Microsoft PowerPoint - 2_증권_BI세미나_ _이지은_Final.ppt
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1 IBM Infosphere Warehousing Jieun Lee September IBM Corporation
2 Agenda 1. 전사정보관리전략 - Information On Demand Information On Demand ( IOD) 개념및필요성 2. IOD for Business Intelligence : Dynamic Warehousing 차세대 EDW 비전 Infosphere 3. 차세대 EDW 를위한인프라 IBM Infosphere Warehouse Dynamic warehousing 을위한 IBM 기술요소 IBM Infosphere Balanced Warehouse 2
3 Information on Demand 란? Information on Demand 적용을통한경쟁력있는비즈니스환경구축 < IDC 백서 > 비즈니스기회및경쟁상황에성공적으로대응하기위하여적절한정보 (Right Information) 를적절한사용자나프로세스 (Right People or Process) 에게적시에 (Right Time) 제공하여모든종류의정보소스를통 합, 분석하고최적화하여비즈니스에필요한가치를창출하고위험을최소화하는솔루션제공을목적으로함 IBM Corporation
4 정보의이슈 -Information Challenges Top Business Challenges 직원생산성증대 비즈니스프로세스최적화 고객요구사항만족 위험관리및각종규제에대한대응 60%+ of CEOs: Need to do a better job leveraging information Key Impact Area Information Availability Information Must Become a Strategic Asset 5X More Value creation by organizations effective at using Information as an Asset Top Technical Challenges 데이터일관성이슈 신뢰할수있는정보의부재 정보통합비용 정보인프라의유연성부족으로인한대응력저하 70% of people s time can be spent searching for relevant information Sources: IBM Attributes & Capabilities Study, 2005; Client Interviews 2004; IBM CFO Study, IBM Corporation
5 Why NOW? Key Challenge is Unlocking the Value of Information NOW! 실시간 / 데이터양적증가 / 다양한포맷 / 사용자확대 IBM Corporation
6 Information On Demand 정보의비즈니스가치증대를통한경쟁력강화 수익성증대 맞춤서비스 효과적인마케팅 고객세분화를통한최적의의사결정 Business Optimization 멀티채널마케팅 6 Better Business Outcomes 비즈니스성과에대한계획, 이해및최적화 비즈니스성과에대한계획, 이해및최적화 End-to-End Capabilities 정확하고신뢰할수있는정보제공및유지관리 Flexible Architecture for Leveraging Existing Investments 정확하고신뢰할수있는정보의제공및유지관리 6 정보수명주기전반에걸친정보관리 비즈니스프로세스내에서의정보활용 Other Information Sources 정보관리및비즈니스프로세스에서의활용
7 Agenda 1. 전사정보관리전략 - Information On Demand Information On Demand ( IOD) 개념및필요성 2. IOD for Business Intelligence : Dynamic Warehousing Dynamic Warehousing & InfoSphere 3. 차세대 EDW 를위한인프라 IBM InfoSphere Warehouse Dynamic warehousing 을위한 IBM 기술요소 IBM InfoSphere Balanced Warehouse 7
8 Dynamic Warehousing - 차세대비즈니스인텔리전스 Information On Demand to Optimize Real-Time Processes and each transactions Dynamic Warehousing OLAP & Data Mining to Understand Why and Recommend Future Action Traditional Data Warehousing Query & Reporting to Understand What Happened 8
9 Dynamic Warehousing 기술요소 Dynamic Warehousing 은사용자관점에서필요한정보를필요한시점에동적으로활용할수있도록하는기존 DW 의확장개념입니다. 정형및비정형데이터로부터필요한정보를통합 / 변환 / 분석하여전통적인분석업무뿐아니라이를운영비즈니스프로세스에서실시간으로사용할수있도록합니다. 검색및비정형텍스트분석기술 비정형데이터로부터의미있는정보를추출하여활용 모든관련정보에적용되는공통메타데이터제공 Search & Text Analytics Information Integration Process Management 전사에걸쳐다양한데이터소스로부터정보를통합, 클린징, 변환하는기술 정보의서비스화 수행되는각종비즈니스활동내에비즈니스통찰력을제공하여의사결정및프로세스최적화에분석의결과가활용될수있도록함. 고객, 거래선, 제품등에대한단일뷰 ( 마스터 ) 제공 비즈니스코어엔티티에대한단일소스로정확하고일관성있는정보가 DW에제공될수있도록함. Enterprise Data Modeling Master Data Management Industry Perspective 산업에특화된데이터모델을통하여효과적으로특정비즈니스도메인에분석력을적용할수있도록함. 각산업을위한분석템플릿활용 9
10 Dynamic Warehousing 활용 IBM Data Warehousing은콜센터, 영업사원등각트랜잭션을최적화할수있는적절한정보를제공할수있도록합니다. DW의가치는과거데이터에대한분석뿐아니라, 사용자의일상업무프로세스의일부분으로실시간분석을활용하는것으로극대화됩니다. Information On Demand Dynamic Warehousing 콜센터등고객서비스센터에서교차판매기회, 이탈가능성및이와관련된이슈를고객을응대하면서바로파악고객서비스의변화 고객접점에서교차판매기회파악및고객과의협상순간에활용할수있는관련고객정보를이해영업효과극대화를위한변화 OLAP & Data Mining Query & Reporting 이탈고객분석, 우수고객스코어링분기별, 지역별매출액분석월별영업실적리포트등쿼리와리포팅 OLAP 데이터마이닝 10
11 The IBM InfoSphere Vision An Industry Unique Information Platform for client value 신뢰할 수 있는 고 품질 정보에 대한 제공 과정의 단순화 주요 정보 관련 프로젝트의 리스크 최소화 각 구성요소의 통합을 통한 상승 효과 단일 업무에서 부터 전사프로젝트까지의 확장성 11
12 IBM InfoSphere Dynamic warehousing & InfoSphere 소스데이터 IOD Framework ODS IBM InfoSphere Information Server IBM InfoSphere Warehouse IBM InfoSphere MDM Server IBM Cognos BI MART REGIONAL How It All Fits Together UNSTRUCTURED STRUCTURED XML DEMOGRAPHIC TRANSACTION Banking Healthcare Data Models Retail Telco Public Insurance Hardware C-ClassClass D-Class E-Class Linux/ Windows AIX/SUN/HP 12
13 IBM InfoSphere Information Server 1) Gather, Transform, Cleanse, And Deliver Trusted Information 소스데이터 IOD Framework IBM InfoSphere Information Server ODS Understand MART REGIONAL Transform Cleanse UNSTRUCTURED STRUCTURED Deliver XML DEMOGRAPHIC Unified Meta Data Management TRANSACTION Banking Healthcare Data Models Retail Telco Public Insurance Hardware C-ClassClass D-Class E-Class Linux/ Windows AIX/SUN/HP 13
14 IBM InfoSphere Warehouse 2) Discover Insight, Uncover Trends, Align Trusted Information Disparate Data IOD Framework IBM InfoSphere Information Server IBM InfoSphere Warehouse ODS Understand Discover MART REGIONAL Transform Design Cleanse Grow UNSTRUCTURED STRUCTURED Deliver Optimize XML DEMOGRAPHIC Unified Meta Data Management Reliable Real Time Delivery TRANSACTION Banking Healthcare Data Models Retail Telco Public Insurance Hardware C-ClassClass D-Class E-Class Linux/ Windows AIX/SUN/HP 14
15 IBM InfoSphere MDM Server 3) Operationalize & Synchronize Master Data Cross Channel Disparate Data IOD Framework IBM InfoSphere Information Server IBM InfoSphere Warehouse IBM InfoSphere MDM Server ODS Understand Discover Define MART REGIONAL Transform Design Manage Cleanse Grow Transact UNSTRUCTURED STRUCTURED Deliver Optimize XML DEMOGRAPHIC Unified Meta Data Management Reliable Real Time Delivery Part, Product, Account TRANSACTION Banking Healthcare Data Models Retail Telco Public Insurance Hardware C-ClassClass D-Class E-Class Linux/ Windows AIX/SUN/HP 15
16 IBM Cognos Business Intelligence 4) Analyze Trusted Information To Determine Where You Are Disparate Data IOD Framework IBM InfoSphere Information Server IBM InfoSphere Warehouse IBM InfoSphere MDM Server IBM Cognos 8 BI ODS Understand Discover Define Report MART REGIONAL Transform Design Manage Analyze Cleanse Grow Transact Scorecard UNSTRUCTURED STRUCTURED Deliver Optimize Plan XML DEMOGRAPHIC Unified Meta Data Management Reliable Real Time Delivery Part, Product, Account Unified Performance System Platform TRANSACTION Banking Healthcare Data Models Retail Telco Public Insurance Hardware C-ClassClass D-Class E-Class Linux/ Windows AIX/SUN/HP 16
17 Agenda 1. 전사정보관리전략 - Information On Demand Information On Demand ( IOD) 개념및필요성 2. IOD for Business Intelligence : Dynamic Warehousing Dynamic Warehousing & InfoSphere 3. 차세대 EDW 를위한인프라 IBM InfoSphere Warehouse Dynamic warehousing 을위한 IBM 기술요소 IBM InfoSphere Balanced Warehouse 17
18 IBM InfoSphere Warehouse Universal Access Portals & Web Apps Reporting Solutions MS Office Web Services SQL/MDX MDX Analytics Acceleration No Copy Analytics Advanced Design & Management Extreme Performance Advanced Capability Text Analytics Data Mining Design Studio Embedded Data Movement Workload Management Data Compression On-line Analytical Processing (OLAP) Remote Data Access Data Retention MPP Data Server DB2 ESE Platform C-Class D-Class E-Class Linux/ Windows AIX/SUN/HP 18
19 IBM InfoSphere Warehouse Analytics Office Universal Access 3 rd Party Data Mining InfoSphere Warehouse Cubing Text Unstructured Text Annotation 데이터추출요건최소화 데이터는 DW 내에존재 분석을위한정보에대한제한없는액세스 새로운데이터에대한분석주기최소화 19 19
20 IBM InfoSphere Warehouse Design & Admin A Complete End to End Solution For Warehouse Application Life Cycle Management Application Developer Develop Coding Debugging Teaming Testing Integrating Database Developer Develop Other Deploy Database Administrator Manage Packaging/versioning Application Merging Change Management Design Data Modeling OLAP ELT Modeling Data Mining Design Eclipse Shared Web Manage Govern Compliance Standard enforcement Auditing logging IBM Business Analyst BI Architect Govern Application Administrator 20 20
21 IBM InfoSphere Warehouse Performance 안정성 / 가용성 / 실시간성능 / 리소스효율극대화를목표로합니다. IBM Dynamic Warehousing 은대용량데이터를병렬로수행하고 복잡한워크로드에대한시스템영향을최소화하기위하여워크로드를관리합니다. 고성능압축기능을통하여스토리지절감및성능이향상됩니다. Complex Strategic Queries Short Tactical Queries Streaming Updates and Batch ETL Complex Queries Comparison ( Lower is bet t er) V9 Baseline V9 Compression Table 21
22 IBM InfoSphere Warehouse Better for Both 수시적재와사용자조회업무를동시에지원하여야하는 Mixed Workload 요건과 OLTP 내에분석기능을 Embed 하는요건의증가로인하여 DW 전용 DBMS 가아닌 OLTP 와 DW 업무성격을동시에지원할수있는 DBMS 가경쟁력을가진다. - Gartner Data Warehouse Forecast, 2006 Embeddable Analytics (Inline & As a Service) 다차원분석 / 데이터마이닝 / 시각화 Beyond Traditional Structured Data 비정형정보를활용한비즈니스통찰력제공 Dynamic Warehouse Data Volumes Unstructured Structured Best of Both Worlds OLTP Foundation 실시간액세스, 안정성, 가용성, 확장성, 보안등에대하여최적화된엔진 Deep Compression 스토리지비용감소디스크활용성증대쿼리응답시간향상 Dedicated Warehousing 병렬아키텍쳐 -Shared Nothing 데이터파티셔닝워크로드관리 22
23 IBM InfoSphere Warehouse Data Retention 데이터사용요건에따른별도스토리지관리를통하여이력데이터관리비용절감및데이터웨어하우스플랫폼성장속도감소 Cubing Services InfoSphere Warehouse High Priority Data Mid Priority Data Optim Data Retention Manager 23 Low Priority Data
24 IBM InfoSphere Balanced Warehouse Better than an appliance BCU( Balanced Configuration Unit) 을기본단위로하는 IBM InfoSphere Balanced Warehouse 는 Dynamic warehousing 을위하여하드웨어, 스토리지, 소프트웨어에대한통합구성에대한사전테스트및구성을완료한검증된인프라입니다. Balanced Warehouse Simplicity 사전구성을통한복잡도감소 MEM CPU CPU MEM CPU CPU.. MEM CPU CPU Data BCU 1 Data BCU 2 Data BCU n Flexibility for Growth BCU 단위의확장 Optimized Performance 최고의성능을위하여테스트를통한최적의사전구성완료 IBM선진사례의경험을바탕으로 risk 최소화 24
25 통합된데이터웨어하우스플랫폼 대용량데이터처리를위한 DB2 병렬파티셔닝, 데이터마이닝, 데이터유지관리및큐빙기술 분석환경뿐아니라운영트랜잭션환경에도최적화된성능보장 Storage Optimization Increase warehouse capacity Manage IBM InfoSphere Warehouse Reliable Real-Time Delivery Performance Management Identifies usage patterns and trends Analyze 확장성및유연성제공 - big or small Workload Management Optimizes workloads and priorities Data Retention based on usage patterns and data governance 25
26 감사합니다. 26
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