1. Agenda: ISUG 2013 13:00 - 13:05 Välkomna och agendaöversikt
13: :50 Tony Curcio (produktchef för Information Server) - will talk about new features in IS 9.1.
13: :00 Rast
14: :45 Ian Baxter - from Data Assessments to Capital Assets
14: :00 Kafferast
15: :20 Folksam - delar med sig av sina erfarenheter av uppgradering av IS
15: :10 Tony Curcio- IS roadmap and performance and tuning of IS + discussion topics/questions
16: :20 Rast
16: :00 Peter Bjelvert - CDC (live demo)
Discovering the Value of IBM InfoSphere Information Server

2. InfoSphere Change Data Capture
An IBM Proof of Technology
Value of IBM InfoSphere Information Server
InfoSphere Change Data Capture
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3. InfoSphere Change Data Capture
An IBM Proof of Technology
InfoSphere Change Data Capture
Real-time changed data capture across database systems
Captures data from production systems without impacting performance
Applies data to target systems in real time
Transforms database operations into Extensible Markup Language (XML) documents
Supports simple or composite XML transactions
Creates audit trails for full data traceability
Log-based Change Data Capture (CDC) technology
Quick deployment through easy-to-use graphical interface
Detects + Delivers Information Across
Heterogeneous Data Stores in Real Time
Information Server Change Data Capture focuses on capturing transactional data from source systems and delivers it to target systems in real time. The technology uses changed data capture (CDC), which means only the data that has changed in each transaction is delivered as opposed to delivering entire database rows in order to maximize throughput and scalability. (Depending on the scenario, full database rows or data fields that have not changed can be delivered as well. This is a competitive differentiator as some solutions do not provide this option.)
Changed data can be packaged into XML documents for posting onto message queues and topics.
Since data is captured on a transactional basis, some customers use Information Server Change Data Capture to track data patterns as well as for creating full audit trails. This capability is especially useful in highly regulated verticals such as pharmaceuticals and financial organizations.
Discovering the Value of IBM InfoSphere Information Server
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4. An IBM Proof of Technology
Scope for today
Identify and understand the benefits of using real-time data integration for:
Integrating data across a heterogeneous landscape
Reducing ETL batch cycles
Developing a near real-time business intelligence (BI) platform
Event enabling relational databases for service oriented architecture (SOA): enterprise application integration (EAI), enterprise service bus (ESB)
Understand the basics of developing and operating InfoSphere Change Data Capture 4
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5. Flexible implementation
Uni-directional
Cascade
Consolidation
Distribution
Bi-directional
Local
Two-way
Multi-thread
Remote capture

6. High level architecture
Java-based GUI
for admin and monitoring
Sources
Targets
Oracle
Database
(Oracle, DB2, SQL Server,
Teradata, etc.)
SQL Server
ETL (DataStage, others)
TCP/IP
DB2
JMS (MQ, others)
Information Server
(DataStage, QualityStage, etc.)
Journal Log
Redo/Archive Logs
Source Engine
and Metadata
Target Engine
and Metadata
Informix
Flat files
Sybase
Web Services

7. InfoSphere CDC  DataStage/QualityStage integration
Option 1: Database Staging
Option 2: MQ-based integration
Option 3: File-based
Option 4: Direct connect
InfoSphere CDC captures change made to source database
InfoSphere CDC writes changes to a staging table.
DataStage reads the changes from the staging table, transforms and cleans the data as needed
Update target database and internal tracking with last bookmark processed
InfoSphere CDC captures/collects changes made to remote database
Captured changes written to MQ
DataStage (via MQ connector) processes message and passes data off to downstream stages
Updates written to target warehouse
InfoSphere CDC writes each transaction to a file
DataStage reads the changes from the file
Update target database with changes
InfoSphere CDC captures and collects changes made to source
Captured changes passed to CDC for DataStage engine
DataStage transaction aware stage processes transactions and passes data off to downstream stages
Update target database with changed data

8. Modes of replication Continuous mirroring
Changes read from database log.
Apply change at the target as soon as it is generated at the source.
Replication job remains active waiting for next available log entry.
Periodic mirroring
Apply net changes on a scheduled basis.
Replication job ends when available log entries are processed.
Refresh
File/table level operation.
Apply a snapshot version of source table.
Typically used to achieve initial synchronization of source and target table.
Three types of replication modes are available depending on the needs of the business.
Continuous mirroring – uses log-based CDC to replicate data transactions in real time as they occur
Periodic mirroring – replicates data only during scheduled intervals, does not provide transactional history
Refresh – one-time snapshot replication from source to target

9. An IBM Proof of Technology
How do I …
DBA
Continuously mirror between databases
Summarize information using InfoSphere CDC
Integrate real time data feeds to an InfoSphere DataStage ETL process 9
Discovering the Value of IBM InfoSphere Information Server
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