditions, and lastly, defined a requisite for data for decision-making of construction works. Moreover, we built the construction data mart technology and developed the data mining technology to be applied in decision-making processes of construction works. Using these subsets, we were able to exploit the integration system of construction DW essential technology and cultivate the technology to be used in build-up construction DW operation environment. In the first stage, a CPI model (which consists of 9 categories) is proposed to standardize construction management works and DW application features for each participant in the construction industry are extracted by analyzing the traits of these 9 categories of management. Construction data are classified and needs for each data are extracted by analyzing 100,000 achievement data for decision-making. The data management systems that are used in the construction industry today are analyzed by examining the systems of 4 major domestic construction companies. Consequently, a test set is set up as an infrastructure of a construction DW. In the second stage of research, based on the first-step construction DW architecture, a construction DW architecture and 4 essential technology modules are developed. A technology of data generating and extracting is developed from 12 models (which consist of 7 essential dimensions and 5 supplement dimensions). The construction legacy system is then analyzed, the technology for data modeling is developed and application strategies for 5 construction participants are proposed by looking into some cases and data of 4 major domestic construction companies. To test the fitness of a data mining process in the construction industry, we conducted 5 case studies where a total of 1,200 time-series record were used. Likewise, to develop an OLAP application technology, an OLAP test model is proposed using 1,200 records. A Construction DW is a system that can store related data with extraction/transformation/clearing/integration techniques, and if it is needed, processes stored data to information for decision-makers. Therefore, the decision-making process using the construction DW can be used as a prototype in knowledge management in the construction industry. The transfer of this sample construction BW model to a construction industry and supporting development of the technology related on the construction DW shall contribute to the improvement of the productivity of the construction industry and ultimately contribute to reinforcing competitive power in the world-wide construction market.
목차 Contents
제 1 장 연구개발과제의 개요...12
제 1 절 연구개발의 배경...12
제 2 절 연구개발의 필요성...12
1. 건설 데이터의 정형기술(Data Modeling)...13
2. 건설 데이터의 요약기술(OLAP, Multi-Dimensional Analysis)...14
※ AI-Helper는 부적절한 답변을 할 수 있습니다.