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Solving Operational Business Intelligence with InfoSphere Warehouse Advanced Edition

Book Description

IBM® InfoSphere® Warehouse is the IBM flagship data warehouse platform for departmental data marts and enterprise data warehouses. It offers leading architecture, performance, backup, and recovery tools that help improve efficiency and reduce time to market through increased understanding of current data assets, while simplifying the daily operations of managing complex warehouse deployments.

InfoSphere Warehouse Advanced Enterprise Edition delivers an enhanced set of database performance, management, and design tools. These tools assist companies in maintaining and increasing value from their warehouses, while helping to reduce the total cost of maintaining these complex environments.

In this IBM Redbooks® publication we explain how you can build a business intelligence system with InfoSphere Warehouse Advanced Enterprise to manage and support daily business operations for an enterprise, to generate more income with lower cost. We describe the foundation of the business analytics, the Data Warehouse features and functions, and the solutions that can deliver immediate analytics solutions and help you drive better business outcomes.

We show you how to use the advanced analytics of InfoSphere Warehouse Advanced Enterprise Edition and integrated tools for data modeling, mining, text analytics, and identifying and meeting the data latency requirements. We describe how the performance and storage optimization features can make building and managing a large data warehouse more affordable, and how they can help significantly reduce the cost of ownership. We also cover data lifecycle management and the key features of IBM Cognos® Business Intelligence.

This book is intended for data warehouse professionals who are interested in gaining in-depth knowledge about the operational business intelligence solution for a data warehouse that the IBM InfoSphere Warehouse Advanced Enterprise Edition offers.

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: Solving complex operational warehouse challenges
    1. Current business challenges
      1. Understand data and the complex warehouse environment
      2. Deliver actionable business insights - when and where needed
      3. Challenges for complex warehouse environments
      4. Gain insight without boundaries with IBM InfoSphere Warehouse
    2. Comprehensive data warehouse solution
    3. InfoSphere Warehouse advanced tooling
  4. Chapter 2: Overview of InfoSphere Warehouse Advanced Edition
    1. InfoSphere Advanced Enterprise Edition components
      1. DB2 10 Enterprise Server Edition
      2. WebSphere Application Server
      3. InfoSphere Warehouse Server
      4. InfoSphere Federation Server
      5. InfoSphere Replication Server
      6. Advanced access control
      7. IBM Cognos Business Intelligence for Reporting
      8. IBM Data Studio
      9. Optim Database Administrator
      10. Optim Development Studio
      11. InfoSphere Warehouse Client - IBM Design Studio and the wh command
      12. InfoSphere Data Architect
      13. InfoSphere Optim Query Workload Tuner
      14. InfoSphere Optim Performance Manager Extended Edition
      15. InfoSphere Optim High Performance Unload
      16. InfoSphere Optim Configuration Manager
      17. DB2 Recovery Expert
      18. DB2 Merge Backup
      19. InfoSphere Warehouse Packs
    2. InfoSphere Warehouse technical overview
      1. InfoSphere Warehouse core architecture
      2. Overview of IBM Cognos Business Intelligence
      3. Architectural overview of the Optim family of tools
      4. InfoSphere Replication Server simplified overview
      5. InfoSphere Warehouse Advanced Edition client applications
      6. InfoSphere Warehouse Advanced Edition command-line tools and utilities
    3. InfoSphere Warehouse implementation scenarios
      1. Scenarios for implementing InfoSphere Warehouse core products
      2. Scenarios for implementing the Optim family of tools
      3. Alternative IBM solutions for data warehousing
  5. Chapter 3: Scenario: Warehouse Live Demo Set
    1. The problem: warehouse growth for “Mom and Pop” retail
    2. Warehouse Live! Demo
    3. Example architecture used in this book
  6. Chapter 4: Data modeling: End to end
    1. Start with the business problem
      1. Online analytical processing
    2. The logical modeling process
      1. Identify the business process
      2. Define the granularity
      3. Identify the dimension tables
      4. Identify the fact tables
    3. InfoSphere Data Architect and logical dimensional modeling
      1. A starting point: The physical data model
      2. Create a logical data model
      3. Add dimensional notation to the logical data model
      4. Create a dimensional physical data model to implement OLAP Data Warehouse
    4. OLAP modeling and cubes
      1. Cube model dimensional concepts
      2. Define a cube model within Design Studio
      3. Deploy a cube model to InfoSphere Warehouse as a cube service
    5. Modeling and IBM Cognos BI
      1. Cognos Framework Manager
      2. Create a Cognos model from cubing services
      3. Create a Cognos model from a logical dimensional model within Data Architect
    6. Introduction to InfoSphere Warehouse Packs
      1. Installation example of InfoSphere Warehouse Insight Pack
  7. Chapter 5: Temporal data management and analytics in an operational warehouse
    1. Temporal data management concepts and use cases
      1. Temporal use cases for the operational data warehouse
      2. Temporal concepts
    2. Temporal data management in InfoSphere Warehouse Advanced Enterprise Edition 10
      1. Temporal data management with system time
      2. System-period temporal tables
      3. Temporal data management with business time
      4. Application-period temporal tables
      5. Bitemporal tables
      6. Views and temporal tables
      7. Register settings for temporal tables
    3. Implications of temporal tables on operational warehousing
      1. Temporal tables, complex workloads and concurrency
      2. System-period temporal tables and history table storage
      3. History table implications for the warehouse archive strategy
      4. Backup, recovery, and pruning history with range partitioning
  8. Chapter 6: Managing complex query workloads in an operational warehouse environment
    1. Get started with Optim Performance Manager in your environment
      1. Creating a database connection
      2. Configuring database monitoring settings
    2. Optim Performance Manager in a partitioned database environment
      1. Collecting large volumes of performance metrics
    3. Using Optim Performance Manager to implement a Stage1 configuration of DB2 WLM
      1. Sample scenario using DB2 WLM and Optim Performance Manager to manage performance
    4. Understanding query workloads in your environment
      1. Identify/define query workloads with Optim Performance Manager
      2. Create/monitor new workloads with Optim Performance Manager
      3. Define service level objectives for all query workloads
    5. Improving the overall performance of an activity
    6. Approaches to workload tuning
      1. Tuning a workload for optimal performance
    7. Monitoring query workloads: Real-time operational to show the state and health of the system
      1. Health monitoring
      2. Performance baselines
  9. Chapter 7: Understand and address data latency requirements
    1. Understand your data latency requirements
      1. Quantify your service level objectives
      2. Calculate the data ingest rate
      3. Analyze your ETL scenarios
    2. Design and develop your ETL application
    3. Use SQW and Bulk Load to get batch data into staging tables
      1. SQW data flow
      2. SQW control flow
      3. SQW and temporal tables
    4. Create and deploy your SQW application
    5. Introduce parallelism to increase ingest volumes
      1. How Ingest and MQT tables correlate with data availability and data latency
  10. Chapter 8: Building a corporate backup and recovery strategy
    1. Advanced features for backup and recovery
      1. Advanced recovery solutions explained
    2. Plan a backup and recovery strategy
      1. Recovery scenarios and objectives
      2. ETL application architecture and process schedule
      3. Backup infrastructure
      4. Data needs of downstream systems
    3. Implement a backup and recovery strategy
    4. Implementing Optim High Performance Unload as part of your recovery strategy
      1. Optim High Performance Unload with backup images
      2. Optim High Performance Unload with backup images usage
      3. Optim High Performance Unload in a production environment
      4. Optim High Performance Unload with named pipes or output files
      5. Optim High Performance Unload control files
      6. Create the control file and issue a db2hpu command
      7. Install and configure Optim High Performance Unload
    5. Example recovery scenarios using Optim High Performance Unload
      1. Recover existing partitioned tables using backup images on disk
      2. Recover dropped partitioned table using backup images on TSM and named pipes
      3. Recover data using non-production database and backup images on TSM
    6. DB2 Recovery Expert as part of your recovery strategy
      1. Schema level repository
      2. Log analysis
      3. Recovery
    7. DB2 Merge Backup as part of your backup strategy
      1. DB2 Merge Backup as part of your infrastructure
      2. Install and configure db2mk in partitioned database environment
      3. DB2 Merge Backup command line and control files
      4. DB2 Merge Backup with local disk backups
      5. DB2 Merge Backup with Tivoli Storage Manager
  11. Chapter 9: Managing data lifecyle with InfoSphere Warehouse
    1. The value of data and its age
    2. Manage the cost of storage with multi-temperature management
      1. Using multi-temperatures features in a sample scenario
    3. Aging data
      1. How active is the data
    4. Optim High Performance Unload to archive or migrate cold data
      1. Archive cold data
      2. Migrate data from production to an alternate database
  12. Chapter 10: Techniques for data mining in an operational warehouse
    1. Data mining in an operational warehouse environment
      1. Data mining overview
      2. Data mining scenarios in an operational data warehousing environment
    2. InfoSphere Warehouse Advanced Enterprise Edition 10.1 tools and features for data mining
      1. Source data exploration in InfoSphere Warehouse 10.1
      2. Data preparation
      3. Data mining modeling in InfoSphere Warehouse Design Studio
      4. Performing data mining scoring with other data mining models through PMML
    3. Extended data mining techniques using SAS Enterprise Miner
      1. About SAS Enterprise Miner
      2. In-database scoring with SAS and InfoSphere Warehouse
      3. Access the scoring model
      4. Additional scoring examples
    4. Deploy and visualize mining results with IBM Cognos 10 Business Intelligence
      1. List of clusters report
      2. Breakdown by cluster report
  13. Chapter 11: Cognos Business Intelligence for InfoSphere Warehouse
    1. Cognos Business Intelligence 10 and InfoSphere Warehouse
      1. IBM Cognos 10 Business Intelligence features
      2. IBM Cognos 10 Business Intelligence architecture
    2. Business modeling with IBM Cognos Framework Manager
    3. IBM Cognos Business Insight
      1. Interact with IBM Cognos Business Insight Editor
      2. Run the IBM Cognos Business Insight dashboard
    4. IBM Cognos disconnected report interaction
      1. IBM Cognos Active Report overview
      2. IBM Cognos Active Report features
      3. Enable an existing report for active reporting
    5. IBM Cognos access from mobile devices
    6. Further information
  14. Chapter 12: InfoSphere Warehouse resilience with Optim Configuration Manager
    1. Challenges to maintaining an operational warehouse
    2. InfoSphere Optim Configuration Manager
    3. Integration of the Optim family of tools
    4. Monitor a DB2 database configuration
    5. Optim tools runtime client
    6. Optimize database storage with Optim Configuration Manager
      1. Example Optim Configuration Manager storage-saving job
      2. Automate multi-temperature storage migration with Optim Configuration Manager
    7. InfoSphere Warehouse high availability with Q replication and Optim Configuration Manager
  15. Appendix A: InfoSphere Warehouse Editions comparison
  16. Related publications
    1. IBM Redbooks
    2. Other publications
    3. Online resources
    4. Help from IBM
  17. Back cover