IBM Information Server Training

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IBM Software Group
IBM Information Server
Transform – DataStage
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IBM Software Group
Why “Transform?”
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IBM Software Group
Why Transformation?
 Business Driver: Single View of Corporate Data
 Projects Related to Information Infrastructure
 Application integration
Business Goals
 Platform migration
 On-demand transformation and correction
 Application re-engineering and migration (ERP to CRM)
 Decision Support (BI, DW, Data Marts)
IT Initiatives
 Opportunity (discover new revenue sources)
 Control (Fraud detection, inventory)
Information
Integration
 Regulatory compliance -SOX, BASEL, Money Laundering
 Portals
 Balanced scorecard dashboards, BAM
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Transformation Pain
 Multiple sources for the same entity
 Lack of standards or consistent semantic
meanings across systems
 Embedded business intelligence
 Evolving transformation requirements
 Need for batch and real-time and service
oriented architectures
 Extreme data volumes!
 Business rules for resolving data conflicts
 Ownership and accountability
 Zero re-use of skills and processes
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IBM Software Group
How Is This Being Done Today?
 Hand coding: Java, C, C++, VB, .NET, COBOL, 4GLs…
 Spreadsheet “farms”
 Early generation ETL tools
 Competitive products
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IBM Information Server
Delivering information you can trust
Discover, model, and
govern information
structure and content
Standardize, merge,
and correct information
Combine and
restructure information
for new uses
Synchronize, virtualize
and move information
for in-line delivery
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IBM Software Group
The IBM Solution: IBM Information Server
Delivering information you can trust
IBM Information Server
Unified Deployment
Unified Metadata Management
WebSphere DataStage
Complex transformation for simplified data
exchange and reduced coding
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Implementation Examples
 Uses real-time data in a financial data warehouse for
intra-day analytics
 Improves supply chain management by creating
forecasts from POS data.
 Basel II initiative will release about 40% of its
minimum capital requirements
Deutsche Bahn
Group
 Replaced 4,000 hand-coded interfaces to create
single view of ticket data
 Manages 3 terabytes of store sales data for
customer and product analysis
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WebSphere DataStage
 Design integration projects
within a graphic, codeless
environment
IBM Information Server
DATASTAGE QUALITYSTAGE CLIENT
 Integrate data from the
widest range of enterprise
and external data sources
COMMON SERVICES
PARALLEL PROCESSING
METADATA
 Produce re-useable
components
 Deploy jobs in real-time,
batch mode, or as services
COMMON CONNECTIVITY
Sources
Targets
 Leverage the most scalable
and adaptable parallel
processing engine
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Graphical Design Metaphor
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Pre-Built Transformations for Productivity
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Graphical Design Metaphor
Extensive list of available
transformation functions
to select from:
Context-sensitive menu:
Easy access to transforms
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Error notification
Immediate notification when
there’s a problem!
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Extensive Re-use
 Shared Containers
Graphical unit of re-use
Share one developer’s (subject matter expert)
 Meta data research
 Business rule definitions
 Transformation logic
 Special techniques
 Routines
Re-usable functions
 Web Services
Deploy jobs as web services. Invoke from other jobs or
applications
Use Web Services
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Connectivity Ensures Data Access
Enterprise Applications
Business Exchange Formats
Flat File and General Access
JD Edwards
Oracle Applications
PeopleSoft
SAP BW (BAPI, IDOC)
SAP R/3 (ABAP, BAPI, IDOC)
Siebel
XMLS
EXML
EDI
FIX
SWIFT
HIPAA
RDBMS
Real-Time
IBM DB2
IBM IMS
VSAM
Oracle
Informix
RedBrick
SQL Server
Sybase
Teradata
U2 (Universe, UniData)
Tandem NON-STOP SQL
SAS
WebSphere MQ
SeeBeyond
Java Messaging Services
Java (Client & Transformer)
XML (Read / Write)
XSL-T XSL-T Transformer
Web Services (SOAP)
Enterprise Java Beans
VSAM
VSAM CICS
IDMS
C-ISAM
Sequential File
Complex Flat File
File Set
Data Set
Named Pipe
FTP (standard, secure)
Compressed / Encoded Data
External Command Call
Parallel Wrap 3rd party applications
…And many more!
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Benefits of Scalability
Process the same data
volume in less time
Processing Volume (gigabytes)
- or -
Processing Time (hours)
20
15
10
5
2
4
8
12
16
Number of CPUs
24
32 - - -
Process more data in the
same amount of time
1t
750
500
250
2
4
8
12
16
24
32 - - -
Number of CPUs
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Parallel Execution Enables Timely Integration
Uniprocessor
SMP System
MPP, GRID, and
Clustered Systems
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Enabling Parallelism
Given a Job Design:
…DataStage creates “n” processes at runtime
for each Stage, where “n” is the number of logical nodes
defined in a configuration file
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Metadata Driven Integration
 Shared metadata across product
modules
Better and faster communication between
team members
Immediate access to definitions and notes on
all objects
Greater understanding, better data
 Powerful Metadata driven design tools
Impact Analysis
Quick Find and Advanced Find
Impact Analysis
Data Lineage reports
Greater productivity, easier maintenance,
reuse
Find Capability
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DataStage Strength Summary
 Graphical, top-down design metaphor
 Extensible, component based architecture
 Strong Re-use capabilities
Shared Containers, Routines & Web Services
 Graphical sequencing (“job flow”)
 Application Deployment
Parameterization
 Changed Data Capture
 Ubiquitous Connectivity
 Unlimited Scalability
Design serially, deploy in parallel
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Thank You
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