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2004년 4월 9일2
Agenda
CRM 개요분석CRM 접근법Sybase IWS 솔루션Sybase IQ 솔루션요약
2004년 4월 9일3
Business Challenges
신규고객확보
고객만족도및이탈방지
재구매율및수익율증가
영업및서비스생산성증가
사기및부정사용축소
비용인식제고
각종규제및보고대응
2004년 4월 9일4
CRM Initiative
기업가치를극대화하기위해서
기존고객및가망고객을대상으로
수요,욕구패턴,기회,위험,비용등을
과학적으로인식하고
효율적으로실천하기위한
‘고객중심’의 경영전략
CRM Type
Operational CRMOperational CRM Analytical CRMAnalytical CRM
CustomerProfile
Analysis
LoyaltyAnalysis
CampaignAnalysis
CustomerCare
Analysis
ProfitabilityAnalysis
SalesAnalysis
BusinessPerformance
Analysis
ERP SCM
LegacySystems
CustomerService
MarketingAutomation
SalesForce
Automation
2004년 4월 9일6
Analytical CRM
7P of Analytical CRM
1. Profiling (segmentation, risk, propensity)2. Promotions (campaign management)3. Persistency (loyalty, retention, churn)4. Performance (sales by product, category, store, channel)5. Profitability (product margin - gross, net, brand)6. Prospecting (customer acquisition, cross-sell, up-sell)7. Product (design, affinity, supply-chain)
2004년 4월 9일7
Agenda
CRM 개요분석CRM 접근법Sybase IWS 솔루션Sybase IQ 솔루션요약
2004년 4월 9일8
CRM and DW
CRM and DW as 2 sides to the same coin
CRM & BISolutions
DataWarehouse
Infrastructure Data Management
Data Integration
Data Models
ApplicationsEnd User ApplicationsEnd User Applications
Information ContentInformation Content
Data AcquisitionData Acquisition
Database PlatformDatabase Platform
2004년 4월 9일9
CRM Solution Evolution
팩키지 중심팩키지 중심
방법론 중심방법론 중심
툴 중심툴 중심
전문가전문가
Mar
ket
Time
팩키지 주도
개발 주도
Sybase IWS Solution
2004년 4월 9일10
Packaged Solution Components
애플리케이션/비즈니스모델
데이터및메타데이터정의
표준리포트및핵심쿼리
기반인프라소프트웨어
적용방법론및절차
컨설팅서비스
2004년 4월 9일11
Key Technical Challenges
Data Model 분석중심의데이터모델
변화에대응할수있는유연성
대량데이터분석성능
Data Integration 데이터품질확보
단순한아키텍처
메타테이터관리
Performance & Scalability 데이터폭발에대응
사용자증가에대응
2004년 4월 9일12
Agenda
CRM 개요분석CRM 접근법Sybase IWS 솔루션Sybase IQ 솔루션요약
2004년 4월 9일13
Sybase Solutions
Internet Applications:
Business Intelligence:
Mobile and EmbeddedComputing:
SQL Anywhere Studio
EnterpriseApplication
Studio“Industry” Warehouse
Studio
Enterprise Solutions:
Adaptive ServerE n t e r p r i s e C o n n ect
2004년 4월 9일14
System Architectures
Applications Layer
Real-time Operational Data Access Not Real-timeAnalytical Data Access
CRM BusinessApplications Personalization e-Information e-Commerce Integrated Intelligence
OrderProcessing
Call Center
MarketingAutomation
SalesAutomation
Financial
LegacySystems
( 내부사용자 ) (파트너 & 고객 )
Enterprise Portal
IWS
Analytical
CRM
Analytical
CRM
Business
Productivity
Business
Productivity
2004년 4월 9일15
IWS Packaging
산업별데이터모델
Data Data WarehouseWarehouseSYBASE IQSYBASE IQSYBASE IQ
프로젝트방법론
구현가이드
Warehouse Architect다차원설계도구
Warehouse Control Center메타데이터관리Informatica
Data Warehouse
ETL 도구(Option)
샘플
어플리케이션
분석 CRM
프로모션
판매분석
고객세분화
고객접촉
로얄티분석
…
샘플데이터
표준보고서표준보고서
BI 도구(Option)
2004년 4월 9일16
Data Model & Applications
Customer Relationship Analytics (CRA)Customer Relationship Analytics (CRA)
WebAnalytics
WebAnalytics
Household Match
Household Match
CreditCardBAI
CreditCardBAI
CapitalMarkets
BAI
CapitalMarkets
BAI
Life Insurance
BAI
Life Insurance
BAI
RetailBanking
BAI
RetailBanking
BAITelcoBAI
TelcoBAI
HealthcareBAI
HealthcareBAI
MediaBAI
MediaBAI
P&C Insurance
BAI
P&C Insurance
BAI
Campaign Analysis
SalesAnalysis
LoyaltyAnalysis
Customer CareAnalysis
Customer Profiling
CRA SQL QuickStartQuery Sets
CRA SQL QuickStartQuery Sets
CRA Business Objects
Integration
CRA Business Objects
Integration
CRA Cognos
Integration
CRA Cognos
Integration
CRA MicroStrategy
Integration
CRA MicroStrategy
Integration
IWS Customer Analytics
Infrastructure (CAI)• IWS Core Models
• IWS Tools
IWS Customer Analytics
Infrastructure (CAI)• IWS Core Models
• IWS Tools
BDA = Business Decision AnalyticsBDA = Business Decision Analytics
BAI = Business Analytics InfrastructureBAI = Business Analytics Infrastructure
Application Add-onApplication Add-on
Yet to be DeployedYet to be Deployed
Color-coding Key
CreditCardBDA
CreditCardBDA
CapitalMarkets
BDA
CapitalMarkets
BDAInsurance
BDAInsurance
BDARetail
BankingBDA
RetailBanking
BDA
TelcoBDA
TelcoBDA
HealthcareBDA
HealthcareBDA
ElectronicBill
Analysis
ElectronicBill
Analysis
MediaCirculationAnalytics
MediaCirculationAnalytics
InsuranceBDA
InsuranceBDA
MediaAdvertisingAnalytics
MediaAdvertisingAnalytics
2004년 4월 9일17
Business Analysis
CustomerProfiling
CampaignAnalysis
CustomerCare
Analysis
LoyaltyAnalysis
EVT_TYP_ID = EVT_TYP_ID
PRD_ID = PRD_ID
ENTY_ID = ENTY_IDENTY_ID = EMP_ID
GEO_ID = GEO_ID
LANGUAGE_ID = LANGUAGE_IDPRODUCT_ID = PRODUCT_ID
DEMO_ID = DEMO_ID
ENTY_ID = V_E_ENTY_ID
ENTY_ID = ENTY_ID
ENTY_ID = F_C_ENTY_ID
COR_EVT_TYP_ID = COR_EVT_TYP_IDCOR_RPT_STRC_ID = COR_RPT_STRC_ID
ENTY_ID = CNTC_RSOL_EMP_IDGEO_ID = GEO_ID
FNCL_SCOR_ID = FNCL_SCOR_IDMEASURE_UNIT_ID = MEASURE_UNIT_ID
COR_EVT_TXN_ID = COR_EVT_TXN_IDLANGUAGE_ID = LANGUAGE_ID
COR_EVT_TXN_SEQ_NB = COR_EVT_TXN_SEQ_NBPN_BHVR_SCOR_ID = PN_BHVR_SCOR_ID
PRODUCT_ID = PRODUCT_IDDEMO_ID = DEMO_ID
ENTY_ID = ENTY_ID
FNCL_SCOR_ID = FNCL_SCOR_IDMEASURE_UNIT_ID = MEASURE_UNIT_ID
DEMO_ID = DEMO_ID
PRODUCT_ID = PRODUCT_IDPN_BHVR_SCOR_ID = PN_BHVR_SCOR_ID
LANGUAGE_ID = LANGUAGE_ID
FNCL_SCORES_ID = FNCL_SCOR_ID
MEASURE_UNIT_ID = D_M_MEASURE_UNIT_IDMEASURE_UNIT_ID = MEASURE_UNIT_ID
GEO_ID = GEO_ID
COR_RPT_STRC_ID = COR_RPT_STRC_ID
EVT_TYP_ID = COR_EVT_TYP_ID
ENTY_ID = F_C_ENTY_IDGEO_ID = GEO_ID
LANGUAGE_ID = LANGUAGE_ID
EVT_TYP_ID = EVT_TYP_ID
DV_HR_EVT_TYPE
EVT_TXN_ID <pk,fk> INTEGER
EVT_TYP_ID <fk> INTEGER
EVT_TYP_SHRT_NM CHAR
EVT_TYP_FULL_NM char
EVT_TYP_CAT_SHRT_N CHAR
EVT_TYP_CAT_FULL_N char
F_HR_EVT
V_E_ENTY_ID <fk> INTEGER
V_E2_ENTY_ID <fk> INTEGER
EVT_DT_PRD_ID INTEGERADMIN <pk,fk> INTEGER
EVT_EMP_ID <pk,fk> INTEGER
EVT_EMP_DEMO <pk,fk> INTEGER
EVT_ADMIN_DEMO <pk,fk> INTEGER
CORE_EXT_ID <pk,fk> INTEGER
CORE_RPTG_STRUC <pk,fk> INTEGER
GEO_ID <pk,fk> INTEGER
MU_ID <pk> INTEGER
FIN_SCORE_ID <pk,fk> INTEGER
LANGUAGE_ID <pk,fk> INTEGER
PB_SCORE_ID <pk> INTEGER
F_C_ENTY_ID <fk> INTEGER
PRODUCT_ID <pk> INTEGER
DEMO_ID <pk,fk> INTEGER
EMP_ID <pk,fk> INTEGER
CDEX_SEQ_NO <pk> INTEGER
QTY integer
F_CORE_EVT
COR_EVT_TXN_ID <pk> INTEGER
COR_EVT_TYP_ID <pk,fk> INTEGER
D_M_MEASURE_UNIT_ID <fk> INTEGER
COR_RPT_STRC_ID <pk,fk> INTEGER
GEO_ID <pk,fk> INTEGER
MEASURE_UNIT_ID <pk,fk> INTEGER
FNCL_SCOR_ID <pk,fk> INTEGER
LANGUAGE_ID <pk,fk> INTEGER
PN_BHVR_SCOR_ID <pk,fk> INTEGER
PRODUCT_ID <pk,fk> INTEGER
DEMO_ID <pk,fk> INTEGER
ENTY_ID <pk,fk> INTEGER
V_E_ENTY_ID <fk> INTEGER
COR_EVT_TXN_SEQ_NB <pk> NUMBER
PRD_ID <fk> INTEGER
AMOUNT NUMBER
D_CORE_EVT_TYP
EVT_TYP_ID <pk> INTEGER
EVT_TYP_SHRT_NAM VARCHAR(15)
EVT_TYP_LONG_NAM VARCHAR(35)
EVT_TYP_SUBTYP_NAM VARCHAR(15)
D_CORE_RPT_STRC
COR_RPT_STRC_ID <pk> INTEGER
HOLDING_COMPANY VARCHAR(35)
ORG_TYPE VARCHAR(20)
ORG_NAME VARCHAR(35)
REGION VARCHAR(20)
SALES_TEAM_TYPE VARCHAR(15)
SALES_TEAM VARCHAR(15)
SALES_PERSON_NAME char
SALES_PERSON_GRADE CHAR
SALES_PERSON_TYPE CHAR
CHNL_CATEGORY1 char(18)
CHNL_TYPE CHAR
CHNL_SUBCAT CHAR
CHNL_NAME char
CHNL_CEASED_TRD_DT DATE
CHNL_ENTY_ID INTEGER
CHNL_CITY VARCHAR(20)
CHNL_POSTCODE VARCHAR(20)BEGIN_DATE_PRD_ID INTEGER
END_DATE_PRD_ID INTEGER
D_GEOGRAPHY
GEO_ID <pk> INTEGER
ALL_ENTRIES CHAR
POSTAL_CODE CHAR VARYING(1
CITY char
POSTAL_CD_PFX char(3)
HZRD_WTHR_AREA CHAR
HZD_WTHR_TYPE CHAR
DMA_CODE CHAR
SMSA_CODE CHAR
ST_PROV_AREA CHAR
TV_REGION CHAR
NTL_RADIO_AREA CHAR
LCL_RADIO_AREA CHAR
REGION CHAR
COUNTRY char(3)
CONTINENTY_ABBR char(3)
GEO_SUB_CNTNT_ABBR char(3)
SMRY_EFF_DT INTEGER
SMRY_END_DT INTEGER
PRISN_ADRS_IND CHAR
D_MSR_UNIT
MEASURE_UNIT_ID <pk> INTEGER
SHRT_DESC char(6)
LONG_DESC char(20)
D_DEMOGRAPHICS
DEMO_ID <pk> INTEGER
ALL_ENTRIES CHAR
INCOME_BAND VARCHAR(50)
AGE_BAND VARCHAR(50)
GNDR CHAR
MRTL_STAT CHAR
HIGH_VALUE_INDICAT CHAR
ACMDTN_CTGRY CHARNBR_IN_HH_BAND VARCHAR(50)
CHLD_AT_HOME_BAND VARCHAR(50)
SIZE_CLS CHAR
LEGAL_ORG_TYPE CHAR
NBR_EMP_BAND VARCHAR(50)
SECTOR_CLS CHAR
MAIL_PRMSN_IND CHAR
TELMKT_PRMSN_IND CHAR
D_FNCL_SCOR
FNCL_SCORES_ID <pk> INTEGER
INTERNAL_FNCL_SCOR VARCHAR(50)
EXPERIAN_SCOR_BAND VARCHAR(50)
SCOR_N_BAND VARCHAR(50)
PRFT_IND_BAND VARCHAR(50)
DEBT_INCOME_RATIO NUMBER
D_LANGUAGE
LANGUAGE_ID <pk> INTEGER
ISO_LANG_CODE CHAR
ISO_LANG_NAME char
LANG_GROUP VARCHAR(20)
D_PN_BHVR_SCOR
PN_BHVR_SCOR_ID <pk> INTEGER
SCORE1_BAND VARCHAR(20)
SCORE_N_BAND VARCHAR(20)
D_PRODUCT
PRODUCT_ID <pk,fk> INTEGER
ENTY_ID <fk> INTEGER
PRODUCT_LINE CHAR
PRODUCT_GROUP CHAR
PRODUCT_CODE CHAR
PRODUCT_NAME CHAR
PD_VARIANT_CODE CHAR
PRODUCT_VARIANT VARCHAR(35)
GRP_INDV_IND CHAR
PD_START_PRD_ID INTEGER
PD_END_PRD_ID INTEGER
F_SALES_EVENT
EVT_TXN_ID <fk> INTEGER
EVT_TYP_ID <fk> INTEGER
RPT_STRC_ID <fk> INTEGER
MEASURE_UNIT_ID <fk> INTEGER
FNCL_SCOR_ID <fk> INTEGER
PN_BHVR_SCOR_ID <fk> INTEGER
ENTY_ID <fk> INTEGER
EMP_ID <fk> INTEGER
EVT_TXN_SEQ_NBR <fk> INTEGER
F_CUS_CNTC_EVT
V_E_ENTY_ID <fk> INTEGER
CUS_CNTC_ID <pk> INTEGER
D_C_CTCT_RSOL_ID <fk> INTEGER
LGCY_SYS_CUS_CNTC INTEGER
CUS_CNTC_REF char
CUS_CNTC_EVT_ID INTEGER
F_C_ENTY_ID <fk> INTEGER
CUS_STSF_RT_ID <fk> INTEGER
CNTC_INIT_DT_ID INTEGER
HOUR_ID <fk> INTEGER
MINUTE_ID <fk> INTEGER
INIT_CNTC_EMP <fk> char
COR_EVT_TXN_ID <fk> INTEGER
COR_EVT_TYP_ID <fk> INTEGER
COR_RPT_STRC_ID <fk> INTEGER
GEO_ID <fk> INTEGER
MEASURE_UNIT_ID <fk> INTEGER
FNCL_SCOR_ID <fk> INTEGER
LANGUAGE_ID <fk> INTEGER
PN_BHVR_SCOR_ID <fk> INTEGER
PRODUCT_ID <fk> INTEGER
DEMO_ID <fk> INTEGER
CNTC_RSOL_EMP_ID <fk> INTEGER
CUS_ID <fk> INTEGER
SRSNS_CUS_CO_ID <fk> INTEGER
DV_EMP
ENTY_ID <pk,fk> INTEGER
RPT_STRC_ID INTEGER
GEO_ID INTEGER
ADR_ID INTEGER
EMP_DEMO_ID INTEGER
EMP_NAME_PFX CHAR
EMP_SNAME VARCHAR(15)
EMP_FNAME VARCHAR(15)
EMP_MNAME VARCHAR(15)
EMP_NAME_SFX CHAR
EMP_NTL_INS_NBR CHAR
EMP_HOME_TEL_NBR CHAR
EMP_PRIM_FAX_NBR CHAR
EMP_EMAIL_ID INTEGER
EMP_DOB DATE
EMP_GNDR CHAR
EMP_MRTL_STAT CHAR
EMP_LIFE_STAT CHAR
EMP_PREF_LANG VARCHAR(20)
F_CPGN_CNTC_EVT
CCE_ID <pk> INTEGERPROMO_EPSD_ID <pk> INTEGER
ENTY_ID <pk,fk> INTEGER
CNTC_PRD_ID <pk> integer
CCH_COUNT <pk> INTEGER
CORE__EVT_TYPE_ID <fk> INTEGER
COR_RPTG_STRUCT_ID <fk> INTEGER
GEO_ID <fk> INTEGER
MU_ID <fk> INTEGER
FINANCIAL_SCORE_ID <fk> INTEGER
LANGUAGE_ID <fk> INTEGER
PB_SCORE_ID <fk> INTEGER
PRODUCT_ID <fk> INTEGER
DEMO_ID <fk> INTEGER
EMP_ID <fk> INTEGER
COR_EVT_TX_SEQ_NO <fk> SMALLINT
TRGT_GRP char(3)
CORE_EVENTY_TYPE_ID INTEGER
CNTCT_CNTRL_GRP_IN CHAR
CCE_RESULT CHAR
P_PSYCH_ID INTEGER
AFFILIATION_ID int
PA_ID INTEGER
CC_COMM_EVT_AMT decimal(10,2)
D_TIME_PERIOD
PRD_ID <pk> INTEGER
DT_NA char(4)
DATE DATE
DAY_NAME char(8)
DAY_ABR char(3)
DAY_IN_WEEK SMALLINT
DAY_IN_MONTH SMALLINT
DAY_IN_YEAR SMALLINT
WEEK_IN_MONTH SMALLINT
WEEK_IN_YEAR SMALLINTCLNT_SVC_WK_IN_YR char(18)
MONTH_NAME char(10)
MONTH_ABR char(3)
MONTH_IN_YEAR SMALLINT
CALENDAR_QTR char(6)
MONTH_IN_QTR SMALLINT
WEEK_IN_QTR SMALLINT
DAY_IN_QTR SMALLINT
FINANCIAL_QTR char(6)
COMPETITOR_FSCL_YR char(6)
MONTH_IN_FNCL_QTR SMALLINT
WEEK_IN_FNCL_QTR SMALLINTDAY_IN_FNCL_QTR SMALLINT
SEMI_YEARLY SMALLINT
YEAR_NAME char(18)
YEAR_ABR char(4)
SEASON_NAME char(18)
SEASON_ABR char(6)
NBR_DAYS_SINCE_90 integer
HOLIDAY_IND CHAR
XMAS_HLDY_IND CHAR
EASTER_HLDY_IND CHAR
D_CPGN_COM_EVT_TYP
EVT_TYP_ID <pk,fk> INTEGER
CPGN_COMM_DESC CHAR
Industry-SpecificBusiness PerformanceAnalysis Industry-Specific
ProfitabilityAnalysis5)
SalesAnalysis
2004년 4월 9일18
----B
usin
ess P
erfo
rman
ce A
naly
sis
Bus
ines
s Per
form
ance
Ana
lysi
s ----
RetailBanking Insurance
Credit Card Telco Utilities Healthcare Retail
Campaign AnalysisCustomer ProfilingCustomer Care Analysis
Sales AnalysisCustomer Loyalty Analysis
Profitability AnalysisTraffic AnalysisPersistency ManagementChurn Management
Network ManagementRisk Management
Usage AnalysisHealthcare TreatmentMarket Basket AnalysisAsset Management
Outage AnalysisSales & Returns Analysis
Fault AnalysisPayment Method Analysis
Location AnalysisCost Discovery
Key Business Measures
Industry WarehouseStudios
CR
M A
naly
sis
CR
M A
naly
sis
Media
Circulation, Advertising Analysis
Key Business Measurements
2004년 4월 9일19
IWS Project Life Cycle
Typical Projects Start Here Start Here with Sybase IWS
Time
Res
ourc
es
Gather RequirementsUnderstand Line-of-BusinessDesign SchemaETL TemplatesBuild Queries for AnalysisImplementTest
1st Generation Warehouse
User FeedbackRefineTest
2nd Generation
Sybase IWSSaves Both
Time & Money
2004년 4월 9일20
IWS Key Benefits
Business OrientationIndustry-oriented DataReduced RiskRapid ImplementationModular & ExtensibleHigh PerformanceCost ManagementIntegratedOpen
2004년 4월 9일21
Agenda
CRM 개요분석CRM 접근법Sybase IWS 솔루션Sybase IQ 솔루션요약
2004년 4월 9일22
DW DBMS Requirements
대용량데이터에대한처리기능
다중사용자환경지원
성능, 유연성, 확장성, 경제성
Schema(모델) 변경에대한대응기능
장애에대한유연한대응기능
Ad-hoc(비정형) 질의처리성능
운영시소요되는인적비용최소화
데이터폭증에대한압축기능
Node추가시용이한기능
사용자증가에대한 처리기능
데이터증가에대한처리기능
Partition 기능
Parallel Processing 기능
I/O를최소화할수있는기법
다양한 Index 기법
성 능 유 연 성
확 장 성
시스템증설시소요되는비용최소화
경 제 성
D/W지원을위한 DBMS의기능
2004년 4월 9일23
Sybase IQ vs. Traditional RDBMS
Sybase IQSybase IQ Traditional RDBMSTraditional RDBMS
Row oriented - optimal for OLTP
Repeatable access to data
Index Explosion
Pre-aggregation - Data Explosion
Clustering, Partitioning, MPP
- high cost
Complex data loading and
management across partitions
Row oriented - optimal for OLTP
Repeatable access to data
Index Explosion
Pre-aggregation - Data Explosion
Clustering, Partitioning, MPP
- high cost
Complex data loading and
management across partitions
Column oriented - optimal for BI
Ad-hoc access
Data compression
Little to no aggregation
Efficient parallel access to
Vertical Data Storage
Simple data load, no table partition
management
Column oriented - optimal for BI
Ad-hoc access
Data compression
Little to no aggregation
Efficient parallel access to
Vertical Data Storage
Simple data load, no table partition
management
2004년 4월 9일24
Sybase IQ Features
Sybase IQ는성능, 유연성, 확장성, 경제성이뛰어난DSS와 DW을위한유일한전용 RDBMS 서버
Partitioning 기법Vertical PartitionHorizontal Partition
최적화된인덱스기법 (Bit-Wise)7가지방식의데이터저장과액세스방식
데이터의압축저장
대규모의데이터의효과적인처리
ASIQ MultiplexShared Disk구조Node 제한없음
2004년 4월 9일25
Flexibility
Ad-Hoc 질의처리시문제점미리정의되어있지않은질의는대용량데이터에대한Full Table Scan을유발함Ad-Hoc질의는최적의 Plan이선택되지않은경우가종종있음일반적으로 Ad-Hoc질의는요약 Table을이용할수없음
Ad-hocQueries
49%
Preplannedreports
51%
Data Warehouse 질의형태
Sybase IQ는모든 Column이 Index화되어있으므로어떠한 형태의질의에도
만족할만한성능을유지함으로새로운요구사항에유연하게대처할수있다. Sybase IQ는모든 Column이 Index화되어있으므로어떠한 형태의질의에도
만족할만한성능을유지함으로새로운요구사항에유연하게대처할수있다.
2004년 4월 9일26
Scalability다중 Node 시스템환경으로확장
SMP Cluster와같이 Shared Disk 구조로확장Sybase IQ Multiplex기능은기본기능
다중 Node 시스템으로확장에대한 Sybase IQ의대응Sybase IQ Multiplex기능은공유데이터베이스형태로구성(MPP , SMP Cluster)Node간간섭없이사용자환경구성용도에따른각 Node의 H/W구성을다르게할수있음
C P U
System Memory
I/O I/O
Sybase IQ MPX
C P U
System Memory
I/O I/O
Sybase IQ MPX
C P U
System Memory
I/O I/O
Sybase IQ MPX
Shared DB
Node간 DB공유
2004년 4월 9일27
Peformance
Column 단위의 Read : 90% 이상 I/O 감소부가적효과 : 기간계항목변경시 DW반영이용이.
기존 RDBMS SYBASE IQ
Vertical Processing(Column-Based)
Input/Output Data처리(필요한 Column만처리) I/O 90% 감소 초고속처리
c5c4c3c2c1 …c9c8c7c6 c5c4c3c2c1 …c9c8c7c6
2004년 4월 9일28
Economy
Sybase IQ -기존 Raw Data의 ~70% 정도로압축저장Data 폭증대응및 I/O Overhead 경감H/W의고성능 CPU, 대규모 Memory Cache활용도를배가시키고, Multi-Processing의자원을충분히활용
7010
5410
85209870
9700
100020003000400050006000700080009000
10000
DB2 UDBIBM
NCR InformixSun
Oracle8Sun
SybaseIQ
Raw Data
1TB
증가데이타
2004년 4월 9일29
Agenda
CRM 개요분석CRM 접근법Sybase IWS 솔루션Sybase IQ 솔루션요약
2004년 4월 9일30
요약
The Next Generation CRM Solution - Sybas IWS
비즈니스전략1
비즈니스어플리케이션
2
전사적 데이터아키텍쳐3
기술인프라4
Business Model
Applications
Data Model
DataManagement
