Implementing an InfoSphere Optim Data Growth Solution

Implementing an InfoSphere Optim Data Growth Solution

by Whei-Jen Chen, David Alley, Barbara Brown, Sunil Dravida, Saunnie Dunne, Tom Forlenza, Pamela S Hoffman, Tejinder S Luthra, Rajat Tiwary, Claudio Zancani
Released November 2011
Publisher(s): IBM Redbooks
ISBN: None

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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

  1. Notices
    1. Trademarks
  2. Preface
    1. The team who wrote this book
      1. Acknowledgements
    2. Now you can become a published author, too!
    3. Comments welcome
    4. Stay connected to IBM Redbooks
  3. Chapter 1: Introduction to IBM InfoSphere Optim
    1. Challenges
      1. Data explosion
      2. Current approaches
    2. Information governance
    3. IBM role in information governance
      1. History
      2. IBM approach to data governance
      3. Data governance maturity model
    4. Information lifecycle management
      1. Benefits of implementing the correct ILM strategy
      2. What is data archiving
    5. IBM InfoSphere Optim Data Growth Solution
    6. Education support
      1. IBM Professional Certification
      2. Information Management Software Services
      3. Protect your software investment: Ensure that you renew your Software Subscription and Support
  4. Chapter 2: Project planning and considerations
    1. Project management
      1. Project methodology
      2. Building the project team
      3. Establishing the project goals
    2. Analyze
      1. Identify business drivers
      2. Define requirements
    3. Design
      1. Conceptual design
      2. Logical design
      3. Physical design
    4. Configure
      1. Implementation
      2. Configuration
    5. Deploy
      1. Integration and user acceptance testing
      2. Deploy to production
      3. Validation
    6. Operate
  5. Chapter 3: Understanding the IBM InfoSphere Optim Data Growth solutions and software
    1. Traditional archiving
    2. Optim concepts
      1. The four pillars of Optim-managed data
    3. Enterprise architecture
      1. Process architecture
      2. Analyze
      3. Design
      4. Deploy and manage
      5. Source
      6. Execute (1/2)
      7. Execute (2/2)
      8. Target
      9. Provide user access (1/2)
      10. Provide user access (2/2)
      11. Storage policy
      12. Security
    4. Complete business object
      1. Elements of a complete business object (1/2)
      2. Elements of a complete business object (2/2)
      3. Data-driven processing examples
    5. Extract, store, and restore processing
    6. Universal access
  6. Chapter 4: Developing an InfoSphere Optim Data Growth Solution architecture
    1. Project management
      1. Business goals
      2. Project scope
      3. Project schedule and phasing
      4. Methodology
    2. Analyze
      1. Requirements
      2. Inventory of assets and technologies
      3. Standards
      4. Use case models
    3. Design
      1. Optim components
      2. Software components
      3. Reference deployment models (1/2)
      4. Reference deployment models (2/2)
      5. Extensibility of the deployment models (1/5)
      6. Extensibility of the deployment models (2/5)
      7. Extensibility of the deployment models (3/5)
      8. Extensibility of the deployment models (4/5)
      9. Extensibility of the deployment models (5/5)
      10. Hardware components (1/3)
      11. Hardware components (2/3)
      12. Hardware components (3/3)
      13. Aligning the solution architecture with the Optim design and planned process flow
      14. Viability assessment
      15. Preliminary hardware sizing estimate
    4. Configure
      1. Installing and configuring Optim
      2. Testing, measuring, tuning, and validating
      3. Hardware sizing
      4. Modifications as necessary
    5. Deploy
      1. Architecting for future phases
    6. Operate
      1. Review project success criteria
    7. Sample Optim solution architecture
      1. Large Optim deployment
  7. Chapter 5: Sizing the Optim infrastructure
    1. Resources for the Optim infrastructure
    2. Types of sizing
    3. Sizing fundamentals
    4. Sizing factors
      1. Optim installed on Linux, UNIX, and Windows: Data sources
      2. Optim installed on z/OS: Data source
      3. Data schema complexity
      4. How fast can Optim extract the source data
      5. Hardware sizing considerations (1/3)
      6. Hardware sizing considerations (2/3)
      7. Hardware sizing considerations (3/3)
      8. Align the hardware resource sizing with the deployment model
      9. Optim design and workflow considerations
    5. Sizing metrics, methodology, and process
    6. Sizing example
      1. Sample large, operationally optimized Optim deployment
      2. Sizing considerations
  8. Chapter 6: Data sources
    1. Data source architecture
      1. Access definition
      2. Data-driven engine
      3. Example (1/2)
      4. Example (2/2)
      5. Data-driven engine (1/3)
      6. Data-driven engine (2/3)
      7. Data-driven engine (3/3)
      8. DB alias
    2. Native data sources
      1. Configuration
      2. Multiple language considerations
    3. Federated data sources
      1. Architecture
      2. Using Federation Server
      3. Using Oracle (1/2)
      4. Using Oracle (2/2)
      5. Configuring Optim Connect ODBC parameters
      6. Optim Connect XML binding parameters
    4. Non-relational data sources
    5. IBM InfoSphere Classic Federation Server
      1. Mapping non-relational sources to relational model
      2. Import Classic references or run a Database Discovery
      3. Array structures
      4. Creating views
      5. Mapping tables and views for redefined data
      6. Creating indexes
      7. Generating DDL
      8. Granting Classic Federation Server privileges
      9. Accessing IMS data
      10. Accessing VSAM data
      11. Accessing sequential data
      12. Accessing SAG-Adabas data
      13. Accessing CA-IDMS data
      14. Accessing CA-Datacom
    6. Optim Connect (1/2)
    7. Optim Connect (2/2)
      1. Setup procedure (1/2)
      2. Setup procedure (2/2)
      3. Managing metadata (1/4)
      4. Managing metadata (2/4)
      5. Managing metadata (3/4)
      6. Managing metadata (4/4)
  9. Chapter 7: Accessing and viewing archived data
    1. Business requirements for accessing archived data
      1. Ad hoc viewing
      2. Reporting
      3. Federated viewing
      4. Optim Data Find
      5. Native application access
      6. Other viewing from within an application
    2. Managing access to archived data
      1. Open data manager
      2. ODBC drivers for Optim solutions on Microsoft Windows
    3. Performance considerations
      1. Searching archives
  10. Chapter 8: Design and configuration
    1. Design considerations
      1. Archiving strategy
      2. Selecting what data to archive
      3. Restoring archived data
      4. Making the final design decision
    2. A sample federated design
      1. Sample business requirements
      2. Sample design
    3. A sample z/OS design
      1. Sample design
    4. Miscellaneous considerations
      1. Optim processing reports
      2. Optim security
      3. Change management
      4. Database schema changes
      5. Optim naming conventions
      6. Named objects versus local objects
      7. Using the export and import utility
      8. Batch processing
      9. Matching Optim directories and DBMS code pages
      10. Handling extreme volumes of data
      11. Complex data selection requirements
      12. Special data retention requirements
  11. Chapter 9: Deployment and operational considerations
    1. Data source and operational design
    2. Single or multi-instance Optim deployment
      1. Multi-instance deployment
    3. Archival job configuration
    4. Restore job configuration
    5. Control tables
      1. Archival job control table
      2. Restoration job control table
    6. Archival job execution
    7. Restoration job execution
      1. Selective restore
      2. Bulk restore
    8. Auditing
    9. Monitoring
    10. Reporting
    11. Tiering
    12. Restarting Optim jobs
    13. Backup and disaster recovery
  12. Chapter 10: Optim performance considerations
    1. Overview
    2. Considerations for processing large data volumes
      1. Using the current release of Optim software
      2. Optim archive parallel processes
      3. Selection criteria
      4. Archive file indexes
      5. Optim archive file collections
      6. Optim process performance reports
      7. Optim relationship index analysis
      8. Optim archive processing steps
      9. Optim table traversal options
      10. Deleting data after archival
      11. Partitioned database tables
      12. Restoring data from archive files
      13. Optim performance parameter settings
    3. Non-relational files
      1. General performance guidelines
      2. Processing non-indexed file types
      3. Trace and log settings
      4. Performance parameter settings
    4. Archive file access
      1. General performance guidelines
      2. Archive file indexes
      3. Archive file collections
      4. Optim Connect performance parameter settings
    5. Analyzing performance with Optim Connect
      1. Using the Optim Connect explain command
  13. Chapter 11: Security
    1. Basic access security model
    2. Optim security architecture
      1. Definitions
      2. Standards matrix
      3. Access flow
    3. Authentication and access
      1. Account management
      2. Functional security
      3. Object security
      4. File access definitions
      5. Database security
    4. Accessing archived data with open data manager
      1. Prerequisites
      2. Open data manager security methods
      3. Open data manager federation configuration
      4. Implementing open data manager workspace security
      5. Open data manager and file access definitions (1/2)
      6. Open data manager and file access definitions (2/2)
      7. Open data manager and FAD example UNIX configuration
    5. Software
      1. Program executables and libraries
      2. Archive, extract, and control files
      3. Logging, trace, and other temporary files
      4. Database objects
    6. Audit trail
      1. Optim
    7. z/OS
    8. Implementation practices for Linux, UNIX, and Microsoft Windows environments
      1. Initializing Optim security
      2. Securing your Optim implementation
      3. Activity classes
      4. Roles
      5. Configuration management
  14. Chapter 12: Troubleshooting
    1. IBM Support
    2. Troubleshooting aids
      1. Environmental information
      2. Optim processes
      3. Tracing (1/2)
      4. Tracing (2/2)
    3. Issues getting data out of sources
      1. Troubleshooting your Optim server
      2. Cannot get to the source data
      3. Poor archive process performance
      4. Deleting data from sources
    4. Issues accessing data after it has been archived
      1. Open data manager
      2. Security
      3. Poor query performance on archived data
    5. Recovery
      1. Optim objects
      2. Accessing a duplicate copy of archive files
  15. Appendix A: Data model
    1. Business event processing
      1. Reference data
      2. Master data
      3. Transaction data
    2. Order management system
      1. Ordering products
      2. Order transactions
      3. Invoice transactions
      4. Items master data table
      5. Customer
      6. Shipments
    3. Optim data model explained
      1. Logical data model
      2. Optim sales table
      3. Optim customers table
      4. Optim orders table
      5. Optim details table
      6. Optim items table
      7. Optim_Ship_To table
      8. Optim_Ship_Instr table
      9. Optim_Male_Rates table
      10. Optim_Female_Rates table
      11. Optim_State_Lookup table
  16. Appendix B: Functions and actions access permissions by roles (1/2)
  17. Appendix B: Functions and actions access permissions by roles (2/2)
  18. Related publications
    1. IBM Redbooks
    2. Other publications
    3. Online resources
    4. Help from IBM
  19. Back cover

Product information

  • Title: Implementing an InfoSphere Optim Data Growth Solution
  • Author(s): Whei-Jen Chen, David Alley, Barbara Brown, Sunil Dravida, Saunnie Dunne, Tom Forlenza, Pamela S Hoffman, Tejinder S Luthra, Rajat Tiwary, Claudio Zancani
  • Release date: November 2011
  • Publisher(s): IBM Redbooks
  • ISBN: None