Chapter 10: Techniques for data mining in an operational warehouse
by Rogerio Silva, Jon Lind, Garrett Fitzsimons, Timothy Donovan, Pat Bates, Whei-Je
Solving Operational Business Intelligence with InfoSphere Warehouse Advanced Edition
- Notices
- Preface
- Chapter 1: Solving complex operational warehouse challenges
- Chapter 2: Overview of InfoSphere Warehouse Advanced Edition
- InfoSphere Advanced Enterprise Edition components
- DB2 10 Enterprise Server Edition
- WebSphere Application Server
- InfoSphere Warehouse Server
- InfoSphere Federation Server
- InfoSphere Replication Server
- Advanced access control
- IBM Cognos Business Intelligence for Reporting
- IBM Data Studio
- Optim Database Administrator
- Optim Development Studio
- InfoSphere Warehouse Client - IBM Design Studio and the wh command
- InfoSphere Data Architect
- InfoSphere Optim Query Workload Tuner
- InfoSphere Optim Performance Manager Extended Edition
- InfoSphere Optim High Performance Unload
- InfoSphere Optim Configuration Manager
- DB2 Recovery Expert
- DB2 Merge Backup
- InfoSphere Warehouse Packs
- InfoSphere Warehouse technical overview
- InfoSphere Warehouse core architecture (1/4)
- InfoSphere Warehouse core architecture (2/4)
- InfoSphere Warehouse core architecture (3/4)
- InfoSphere Warehouse core architecture (4/4)
- Overview of IBM Cognos Business Intelligence
- Architectural overview of the Optim family of tools
- InfoSphere Replication Server simplified overview
- InfoSphere Warehouse Advanced Edition command-line tools and utilities
- InfoSphere Warehouse implementation scenarios
- InfoSphere Advanced Enterprise Edition components
- Chapter 3: Scenario: Warehouse Live Demo Set
- Chapter 4: Data modeling: End to end
- Chapter 5: Temporal data management and analytics in an operational warehouse
- Temporal data management concepts and use cases
- Temporal data management in InfoSphere Warehouse Advanced Enterprise Edition 10
- Temporal data management with system time (1/2)
- Temporal data management with system time (2/2)
- System-period temporal tables (1/2)
- System-period temporal tables (2/2)
- Temporal data management with business time (1/2)
- Temporal data management with business time (2/2)
- Application-period temporal tables (1/2)
- Application-period temporal tables (2/2)
- Bitemporal tables
- Views and temporal tables
- Register settings for temporal tables
- Implications of temporal tables on operational warehousing
- Chapter 6: Managing complex query workloads in an operational warehouse environment
- Get started with Optim Performance Manager in your environment
- Optim Performance Manager in a partitioned database environment
- Using Optim Performance Manager to implement a Stage1 configuration of DB2 WLM
- Understanding query workloads in your environment
- Improving the overall performance of an activity
- Approaches to workload tuning
- Monitoring query workloads: Real-time operational to show the state and health of the system
- Chapter 7: Understand and address data latency requirements
- Chapter 8: Building a corporate backup and recovery strategy
- Advanced features for backup and recovery
- Plan a backup and recovery strategy
- Implement a backup and recovery strategy
- Implementing Optim High Performance Unload as part of your recovery strategy
- Optim High Performance Unload with backup images
- Optim High Performance Unload with backup images usage
- Optim High Performance Unload in a production environment
- Optim High Performance Unload with named pipes or output files
- Optim High Performance Unload control files
- Create the control file and issue a db2hpu command
- Install and configure Optim High Performance Unload
- Example recovery scenarios using Optim High Performance Unload
- DB2 Recovery Expert as part of your recovery strategy
- DB2 Merge Backup as part of your backup strategy
- Chapter 9: Managing data lifecyle with InfoSphere Warehouse
- Chapter 10: Techniques for data mining in an operational warehouse
- Chapter 11: Cognos Business Intelligence for InfoSphere Warehouse
- Chapter 12: InfoSphere Warehouse resilience with Optim Configuration Manager
- Challenges to maintaining an operational warehouse
- InfoSphere Optim Configuration Manager
- Integration of the Optim family of tools
- Monitor a DB2 database configuration (1/2)
- Monitor a DB2 database configuration (2/2)
- Optim tools runtime client (1/2)
- Optim tools runtime client (2/2)
- Optimize database storage with Optim Configuration Manager
- InfoSphere Warehouse high availability with Q replication and Optim Configuration Manager (1/7)
- InfoSphere Warehouse high availability with Q replication and Optim Configuration Manager (2/7)
- InfoSphere Warehouse high availability with Q replication and Optim Configuration Manager (3/7)
- InfoSphere Warehouse high availability with Q replication and Optim Configuration Manager (4/7)
- InfoSphere Warehouse high availability with Q replication and Optim Configuration Manager (5/7)
- InfoSphere Warehouse high availability with Q replication and Optim Configuration Manager (6/7)
- InfoSphere Warehouse high availability with Q replication and Optim Configuration Manager (7/7)
- Appendix A: InfoSphere Warehouse Editions comparison
- Related publications
- Back cover
© Copyright IBM Corp. 2012. All rights reserved. 355
Chapter 10. Techniques for data mining
in an operational warehouse
In this chapter we provide an overview of data mining techniques and use cases
in an operational data warehouse environment. We look at IBM and non-IBM
data mining tools and functions for implementing data mining for operational
warehousing.
The main focus of the chapter is on the integrated data mining modeling and
runtime features in InfoSphere Warehouse 10.1 Advanced Enterprise Edition
and Design Studio. We then consider an alternative data mining scenario using
SAS Enterprise Miner to provide an integrated and complementary solution.
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