Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications [NOOK Book]

Overview

"If you are looking for a complete treatment of business intelligence, then go no further than this book. Larissa T. Moss and Shaku Atre have covered all the bases in a cohesive and logical order, making it easy for the reader to follow their line of thought. From early design to ETL to physical database design, the book ties together all the components of business intelligence."
--Bill Inmon, Inmon Enterprises

This is the eBook version of the print title. The eBook edition contains the same content as the print ...

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Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications

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Overview

"If you are looking for a complete treatment of business intelligence, then go no further than this book. Larissa T. Moss and Shaku Atre have covered all the bases in a cohesive and logical order, making it easy for the reader to follow their line of thought. From early design to ETL to physical database design, the book ties together all the components of business intelligence."
--Bill Inmon, Inmon Enterprises

This is the eBook version of the print title. The eBook edition contains the same content as the print edition. You will find instructions in the last few pages of your eBook that directs you to the media files.

Business Intelligence Roadmap is a visual guide to developing an effective business intelligence (BI) decision-support application. This book outlines a methodology that takes into account the complexity of developing applications in an integrated BI environment. The authors walk readers through every step of the process--from strategic planning to the selection of new technologies and the evaluation of application releases. The book also serves as a single-source guide to the best practices of BI projects.

Part I steers readers through the six stages of a BI project: justification, planning, business analysis, design, construction, and deployment. Each chapter describes one of sixteen development steps and the major activities, deliverables, roles, and responsibilities. All technical material is clearly expressed in tables, graphs, and diagrams.

Part II provides five matrices that serve as references for the development process charted in Part I. Management tools, such as graphs illustrating the timing and coordination of activities, are included throughout the book. The authors conclude by crystallizing their many years of experience in a list of dos, don'ts, tips, and rules of thumb.

Both the book and the methodology it describes are designed to adapt to the specific needs of individual stakeholders and organizations. The book directs business representatives, business sponsors, project managers, and technicians to the chapters that address their distinct responsibilities. The framework of the book allows organizations to begin at any step and enables projects to be scheduled and managed in a variety of ways.

Business Intelligence Roadmap is a clear and comprehensive guide to negotiating the complexities inherent in the development of valuable business intelligence decision-support applications.

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Product Details

  • ISBN-13: 9780321630117
  • Publisher: Pearson Education
  • Publication date: 3/11/2003
  • Series: Addison-Wesley Information Technology Series
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • Pages: 576
  • Sales rank: 1,212,374
  • File size: 11 MB
  • Note: This product may take a few minutes to download.

Meet the Author

Larissa Moss is founder and president of Method Focus, Inc., a consulting firm specializing in business intelligence and data warehousing. She is a frequent lecturer and speaker at conferences in the United States, Europe, and Asia on data warehousing, project management, development methodologies, and organizational and cultural issues. Her articles on these topics are regularly published in magazines such as DM Review and Journal of Data Warehousing. She is coauthor of Data Warehouse Project Management (Addison-Wesley, 2000) and Impossible Data Warehouse Situations (Addison-Wesley, 2003). She is a senior consultant at the Cutter Consortium and one of the authors of their Business Intelligence Executive Reports.

Shaku Atre is president of Atre Group, Inc., a Santa Cruz, CA based consulting organization specializing in business intelligence and data warehousing implementations. She is also the president of Atre Associates, Inc., a systems integration company based in New York City. Previously, she was a partner with PricewaterhouseCoopers, held a variety of management and staff positions at IBM, and served as a faculty member of IBM's prestigious Systems Research Institute. She has authored hundreds of articles as a columnist for Information Week, Computerworld, eWeek and a number of other publications. She is the author of five books including Data Base: Structured Techniques for Design, Performance, and Management, Second Edition (John Wiley & Sons, 1988) and Distributed Databases, Cooperative Processing, and Networking (McGraw-Hill, 1992).

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Table of Contents

About the Authors.


Foreword.


Preface.

The Purpose of This Book.

Complexity.

Step-by-Step Guide.

How This Book Is Organized.

Part I: Stages and Steps.

Part II: At a Glance.

How to Use This Book.

Who Should Read This Book.

Business Representatives.

Business Sponsors.

Project Managers.

Technicians.

Comments.

I. STAGES AND STEPS.

0. Guide to the Development Steps.

Business Intelligence Definition.

BI Decision-Support Initiatives.

Development Approaches.

The Traditional Development Approach.

The Cross-Organizational Development Approach.

Engineering Stages and the Development Steps.

Parallel Development Tracks.

BI Project Team Structure.

The Core Team.

The Extended Team.

The BI Arbitration Board.

Justification for Using This Project Lifecycle Guide.

Bibliography and Additional Reading.

1. Step 1: Business Case Assessment.

Business Justification.

Business Drivers.

Business Analysis Issues.

Information Needs.

Types of Data Sources.

Source Data Quality.

Cost-Benefit Analysis.

Risk Assessment.

Business Case Assessment Activities.

Deliverable Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step.

Bibliography and Additional Reading.

2. Step 2: Enterprise Infrastructure Evaluation.
Step 2, Section A: Technical Infrastructure Evaluation.

The Hardware Platform.

Controlled Chaos.

Hardware Platform Requirements.

The Middleware Platform.

DBMS Gateways.

The DBMS Platform.

Criteria for Selecting a DBMS.

Technical Infrastructure Evaluation Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 2, Section A.

Step 2, Section B: Nontechnical Infrastructure Evaluation.

The Effects of Stovepipe Development.

The Need for Nontechnical Infrastructure.

Enterprise Architecture.

Enterprise Standards.

Nontechnical Infrastructure Evaluation Activities.

Deliverable Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 2, Section B.

Bibliography and Additional Reading.

Technical Infrastructure Evaluation.

Nontechnical Infrastructure Evaluation.

3. Step 3: Project Planning.

Managing the BI Project.

Defining the BI Project.

Project Goals and Objectives.

Project Scope.

Project Risks.

Project Constraints.

Assumptions.

Change-Control Procedures.

Issues Management Procedures.

Planning the BI Project.

Activities and Tasks.

Estimating Techniques.

Resource Assignment.

Task Dependencies.

Resource Dependencies.

Critical Path Method.

Project Schedules.

Project Planning Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 3.

Bibliography and Additional Reading.

4. Step 4: Project Requirements Definition.

General Business Requirements.

Interviewees for General Business Requirements.

Data Quality Requirements.

Business Requirements Report .

Project-Specific Requirements.

Interviewees for Project-Specific Requirements.

Application Requirements Document.

The Interviewing Process.

Interviewing Considerations.

Interviewing Tips.

Project Requirements Definition Activities.

Deliverable Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 4.

Bibliography and Additional Reading.

5. Step 5: Data Analysis.

Business-Focused Data Analysis.

Top-Down Logical Data Modeling.

Project-Specific Logical Data Model.

Enterprise Logical Data Model.

Logical Data Modeling Participants.

Standardized Business Meta Data.

Bottom-Up Source Data Analysis.

Technical Data Conversion Rules.

Business Data Domain Rules.

Business Data Integrity Rules.

Data Cleansing.

Data Quality Responsibility.

Source Data Selection Process.

Key Points of Data Selection.

To Cleanse or Not to Cleanse.

Cleansing Operational Systems.

Data Analysis Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 5.

Bibliography and Additional Reading.

6. Step 6: Application Prototyping.

Purposes of Prototyping.

Time-Boxing.

Best Practices for Prototyping.

Considerations for Prototyping.

Types of Prototypes.

Show-and-Tell Prototype.

Mock-Up Prototype.

Proof-of-Concept Prototype.

Visual-Design Prototype.

Demo Prototype.

Operational Prototype.

Building Successful Prototypes.

Prototype Charter.

Guidelines for Prototyping.

Skills Survey.

Application Prototyping Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 6.

Bibliography and Additional Reading.

7. Step 7: Meta Data Repository Analysis.

The Importance of Meta Data.

Meta Data Categories.

Meta Data Repository as Navigation Tool.

Data Standardization.

Meta Data Classifications.

Groupings of Meta Data Components.

Prioritization of Meta Data Components.

Meta Data Repository Challenges.

Technical Challenges.

Staffing Challenges.

Budget Challenges.

Usability Challenges.

Political Challenges.

The Logical Meta Model.

The Entity-Relationship Meta Model.

Meta-Meta Data.

Meta Data Repository Analysis Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 7.

Bibliography and Additional Reading.

8. Step 8: Database Design.

Differences in Database Design Philosophies.

Operational Databases.

BI Target Databases.

Logical Database Design.

The Star Schema.

The Snowflake Schema.

Physical Database Design.

Implementation Options.

Physical Dataset Placement.

Partitioning.

Clustering.

Indexing.

Reorganizations.

Backup and Recovery.

Parallel Query Execution.

Database Design Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 8.

Bibliography and Additional Reading.

9. Step 9: Extract/Transform/Load Design.

Implementation Strategies.

Preparing for the ETL Process.

The Initial Load.

The Historical Load.

The Incremental Load.

Designing the Extract Programs.

Designing the Transformation Programs.

Source Data Problems.

Data Transformations.

Designing the Load Programs.

Referential Integrity.

Indexing.

Designing the ETL Process Flow.

The Source-to-Target Mapping Document.

The ETL Process Flow Diagram.

The Staging Area.

Evaluating ETL Tools.

ETL Design Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 9.

Bibliography and Additional Reading.

10. Step 10: Meta Data Repository Design.

Meta Data Silos.

Sources of Meta Data.

Meta Data Repository Solutions.

Centralized Meta Data Repository.

Decentralized Meta Data Repository.

Distributed XML-Enabled Meta Data Solution.

Designing a Meta Data Repository.

Entity-Relationship Design.

Object-Oriented Design.

Licensing (Buying) a Meta Data Repository.

Product Evaluation.

Vendor Evaluation.

Meta Data Repository Design Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 10.

Bibliography and Additional Reading.

11. Step 11: Extract/Transform/Load Development.

Source Data Transformation.

Data Transformation Activities.

Underestimating Data Transformation Efforts.

Reconciliation.

Calculating Reconciliation Totals.

Storing Reconciliation Statistics.

Peer Reviews.

ETL Testing.

Unit Testing.

Integration Testing.

Regression Testing.

Performance Testing.

Quality Assurance Testing.

Acceptance Testing.

Formal Test Plan.

ETL Development Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 11.

Bibliography and Additional Reading.

12. Step 12: Application Development.

Online Analytical Processing Tools.

Advantages of OLAP Tools.

OLAP Tool Features.

Multidimensional Analysis Factors.

Multivariate Analysis.

Online Analytical Processing Architecture.

Presentation Services.

OLAP Services.

Database Services.

Development Environments.

Application Development Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 12.

Bibliography and Additional Reading.

13. Step 13: Data Mining.

Defining Data Mining.

The Importance of Data Mining.

Data Sources for Data Mining.

Data Mining Techniques.

Associations Discovery.

Sequential Pattern Discovery.

Classification.

Clustering.

Forecasting.

Data Mining Operations.

Predictive and Classification Modeling.

Link Analysis.

Database Segmentation.

Deviation Detection.

Applications of Data Mining.

Data Mining Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 13.

Bibliography and Additional Reading.

14. Step 14: Meta Data Repository Development.

Populating the Meta Data Repository.

Meta Data Repository Interface Processes.

The Tool Interface Process.

The Access Interface Process.

Meta Data Repository Testing.

Preparing for the Meta Data Repository Rollout.

Meta Data Repository Directory.

Meta Data Repository Development Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 14.

Bibliography and Additional Reading.

15. Step 15: Implementation.

Incremental Rollout.

Security Management.

Security Measures for BI Applications.

Security in a Multi-Tier Environment.

Security for Internet Access.

Data Backup and Recovery.

Monitoring the Utilization of Resources.

Computer Utilization.

Network Utilization.

Personnel Utilization.

Growth Management.

Growth in Data.

Growth in Usage.

Growth in Hardware.

Implementation Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 15.

Bibliography and Additional Reading.

16. Step 16: Release Evaluation.

The Application Release Concept.

Guidelines for Using the Release Concept.

Post-Implementation Reviews.

Organizing a Post-Implementation Review.

Post-Implementation Review Session Flow.

Release Evaluation Activities.

Deliverables Resulting from These Activities.

Roles Involved in These Activities.

Risks of Not Performing Step 16.

Bibliography and Additional Reading.

II. AT A GLANCE.

17. Resource Allocation Matrix.
18. Entry & Exit Criteria and Deliverables Matrix.
19. Activity Dependency Matrix.
20. Task/Subtask Matrix.
21. Practical Guidelines Matrix.
Appendix. Work Breakdown Structure.
Index

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Customer Reviews

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Sort by: Showing all of 3 Customer Reviews
  • Anonymous

    Posted April 19, 2003

    A Must for Every BI/DW Professional

    It is refreshing to read a book that presents in-depth techniques for developing a BI application from cradle to grave in a continuous evolutionary process. Various matrices and WBS samples in Part II of the book serve as a quick reference for iterative planning and delivering of decision-support systems.The authors have done a phenomenal job in integrating business, technical,and management aspects of a BI and decision-support system to present an exhaustive set of guidelines. After working with numerous clients and having read Inmon¿s Building the Data Warehouse, Kimball¿s The Data Warehouse Lifecycle Toolkit as well as various BI white papers, I know that data ETL and data warehouses are a major part of any BI strategy. However, after reviewing the summary of over 20 BI related books, I found that the primary focus of many BI books is normally limited to data presentation and analytical layers only.This book is an exception . I would recommend this book to expert as well as novice DW/BI professionals alike, who may be business users, data analysts, architects, project managers, statisticians,or executive stakeholders.

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  • Anonymous

    Posted April 2, 2003

    Very Useful

    This is an excellent book and, more importantly, it¿s very useful. It¿s loaded with specifics and checklists on what to do and how to do it (it also tells you what not to do). It lays out the pitfalls and tells you how to avoid them. The stages and steps outlined in the book are very specific and the authors, with their wealth of experience, tell you how to implement a successful data warehouse. The work breakdown structure (the tasks you need to implement the data warehouse), the deliverables matrix, and entry and exit criteria for each step are very detailed and alone are worth the price of the book. The book will give those responsible for a data warehouse the information they need to establish best practices within their own organization and will give these folks the ammunition and support to ask for the necessary resources to implement a data warehouse.

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  • Anonymous

    Posted December 30, 2012

    No text was provided for this review.

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