Agenda: ISUG 2013 13:00 - 13:05 Välkomna och agendaöversikt 13:05 - 13:50 Tony Curcio (produktchef för Information Server) - will talk about new features in IS 9.1. 13:50 - 14:00 Rast 14:00 - 14:45 Ian Baxter - from Data Assessments to Capital Assets 14:45 - 15:00 Kafferast 15:00 - 15:20 Folksam - delar med sig av sina erfarenheter av uppgradering av IS 15:20 - 16:10 Tony Curcio- IS roadmap and performance and tuning of IS + discussion topics/questions 16:10 - 16:20 Rast 16:20 - 17:00 Peter Bjelvert - CDC (live demo) Discovering the Value of IBM InfoSphere Information Server

InfoSphere Change Data Capture An IBM Proof of Technology Value of IBM InfoSphere Information Server InfoSphere Change Data Capture Go to 'View > Header and Footer' to change this to match the event title 2

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 Go to 'View > Header and Footer' to change this to match the event title

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 Go to 'View > Header and Footer' to change this to match the event title 4

Flexible implementation Uni-directional Cascade Consolidation Distribution Bi-directional Local Two-way Multi-thread Remote capture

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

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

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

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 Go to 'View > Header and Footer' to change this to match the event title 9