Front cover IBM® Information Management Software Implementing an InfoSphere Optim Data Growth Solution Understanding the InfoSphere Optim Data Growth solution architectures Implementing InfoSphere Optim Data Growth solutions Managing data growth with flexibility Whei-Jen Chen David Alley Barbara Brown Sunil Dravida Saunnie Dunne Tom Forlenza Pamela S Hoffman Tejinder S Luthra Rajat Tiwary Claudio Zancani ibm.com/redbooks International Technical Support Organization Implementing an InfoSphere Optim Data Growth Solution November 2011 SG24-7936-00 Note: Before using this information and the product it supports, read the information in “Notices” on page xi. First Edition (November 2011) This edition applies to IBM InfoSphere Optim Data Growth Solution Version 7.3.1. © Copyright International Business Machines Corporation 2011. All rights reserved. Note to U.S. Government Users Restricted Rights -- Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Notices . xi Trademarks . xii Preface . xiii The team who wrote this book . xiii Acknowledgements . xvi Now you can become a published author, too! . xvii Comments welcome. xvii Stay connected to IBM Redbooks . xviii Chapter 1. Introduction to IBM InfoSphere Optim . 1 1.1 Challenges . 2 1.1.1 Data explosion . 2 1.1.2 Current approaches . 3 1.2 Information governance. 3 1.3 IBM role in information governance. 4 1.3.1 History . 4 1.3.2 IBM approach to data governance . 5 1.3.3 Data governance maturity model . 7 1.4 Information lifecycle management. 8 1.4.1 Benefits of implementing the correct ILM strategy . 11 1.4.2 What is data archiving. 11 1.5 IBM InfoSphere Optim Data Growth Solution . 12 1.6 Education support . 13 1.6.1 IBM Professional Certification . 14 1.6.2 Information Management Software Services . 15 1.6.3 Protect your software investment: Ensure that you renew your Software Subscription and Support . 16 Chapter 2. Project planning and considerations . 17 2.1 Project management . 18 2.1.1 Project methodology . 18 2.1.2 Building the project team. 18 2.1.3 Establishing the project goals . 21 2.2 Analyze . 21 2.2.1 Identify business drivers . 21 2.2.2 Define requirements . 23 2.3 Design . 24 2.3.1 Conceptual design . 25 © Copyright IBM Corp. 2011. All rights reserved. iii 2.3.2 Logical design . 25 2.3.3 Physical design . 28 2.4 Configure. 29 2.4.1 Implementation . 29 2.4.2 Configuration. 30 2.5 Deploy . 31 2.5.1 Integration and user acceptance testing . 31 2.5.2 Deploy to production . 31 2.5.3 Validation . 32 2.6 Operate . 32 Chapter 3. Understanding the IBM InfoSphere Optim Data Growth solutions and software . 33 3.1 Traditional archiving . 34 3.2 Optim concepts . 38 3.2.1 The four pillars of Optim-managed data . 42 3.3 Enterprise architecture . 42 3.3.1 Process architecture . 44 3.3.2 Analyze . 45 3.3.3 Design . 46 3.3.4 Deploy and manage . 49 3.3.5 Source. 50 3.3.6 Execute . 52 3.3.7 Target . 62 3.3.8 Provide user access . 64 3.3.9 Storage policy . 71 3.3.10 Security . 73 3.4 Complete business object . 74 3.4.1 Elements of a complete business object. 76 3.4.2 Data-driven processing examples. 82 3.5 Extract, store, and restore processing. 85 3.6 Universal access . 90 Chapter 4. Developing an InfoSphere Optim Data Growth Solution architecture . 93 4.1 Project management . 96 4.1.1 Business goals . 96 4.1.2 Project scope . 96 4.1.3 Project schedule and phasing . 97 4.1.4 Methodology . 98 4.2 Analyze . 99 4.2.1 Requirements . 99 4.2.2 Inventory of assets and technologies . 104 iv Implementing an InfoSphere Optim Data Growth Solution 4.2.3 Standards . 105 4.2.4 Use case models. 106 4.3 Design . 107 4.3.1 Optim components . 107 4.3.2 Software components . 115 4.3.3 Reference deployment models . 117 4.3.4 Extensibility of the deployment models . ..