Transcript CHAPTER 1

7장
구조의 구성요소
THE ARCHITECTURAL
COMPONENTS
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장의 목표
• 데이터 웨어하우스 구조를 이해
• 구조의 구성요소에 관해 배운다
• 데이터 웨어하우스 구조의 뚜렷한 특성을
검토
• 구조의 프레임워크가 어떻게 데이터 흐름
을 지원하는가를 조사
• 기술적인 구조가 무엇을 의미하는지 파악
• 구조의 구성요소의 기능과 서비스를 공부
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7.1 데이터 웨어하우스 구조의 이해
• Major architectural components
– Source data, data staging, data storage,
information delivery, metadata, management
and control
• The architectural components enable the
flow of data from sources to the end-users
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구조: Definitions
• The structure that brings all the
components of a data warehouse together
• Provide the overall framework for
developing and deploying the data
warehouse
– Comprehensive blueprint
• Define the standards, measurements,
general design, and support techniques
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Architecture in Three Major Areas
• Three major areas
– 데이터 획득
– 데이터 저장장치
– 정보 전달
• Figure 7-1
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7.1 뚜렷한 특성
DISTINGISHING CHARACTERISTICS
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다른 목적과 범위
데이터 내용
복잡한 분석과 빠른 응답
유연하고 동적인
메타데이터-주도
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Different Objectives and Scope
• The number and extent of the data source
• The data transformation and integration
functions
• Data granularity and data volumes
• The impact of the data warehouse in the
existing operational systems
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Data Content
• Keep data integrated from multiple sources
• The integrated data into the data warehouse
repository as read-only data
• The storing of data grouped by business
subjects
• Historical data stored in the data warehouse
– Very high data volumes
– Keep data going back 10 years in the data
warehouse
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Complex Analysis and Quick
Responses
• Support complex analysis of the strategic
information by the users
• Variations for providing analysis
– Drill down, roll up, slice and dice data, and
play with “what-if” scenarios
• Graphical charts
• The tools and information for a quick
response to the problem
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Flexible and Dynamic
• Flexible enough to accommodate
additional requirements as and when they
surface
• Changing business conditions
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Metadata-driven
• The metadata component holds data
about every phase of the movement
• The metadata component interleaves with
and connects the other components
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7.3 구조의 프레임워크
• Architecture Supporting Flow of Data
– Enable the flow of data from beginning to end
– Figure 7-2: The management and control
module govern the flow of data
– At the Data Source: source data and data
staging
– In the Data Warehouse Repository: data
storage and metadata
– At the User End: information delivery
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관리 및 제어 모듈
• Two major functions
– To constantly monitor all the ongoing
operations
– To step in and recover from problems when
things go wrong
• Figure 7-3
• Also govern data security and provide
authorized access to the data warehouse
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7.4 기술적인 구조
• The technical architecture of a data warehouse
– The complete set of functions and services provided
within its components
– Include the procedures and rules that are required to
perform the functions and provide the services
– Encompass the data stores needed for each
component to provide the services
• Tools are the means to implement the
architecture
– Architectures comes first and the tools follow
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데이터 획득
Data Acquisition
• Figure 7-4
• Data Flow
– Flow : data sources  staging area
– Data Sources
• Fourth generation language of legacy systems
• SQL-based language of relational DBMSs
– Intermediary Data Stores
– Staging Area
• Sequential or flat files
• Data warehouse RDBMS
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Functions and Services
(of Data Acquisition)
• Data Extraction
– Select data sources and determine the types of filters to be
applied to individual sources
– Generate automatic extract files from operational systems using
replication and other techniques
• Data Transformation
– Map input data to data for data warehouse repository
– Clean, deduplicate, and merge/purge
• Data Staging
– Provide backup and recovery for staging area repositories
– Sort and merge files
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데이터 저장장치
Data Storage
• Figure 7-5
• Data Flow
– Flow : staging area  data warehouse
repository
– Data Groups
• Data for the initial loading of the data warehouse
• Data for ongoing incremental loads
– The Data Repository: relational databases
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기능과 서비스 목록
(of Data Storage)
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DW 테이블의 완전 재생을 위한 데이터 적재
정기적인 증진적인 적재
상세하고 요약된 수준들에서 적재
적재 과정을 최적화
자동화된 작업 제어 서비스들을 제공
DW DB에 대한 백업과 복구를 제공
보안을 제공
데이터베이스를 감시하고 미세-조정
데이터를 주기적으로 아카이브
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정보 전달
Information Delivery
• For your users, the information delivery
component is the data warehouse
• The information delivery component makes it
easy for the users to access the information
– Online query and interactive analysis sessions
– Regular and ad hoc reports
– OLAP
• Figure 7-6
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Data Flow
(of Information Delivery)
• Flow
– Begins at
• The enterprise-wide data warehouse
• The set of conformed data marts
– Flows to
• The user desktops
• EIS or multidimensional databases for OLAP
• Service Locations
– Query services from user desktop, application server,
or database itself
• Data Stores : intermediary data stores
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Functions and Services
(of Information Delivery)
• 정보 접근을 제어하기위해 보안 제공
• 서비스를 개선하고 미래의 증진을 위해 사용자 접근 감
시
• 사용자들에게 데이터 웨어하우스 내용을 가져오는 것을
허용
• 사용자들로부터 데이터 저장장치의 내부 복잡도를 숨김
으로 접근을 단순화
• 최적의 실행을 위해 자동적으로 질의들을 재 포맷
• 질의들에게 더 빠른 결과들을 위한 집계 테이블들을 알
게 하라
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기능과 서비스(계속)
• 질의들을 관리하고 끝없이 수행되는 질의들을 제어
• 사용자들을 위한 셀프서비스의 보고서 생성을 제공
• 앞으로의 사용을 위해 질의들의 결과 집합들과 보고서들을
저장
• 데이터 구체화정도에 대한 다수의 수준들을 제공
• 데이터 적재를 감시하기위해 사건 트리거를 제공
• 사용자들이 OLAP을 통하여 복잡한 분석을 수행
• EIS와 데이터 마이닝과 같은 다운스트림이고 전문화된 의
사결정 지원 시스템들에게 데이터 공급
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