®
IBM Software Group
© 2005 IBM Corporation
Steven Fontana, IBM, Integration Specialist - Citigroup [email protected] 631-804-8888
John Bekisz, IBM, Integration System Engineer
Enterprise Data Integration
Integration Solution Overview
November 18, 2005
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Financial Services Institutions Face Key Market Challenges
Channel Optimization Multiple touch points provide challenges in
maximizing customer wallet and mind share
Single View of Product and Customer
Past CRM investments have not achieved the promise of wallet share due to silo LOB
implementations
Complex Business Infrastructure
Legacy applications continue to put pressure on profits and prevent enterprise views of customers,
products, trades, positions, etc
Regulatory ComplianceGovernment mandates and industry standards
require data infrastructures to be compliant with USA Patriot, Sarbanes, Basel 2, etc
Market and Partner Networks
Enhanced market infrastructures (e.g., SWIFT Net) provide new ways to optimize payments and
settlements infrastructures
Key FS Market Challenges
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Key FS Market Challenges
IBM Information Integration’s Capabilities Address These Challenges
Channel Optimization
Single View
Complex Business Infrastructure
Regulatory Compliance
Market and Partner Networks
Deliver a single version of the truth across multiple channels and business units
Accelerate consolidation of legacy sources to target applications to reduce support costs
Enhanced support for market infrastructuressuch as SWIFT Net and new connectivitystandards such as SWIFT ML
Profile, cleanse and transform enterprise data to support Sarbanes, Basel 2, AML
IBM Information Integration’s Capabilities
Deliver updated portfolio, account and customer information to multiple channels to support marketing and customer service
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IBM Information Integration’s FS Successes
Consolidated data across dozens of silo LOB’s ; branches, service centers at Top 10 Brokerage Firm to provide point of contact up sell capability
More than 20,000 users utilize single standard corporate utility to analyze customer profitability at JP Morgan Chase
Consolidated multiple mortgage and lending systems to provide new CRM-based system for GMAC Mortgage
Single common library of data integration routines deployed throughout 39 countries for Standard Chartered Bank-sets the stage for Basel II IRB
Accelerated adoption of new SWIFT standards at Credit Suisse Group without back office changes
IBM Information Integration’s Customers are Proof Points
Deliver a single version of the truth across multiple channels and business units
Accelerate consolidation of legacy sourcesto target applications to reduce support costs
Enhanced support for market infrastructuressuch as SWIFT Net and new connectivitystandards such as SWIFT XML
Profile, cleanse and transform enterprise data to support Sarbanes, Basel 2, AML
IBM Information Integration’s Capabilities
Deliver updated portfolio, account and customer information to multiple channels to support marketing and customer service
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Enterprise Data
Warehouse
Technologies Introduced To Address The Problem
Oracle
Othersources
SAP
PeopleSoft
Legacydata
Siebel
TradingPartners
ElectronicMarketplaces
DataMart
DataMart
Operational Data Store
ConsumerPortals
Analytical
Important and beneficial functionality But no real solution to the key data
problems
Extract/Transform/LoadETL
Enterprise Application Integration EAI
Web Integration
Enterprise Information Integration EII
Poor data design and organization
Poor data management
Deteriorating data quality
Changing business & technology
Inadequate data delivery
Extract, Transform and Load ETL
Enterprise Data Enterprise Data IntegrationIntegration
Integrate the Parts Common Meta Data Automation
Which Technology do I use? Will my data be siloed?
Profiling
How Flexible Is My Design?
SOACleansing
Reusability
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Application Consolidation, BI/DwH, ComplianceCustomer Challenges
Payroll3
Payroll1
Payroll2Fin 3Fin 2
Payroll3
Payroll1
Payroll2Fin 3Fin 2
FinancialFinancial RisksRisks
Customers I
Customers I
CustomersII
CustomersIISUPPORTSUPPORTSUPPORTSUPPORT
PRODUCTIONPRODUCTIONPRODUCTIONPRODUCTION
DISTRIBUTIONDISTRIBUTIONDISTRIBUTIONDISTRIBUTION
REFERENCESREFERENCESREFERENCESREFERENCES
GROUP LEVEL
COMPANY LEVEL
METADATA REPOSITORY
Current State In Large Enterprises
Overlapping and redundant: Data Applications Infrastructure (servers and storage)
No single, consolidated view of enterprise data
Hand coded data integration spaghetti
Supporting all of the above: Consumes >40% of IT budget Chokes flexibility and competitiveness
Desired End State In Large Enterprises
Radical consolidation of: Data Applications Infrastructure (servers and storage)
Run the business on a single, consolidated view of enterprise data (Master Reference Data)
Eliminate hand coded data integration spaghetti
Reduce costs radically while improving competitiveness
Big Gap
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Payroll3
Payroll1
Payroll2Fin 3Fin 2
Payroll3
Payroll1
Payroll2Fin 3Fin 2
FinancialFinancial RisksRisks
Customers I
Customers I
CustomersII
CustomersIISUPPORTSUPPORTSUPPORTSUPPORT
PRODUCTIONPRODUCTIONPRODUCTIONPRODUCTION
DISTRIBUTIONDISTRIBUTIONDISTRIBUTIONDISTRIBUTION
REFERENCESREFERENCESREFERENCESREFERENCES
GROUP LEVEL
COMPANY LEVEL
METADATA REPOSITORY
Current State MetricsData Major US Bank has tens of terabytes of redundant and overlapping data
following acquisitions.
Applications A major global chemicals company is running 12 instances of SAP and
has no consolidated view of the business. A major global telco was operating three order systems and had no
consolidated view of orders.
Infrastructure Global logistics supplier needs to consolidate:
18 data centers to 3-4 data centers 1500 applications to 200 applications 2600 servers to 1600 servers
Hand coded data integration Major US Bank - 3,000 people hand coding Canadian Bank – 5,000 people hand coding
Big Gap
Desired End State MetricsData Creating consolidated view of enterprise data will save the US Bank $30 million in
storage costs on one project.
Applications Consolidation to 1 global SAP instance will reduce operating costs by $40 million
annually. Creating a consolidated view of orders led to the capture of $200 million in
revenue that was previously lost.
Infrastructure Restructuring and consolidation will increase the logistics supplier’s operating
profit by at least € 1 billion annually by 2005.
Hand coded data integration US Bank – 50% productivity gain would save $150 million annually Canadian Bank – 50% productivity gain would save $250 million annually
Customer Challenges
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Enterprise Information Integration Platform
CRMERPSCM
RDBMSLegacy
EAI/ Messaging
Web servicesXML/EDI
Data Warehouse
ANY SOURCE ANY TARGET
CRMERPSCMBusiness IntelligenceRDBMSEAI/ MessagingWeb servicesXML/EDIData Warehouse
Parallel Execution
Meta Data Management
DISCOVERDISCOVER
Discover data content and structure
Profile StageAudit Stage
PREPAREPREPARE
Standardize, match, and
correct data
TRANSFORMTRANSFORM
Transform, enrich, and deliver data
DataStageDataStageTX
Federated
UnderstandUnderstand ReconcileReconcile DeliverDeliver
Quality Stage
Service Oriented Architecture
On-Demand and Event Driven Services
Discovery Meta Data SemanticsStandardization Enhancement
Cleansing
Transformation
AuditingLogicDelivery
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COE
Project #1
Billing SystemConsolidation
MasterReference
Data
Project #2
GlobalData Warehouse
Project #3
General LedgerConsolidation
Project #4
Single View of Customer
(Siebel)
1. Implement First Project
ArchitectureMethodologySoftware PlatformMentoring and best practices
2. Start implementing COE and MRD on first project
3. Cost savings on first project fund COE and downstream projects.
4. Start implementing downstream projects• Leverage capabilities developed previously
• trained staff• software templates, software components, business rules, etc.
• Continue to build COE and Master Reference Data
5. Build Self Sufficiency
Making The Transition
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Financial Lending Institution
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Our Capabilities in Financial Services
TransactionalTransactional OperationalOperational AnalyticalAnalytical
Subsidiaries/LOB Units
Financial Institution
Customers
Standards Adoption (SWIFT Net Migration & FiXML)
Single View Across Product,Customer, Portfolio
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11 5533
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22Master Data Management forReference & market Data
Core Banking & Legacy Application Consolidation
Channel Optimization 66
66Financial Services
Value Chain
IBMCapabilities
Environments
44Risk Management & Regulatory Compliance
Market and Partner Network
22
Subsidiaries/LOB Units
Branches/LOB Units
44
55
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Complex messages; difficulty in adding new messages or supporting new versions
Many industry protocols, transports and data formats. Flexibility is key
Need for integration with back-end systems hosting data in complex formats
Need for quality data to have quality partner interaction
Support for SWIFT, EDI and other industry standards for partner trading, with message data normalized for streamlined updates
Broad range of back-end connectivity options supported by powerful data transformation and connectivity via SAA
Data matching and standardization, limiting errors and delivering consistency
Data connectivity, transformation and quality – in one integrated platform.
Standards-Based Trading Pain Points IBM Information Integration Value Customer ExamplesCredit Suisse Group
Deutsche Bank
KAS Bank
Fidelity Investments
Bank of New York
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Standards Adoption
IBM PACK for SWIFT
Back-end Systems
LogicalMessageFormat
IBMDataStage TX
Clients
CPGCounter-parties
CPGServiceProviders
SWIFTNet
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Credit Suisse Group
Heightened ROI and competitive pressures required the automation of the process flows to reduce overall settlement times without access to incremental internal resources. Needed to convert to ISO 15022 messages from 7775 format without impacting multiple back office systems
Implemented IBM DataStage™ TX and IBM™ PACK for SWIFT with Logical Message Format for complete SWIFT integration and support for all SWIFTNet services. LMF shields back end systems from periodic message format changes
Accelerated and simplified adoption of new messages (ISO 15022) without overhaul of back-office systems, with normalized message data across the organization. Simplified management and monitoring, providing complete visibility into transactions and messages
Credit Suisse Group | World-leading financial services company, advising clients in all aspects of finance, around the world, around the
clock. 360° Finance
Problem Solution Result
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Duplications, errors and manual overrides in transactional data received from sales channels
Duplicated and inconsistent data in corporate systems
No single understanding of customers
Not ready for Global Data Synchronization
De-duplication of security records stored in multiple formats/systems
Real time reconcilations against data received from custodians, buy side, sell side, street etc
Customizable business rules for matching
Investigate and understand data structures and formats
Single View Integration Pain Points IBM Information Integration Value Customer Example
Top Ten Brokerage Firm
Freddie Mac
Wells Fargo
Mrs. M. Talber
Global Custodians
Brokerage Firm
Institutional / Individual Accounts
Institutional / Individual Accounts
Funds Managers
Trading Accounts
Buy and Sell side allocation
Security masters, SSI’s
Reference DataReference Data
DTC and CUSIPS, etc Single View and Mappingto Industry Data Pools
Master Data Management22
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Freddie Mac
Freddie Mac | A stockholder-owned corporation established by Congress in 1970 to
support home ownership and rental housing
Unable to quickly assess the impact of millions of changes to their mortgage portfolio on a daily basis. This limited their ability to manage risk, extend loans and optimize margins by exploiting small rate differences between financial borrowing markets and lending rates.
Replacing hundreds of manually-coded integration programs with automated, metadata-driven parallel solution. Cut time required to update 1M+ transactions per data. Using metadata to document process for easier maintenance and extensibility.
Changes to mortgage portfolio will be visible via Freddie Mac’s enterprise data warehouse systems within 12 hours of occurring Richer and timelier reporting environment Greater opportunity to increase margins and expand lending
Problem Solution Result
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High maintenance costs and lack of data/process unity associated with running multiple instances of the same application
Unrealized value from mergers and acquisitions with multiple DDA and credit , lending systems
Keeping track of metadata during application transition and consolidations
Uncoordinated technical architecture
Rapidly profile and analyze data across corporate systems to prepare for migrations and consolidations
Migrate only data that is meaningful, active and de duplicated
Rapidly locate all institutional data in source systems and prepare to migrate to target applications
Conduct impact analysis on potential changes to metadata
Legacy Application Pain Points IBM Information Integration Value Customer Examples
GMAC Mortgage
Nordea
Lloyds Bank
Target Staging
IBM Information Integration Platform
TargetEnvironmentLegacy
R/3
R/3
R/3
R/3
Initial Staging
Define Relations
Standardize
Cleanse
De-Dupe
Map
Core Banking and Legacy Application Consolidation
Legacy
Legacy
Legacy
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Nordea
Needed to support a sub ledger consolidation from 4 large retail banks. Auditing and guaranteed delivery are critical.
Transactions arrive from complex flat files from many countries, and must be validated, mapped, reconciled and prepared before loading into R/3.
IBM DataStage™ and SAP R/3 PACK prepares data for the initial load into R/3.
Nordea is able to act as one operating unit, in support of having one brand Cut IT budget by 25%, resulting in savings of $8M by 2003
Problem Solution Result
Nordea | Largest financial services group in Scandinavia with EUR 252 billion in total assets, 9.7 million personal and 1 million corporate customers
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Three year period of measuring operational risk data to meet Basel II Accords has begun
US Patriot Act has extreme focus on Anti Money Laundering and Know Thy Customer- fines for non compliance are severe
Sarbanes Oxley and other Regulatory mandates place intense focus on data quality
Rapidly profile and analyze data across corporate systems to prepare for internal ratings based approach for Basel 2
Data Quality Assessments that quickly identify gaps in required data for compliance in SOX, AML etc
Conduct impact analysis on potential changes to metadata and change data management
Risk Management Pain Points IBM Information Integration ValueCustomer Examples
Ny Kredt
NASDR
Standard Chartered
AIG
Risk Management & Compliance
Meta Stage and DBMS
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Data
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Data
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Data
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Data
Data Marts
LossData store
FinancialData store
HistoricData store
EnterpriseData store
Core Banking Products
Credit
Collaterals
Customer
Loss Data
Data sourceTransformation& calculation
Rating, PD, LGD,CCF Models
BII OperationalRisk Engine
BII CreditRisk Engine
Interest RateRisk Engine
Internal CreditRisk Engine
Market Data
Reporting
Analysis
Disclosure
Management
Data
Meta Stage and DBMS
Extr
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Data Integration
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Data
Data Marts
Result
Data
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Data
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Data
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Data
Result
Data
Result
Data
Result
Data
Result
Data
Data Marts
LossData store
FinancialData store
HistoricData store
EnterpriseData store
LossData store
LossData store
FinancialData store
HistoricData store
EnterpriseData store
Core Banking Products
Credit
Collaterals
Customer
Loss Data
Data sourceTransformation& calculation
Rating, PD, LGD,CCF Models
BII OperationalRisk Engine
BII CreditRisk Engine
Interest RateRisk Engine
Internal CreditRisk Engine
Market Data
Reporting
Analysis
Disclosure
Management
Data
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Standard Chartered
Standard Chartered | World- leading emerging markets bank with over 500 offices in more than 50
countries
Wholesale Bank Basel II Credit Risk Project goal is to meet Basel II Capital Accord guidelines by 2006, utilizing new internal modeling approaches for capital calculations. Required strong risk management analytics, processes and disclosure. Needed consistent data management processes across operations, customers and supporting technology in more than 50 countries
Problem Solution Result
Centralized Basel II Data Integration Solution leverages IBM Enterprise Integration Suite™ to deliver enterprise integration. Integration routines are built in IBM DataStage™ and deployed throughout Standard Chartered Bank in repeatable manner. Data is treated in a consistent manner, critical to Basel II compliance.
• Delivers enterprise integration and data consistency necessary for Basel II
• Supports groups across the Wholesale Bank (Group Risk Management, Finance and Special Asset Management teams)
• Provides reliable information for management and regulatory reporting, portfolio management and front-line business users
“With IBM, Standard Chartered Bank will build one common library of data integration routines and deploy them throughout our company, a critical factor to ensuring that our risk data is all handled in accordance with company standards." -- Senior Project Manager, BASEL IS
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Duplications, errors and manual overrides in transactional data received from sales channels
Duplicated and inconsistent data in corporate systems
No single understanding of customers
Not ready for Global Data Synchronization
De-duplication of customer records stored in multiple formats/systems
Real time account and customer information against data received from branches; call centers, Web etc
Customizable business rules for matching
Single View Integration Pain Points IBM Information Integration ValueCustomer Example
JP Morgan Chase
Wells Fargo
Edward Jones
Mrs. M. Talber
John & Molly Talber
Molly Talber
Customer AccountsCustomer Accounts
M Talber
Depository Accounts
Credit and Lending
Investment Accounts
Product RecordsProduct Records
Mortgage, etcSingle View and Mappingto Industry Data Pools
Single View55
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JP Morgan Chase
JPMorgan Chase | A leading global financial services company
Needed single, authorized source for customer profitability reporting & analysis. Solution required highly automated integration process, straightforward change management, and ability to handle a diversity of data sources.
Used IBM Information Integration solution to receive 300+ feeds from product systems worldwide, then transform and load into a data warehouse. 1TB+ of data is now updated every 48 hours with daily refreshes planned.
More than 20,000 internal customers now use a single corporate-standard customer profitability “utility” to analyze and make decisions that improve the overall profitability of the company No one is allowed to comment or “spin” profitability without referring to this utility
Problem Solution Result
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Channel Optimization
AuthoritativeDatabase
Source Systems:
•Kiosks•ATM’s•Call Centers•Internet •DDA Core Banking•Branches
Customer Inf File
IBM Information Integration Suite
No single understanding of customers or brands
Lack of a comprehensive view of data across systems
Duplications, errors and manual overrides in transactional data received from sales channels
Inconsistencies between data in different systems causing inaccurate information
Link multiple disparate sources of information through semantics-mapping and data matching
Standards-based interfaces to integration brokers
Maintain meta linking and matching between data sources
In-flight data enrichment
Access to a broad range of legacy sources
Channel Pain Points IBM Information Integration Value Customer Examples
Top Ten Brokerage Firm
New York Life
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New York Life Insurance | Largest mutual life insurance company in the United States
Agents and HQ staff were unable to maximize customer profitability or pursue up-sell/cross-sell opportunities. Detailed customer and policy data residing in 15+ separate legacy mainframe policy systems with little to no documentation and poor data quality was unavailable to users and multiple channels.
Improved customer visibilityby providing 10+ staff with adhoc reporting to completecustomer information Reduced IT costs by $130kannually by eliminating manualreporting Provided agents with 7x24detailed customer and policydata through secure web site
Problem Solution Result
New York Life Insurance
Multi-tier solution with UNIX-based operational data store and enterprise data warehouse feeding marts for reporting, and 7x24 web-based access. Leveraging IBM DataStage™ to integrate legacy data into warehouse and IBM ProfileStage™ to better understand and access mainframe sources.
®
IBM Software Group
© 2005 IBM Corporation
Websphere Data Integration Suite Technical Product Overview
John Bekisz
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Delivering accurate, consistent, timely, and coherent business information
WebSphere Information Integration Solutions
Integrated Metadata
Integrated Metadata
StandardAPIs
Service-oriented Scheduled Event-driven
Connect to Data and Content
Find Federate Place Publish
Analyze Model Cleanse TransformInformationIntegrationServices
RTI
DataStageDataStage TX
MetaStage
QualityStage
ProfileStageAuditStage
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The Ascential/IBM Data Integration Solution
Parallel Execution Engine
DISCOVERDISCOVER
Discover data
content and
structure
PREPAREPREPARE
Standardize, match, and correct data
TRANSFORM and DELIVERTRANSFORM and DELIVER
Transform, enrich, and deliver data
ProfileStageAuditStage
ProfileStageAuditStage
QualityStageQualityStage DataStageDataStage TX
DataStageDataStage TX
Meta Data Management
Service-Oriented Architecture
Real-Time Integration Services
Enterprise Connectivity
and Event Management
• Open, Service-Oriented Architecture
• Integrated Data Profiling & Data Quality
• Advanced Data Transformation and Routing
• Reusable Components & Rules• Unlimited Performance with
Linear Scalability• Robust, Intelligent Adapters• Anytime, Anywhere Connectivity• Industry Standard Compliant
(XML, EDI, JMS, JCA)• Industry-Ready Integration
Solutions
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Data Transformation: DataStage
Why DataStage?
Graphical, codeless design environment
Extensible transformation platform that leverages existing business logic
Built on the most scalable and adaptable processing engine
Enterprise-class platform that delivers proven ROI
Manages the evolution from development to deployment smoothly
Business Benefits
Unsurpassed levels of productivity
Accurate, consistent information delivered on-time
Consistent rules applied across applications
Data and process is auditable
DataStageDataStage
Inputs
Transform
Quality
Output
DataStage Server
Multiple Jobs in Parallel
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Complete Development Environment
Integrated ETL development workbench
Design, develop, view data
Debug, test, monitor & manage
Metadata driven ETL processing
Portability
Develop anywhere, Deploy anywhere
Client has access to multiple servers
Server maintains all connectivity
Extensible architecture
Many Plug-ins to other vendors products
Tran
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mTr
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It’s in There
Pre-built Functions
Date/Time Conversions
Data Type Conversions
String Manipulations
Mathematical Formulas
Data Warehouse Functions
Surrogate Key Generation & Maintenance
Aggregation
Change Compare
Data Manipulations
Sorting, Merging, Joining, Filtering
FTP, HTTP, operating commands
Online Library available for Download
Tran
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DataStage Architecture
High Degree of Reuse and version control at each level
We keep you in the tool
Transforms and Routines
Shared Container
Job
Job Sequencer
Tables
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80/20 Rule
80% of Transformations are simple
Only Spend 20% of your time on these rules
String formatting, Date conversions, Look-ups
20% of Transformations are complex
Spend 80% of your TIME on the 20% Complex
Too Much Data; Too Little Time
Data Scrubbing, householding, survivorships
Multiple Sources to Multiple Targets
Complex Business Rules which require business logic
– Nested if/then/else; case; loops; arrays
EVERYBODY Does the 80% Easy Stuff Easily
ONLY Ascential Makes the 20% Complex look Easy
Tran
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Easy to Use GUI
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Work as you think
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Extracting from DB/2 into Hash Files
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More Robust Example
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Transformation
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Example: MQ and QualityStage Integration
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Example: MQ and QualityStage Integration
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Example: MQ and QualityStage Integration
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Example: MQ and QualityStage Integration
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High Level Design
Design the Extraction, Transformation and Load processes
Work as you think: Move easily from
white board to design
Integrated: Test, debug, data viewer,
run DS jobs and perform maintenance from a common graphical workbench.
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Single Point of Control
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Full job control
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Produce and Consume Web Services
Invokes Web services from within DataStage jobs
WSDL browse & import capabilities
Easily call WS operations from DataStage
Web services can be sources, targets, or transformations
Use WS PACK to invoke a Web service from a DataStage job
Use RTI to package a DataStage job as a Web service
DataStage job
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Real-time Integration (RTI) Services
RTI Services connection to Enterprise Applications, Portals, and Business Process Integration
“Always on”
DataStage Server 1
“Always on”
DataStage Server 2DataStage Server N
PlatformLoad
Balancing
Logging
AuthorizationEnterprise Java Beans
Authentication
Auditing
Java Messaging Service
Web Service Client
RTIAgent
Web Service Client
JMS Client
Java Application
“Always on”
RTIAgent
RTIAgent
RTI Input QualityStage
RTI Console
Ascential RTI Server – J2EE Environment
Enterprise Integration Suite
Transformer RTI Output
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One Integrated Solution
Three Points of Integration GUI Server Metadata