Book description
Today, organizations face tremendous challenges with data explosion and information governance. InfoSphere™ Optim™ solutions solve the data growth problem at the source by managing the enterprise application data. The Optim Data Growth solutions are consistent, scalable solutions that include comprehensive capabilities for managing enterprise application data across applications, databases, operating systems, and hardware platforms. You can align the management of your enterprise application data with your business objectives to improve application service levels, lower costs, and mitigate risk.
In this IBM® Redbooks® publication, we describe the IBM InfoSphere Optim Data Growth solutions and a methodology that provides implementation guidance from requirements analysis through deployment and administration planning. We also discuss various implementation topics including system architecture design, sizing, scalability, security, performance, and automation.
This book is intended to provide various systems development professionals, Data Solution Architects, Data Administrators, Modelers, Data Analysts, Data Integrators, or anyone who has to analyze or integrate data structures, a broad understanding about IBM InfoSphere Optim Data Growth solutions. By being used in conjunction with the product manuals and online help, this book provides guidance about implementing an optimal solution for managing your enterprise application data.
Table of contents
- Notices
- Preface
- Chapter 1: Introduction to IBM InfoSphere Optim
- Chapter 2: Project planning and considerations
- Chapter 3: Understanding the IBM InfoSphere Optim Data Growth solutions and software
-
Chapter 4: Developing an InfoSphere Optim Data Growth Solution architecture
- Project management
- Analyze
-
Design
- Optim components
- Software components
- Reference deployment models (1/2)
- Reference deployment models (2/2)
- Extensibility of the deployment models (1/5)
- Extensibility of the deployment models (2/5)
- Extensibility of the deployment models (3/5)
- Extensibility of the deployment models (4/5)
- Extensibility of the deployment models (5/5)
- Hardware components (1/3)
- Hardware components (2/3)
- Hardware components (3/3)
- Aligning the solution architecture with the Optim design and planned process flow
- Viability assessment
- Preliminary hardware sizing estimate
- Configure
- Deploy
- Operate
- Sample Optim solution architecture
-
Chapter 5: Sizing the Optim infrastructure
- Resources for the Optim infrastructure
- Types of sizing
- Sizing fundamentals
-
Sizing factors
- Optim installed on Linux, UNIX, and Windows: Data sources
- Optim installed on z/OS: Data source
- Data schema complexity
- How fast can Optim extract the source data
- Hardware sizing considerations (1/3)
- Hardware sizing considerations (2/3)
- Hardware sizing considerations (3/3)
- Align the hardware resource sizing with the deployment model
- Optim design and workflow considerations
- Sizing metrics, methodology, and process
- Sizing example
-
Chapter 6: Data sources
- Data source architecture
- Native data sources
- Federated data sources
- Non-relational data sources
-
IBM InfoSphere Classic Federation Server
- Mapping non-relational sources to relational model
- Import Classic references or run a Database Discovery
- Array structures
- Creating views
- Mapping tables and views for redefined data
- Creating indexes
- Generating DDL
- Granting Classic Federation Server privileges
- Accessing IMS data
- Accessing VSAM data
- Accessing sequential data
- Accessing SAG-Adabas data
- Accessing CA-IDMS data
- Accessing CA-Datacom
- Optim Connect (1/2)
- Optim Connect (2/2)
- Chapter 7: Accessing and viewing archived data
-
Chapter 8: Design and configuration
- Design considerations
- A sample federated design
- A sample z/OS design
-
Miscellaneous considerations
- Optim processing reports
- Optim security
- Change management
- Database schema changes
- Optim naming conventions
- Named objects versus local objects
- Using the export and import utility
- Batch processing
- Matching Optim directories and DBMS code pages
- Handling extreme volumes of data
- Complex data selection requirements
- Special data retention requirements
- Chapter 9: Deployment and operational considerations
-
Chapter 10: Optim performance considerations
- Overview
-
Considerations for processing large data volumes
- Using the current release of Optim software
- Optim archive parallel processes
- Selection criteria
- Archive file indexes
- Optim archive file collections
- Optim process performance reports
- Optim relationship index analysis
- Optim archive processing steps
- Optim table traversal options
- Deleting data after archival
- Partitioned database tables
- Restoring data from archive files
- Optim performance parameter settings
- Non-relational files
- Archive file access
- Analyzing performance with Optim Connect
- Chapter 11: Security
- Chapter 12: Troubleshooting
- Appendix A: Data model
- Appendix B: Functions and actions access permissions by roles (1/2)
- Appendix B: Functions and actions access permissions by roles (2/2)
- Related publications
- Back cover
Product information
- Title: Implementing an InfoSphere Optim Data Growth Solution
- Author(s):
- Release date: November 2011
- Publisher(s): IBM Redbooks
- ISBN: None
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