You are previewing Building 360-Degree Information Applications.
O'Reilly logo
Building 360-Degree Information Applications

Book Description

Today's businesses, applications, social media, and online transactions generate more data than ever before. This data can be explored and analyzed to provide tremendous business value. IBM® Watson™ Explorer and IBM InfoSphere® Master Data Management (InfoSphere MDM) enable organizations to simultaneously explore and derive insights from enterprise data that was traditionally stored in "silos" in enterprise applications, different data repositories, and in different data formats.

This IBM Redbooks® publication provides information about Watson Explorer 9.0, InfoSphere MDM, and IBM InfoSphere MDM Probabilistic Matching Engine for InfoSphere BigInsights™ (PME for BigInsights). It gives you an overview, describes the architecture, and presents use cases that you can use to accomplish the following tasks:

  • Understand the core capabilities of Watson Explorer, InfoSphere MDM, and PME for BigInsights.

  • Realize the full potential of Watson Explorer applications.

  • Describe the integration and value of the combination of Watson Explorer and InfoSphere MDM.

  • Build a 360-degree information application.

  • Learn by example by following hands-on lab scenarios.
    [/ul>]

  • Table of Contents

    1. Front cover
    2. Notices
      1. Trademarks
    3. Preface
      1. Authors
      2. Now you can become a published author, too!
      3. Comments welcome
      4. Stay connected to IBM Redbooks
    4. Summary of changes
      1. September 2014, Second Edition
    5. Chapter 1. Introduction to 360-degree information applications
      1. 1.1 Defining a 360-degree information application
      2. 1.2 Business value delivered through 360-degree information applications
      3. 1.3 Benefits of 360-degree information applications
      4. 1.4 Introduction to IBM Watson Explorer
      5. 1.5 Introduction to master data management
        1. 1.5.1 What master data management is
        2. 1.5.2 Integration between InfoSphere MDM and Watson Explorer
    6. Chapter 2. IBM Watson Explorer overview
      1. 2.1 Introduction
      2. 2.2 Watson Explorer architecture
        1. 2.2.1 Connectors and crawling
        2. 2.2.2 Converting and augmenting data for indexing
        3. 2.2.3 Indexing data
        4. 2.2.4 Capitalizing on existing search applications through query routing
        5. 2.2.5 Querying repositories and displaying search results
      3. 2.3 Security in Watson Explorer Engine applications
      4. 2.4 Overview of the Watson Explorer Engine administration tool
      5. 2.5 Watson Explorer Engine requirements
        1. 2.5.1 Watson Explorer Engine server requirements
        2. 2.5.2 Watson Explorer Engine client requirements
      6. 2.6 Application Builder architecture
        1. 2.6.1 Modeling data and data relationships using entities
        2. 2.6.2 Displaying information using pages and widgets
        3. 2.6.3 Overview of the Application Builder administration tool
        4. 2.6.4 Scaling and availability for enterprise applications
      7. 2.7 Application Builder system requirements
        1. 2.7.1 Application Builder server requirements
        2. 2.7.2 Application Builder client requirements
    7. Chapter 3. IBM InfoSphere Master Data Management overview
      1. 3.1 InfoSphere Master Data Management (MDM)
      2. 3.2 IBM InfoSphere MDM Suite of products
        1. 3.2.1 IBM InfoSphere Master Data Management
        2. 3.2.2 InfoSphere MDM Collaboration Server
        3. 3.2.3 InfoSphere MDM Reference Data Management Hub (RDM)
      3. 3.3 InfoSphere MDM general product features
        1. 3.3.1 Matching and linking
        2. 3.3.2 Search
        3. 3.3.3 Security and audit
        4. 3.3.4 Extensibility
        5. 3.3.5 Standardization
        6. 3.3.6 Data load
        7. 3.3.7 Software development kit (SDK)
        8. 3.3.8 Stewardship and governance
        9. 3.3.9 Business process management
        10. 3.3.10 MDM Workbench
      4. 3.4 Architecture overview
        1. 3.4.1 InfoSphere MDM Standard Edition
        2. 3.4.2 InfoSphere MDM Physical/ Advanced Edition architecture
        3. 3.4.3 InfoSphere MDM Collaborative Edition architecture
        4. 3.4.4 InfoSphere MDM Reference Data Management architecture
      5. 3.5 Use cases
        1. 3.5.1 Government
        2. 3.5.2 Financial services
        3. 3.5.3 Healthcare
        4. 3.5.4 Retail
    8. Chapter 4. Planning a 360-degree information application
      1. 4.1 Identifying use cases and users
      2. 4.2 Identifying data sources
      3. 4.3 Modeling entity relationships
        1. 4.3.1 Matching entities with non-identical fields
      4. 4.4 Planning for deployment and implementation
        1. 4.4.1 Example hardware architecture
        2. 4.4.2 Scalability
    9. Chapter 5. Lab scenario overview
      1. 5.1 Key business challenge
      2. 5.2 Identifying use cases and users
      3. 5.3 Identifying the data sources
      4. 5.4 Modeling entity relationships
    10. Chapter 6. Installation and initial configuration
      1. 6.1 Watson Explorer installation and configuration
      2. 6.2 InfoSphere MDM installation
      3. 6.3 InfoSphere MDM Connector installation and configuration
        1. 6.3.1 InfoSphere MDM Standard Edition connector
    11. Chapter 7. Building a golden record
      1. 7.1 Overview
      2. 7.2 MDM implementation styles
        1. 7.2.1 Virtual
        2. 7.2.2 Physical
        3. 7.2.3 Hybrid
      3. 7.3 Sample process for building a virtual record
        1. 7.3.1 Three stages to construct and manage a golden record
        2. 7.3.2 Workflow for arriving at a golden view
    12. Chapter 8. Preparing data for IBM Watson Explorer Application Builder
      1. 8.1 Creating the search collections
      2. 8.2 Configuring the search collections and crawling the data
        1. 8.2.1 Configuring collection seeds
        2. 8.2.2 Testing the crawling and conversion processes
        3. 8.2.3 Adding a converter
        4. 8.2.4 Final search collection configuration
        5. 8.2.5 Crawling the data
      3. 8.3 Optional: Scheduling a refresh
    13. Chapter 9. Creating an application with Application Builder
      1. 9.1 Defining entities
        1. 9.1.1 Logging in
        2. 9.1.2 Connecting the engine
        3. 9.1.3 Creating an entity
        4. 9.1.4 Viewing entities
      2. 9.2 Enhancing an entity page
        1. 9.2.1 Enhancing an entity information widget
        2. 9.2.2 Adding an order-detail entity
        3. 9.2.3 Associating products with order details
        4. 9.2.4 Formatting order details
        5. 9.2.5 Sorting orders by ship date
        6. 9.2.6 Creating a chart widget for top purchases
      3. 9.3 Searching entities
        1. 9.3.1 Making an entity searchable
        2. 9.3.2 Enhancing your search display
        3. 9.3.3 Adding search refinements
      4. 9.4 Conclusion
    14. Chapter 10. IBM InfoSphere MDM Probabilistic Matching Engine for InfoSphere BigInsights
      1. 10.1 Introduction
      2. 10.2 Use cases
        1. 10.2.1 Probabilistic search
        2. 10.2.2 360-degree view
      3. 10.3 PME for BigInsights architecture
      4. 10.4 Installation
        1. 10.4.1 Prerequisites
        2. 10.4.2 Installing PME for BigInsights
      5. 10.5 Lab scenario
        1. 10.5.1 Business challenge
        2. 10.5.2 Data sources
        3. 10.5.3 MDM algorithm
      6. 10.6 Configuration
        1. 10.6.1 Site
        2. 10.6.2 Algorithm
        3. 10.6.3 Table
        4. 10.6.4 Dashboard
      7. 10.7 Derivation, comparison, and linking
        1. 10.7.1 Uploading the data
        2. 10.7.2 Importing the data
        3. 10.7.3 Verifying the import
        4. 10.7.4 Verifying derivation
        5. 10.7.5 Verifying comparison
        6. 10.7.6 Verifying linking
      8. 10.8 Probabilistic search
        1. 10.8.1 Dashboard
        2. 10.8.2 PME Search
      9. 10.9 360-degree view
        1. 10.9.1 PME Extract
        2. 10.9.2 Composite filters
    15. Appendix A. Additional material
      1. Locating the Web material
      2. Using the Web material
    16. Related publications
      1. Online resources
      2. Help from IBM
    17. Back cover
    18. IBM System x Reference Architecture for Hadoop: IBM InfoSphere BigInsights Reference Architecture
      1. Introduction
      2. Business problem and business value
      3. Reference architecture use
      4. Requirements
      5. InfoSphere BigInsights predefined configuration
      6. InfoSphere BigInsights HBase predefined configuration
      7. Deployment considerations
      8. Customizing the predefined configurations
      9. Predefined configuration bill of materials
      10. References
      11. The team who wrote this paper
      12. Now you can become a published author, too!
      13. Stay connected to IBM Redbooks
    19. Notices
      1. Trademarks