Business Intelligence Guidebook: From Data Integration to Analytics
- 10h 38m
- Rick Sherman
- Elsevier Science and Technology Books, Inc.
- 2015
Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors' tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled - projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers.
After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget - turning the deluge of data into actionable information that fuels business knowledge. Finally, you'll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success.
- Provides practical guidelines for building successful BI, DW and data integration solutions.
- Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language.
- Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses
- Describes best practices and pragmatic approaches so readers can put them into action.
In this Book
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Foreword
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How to Use This Book
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The Business Demand for Data, Information, and Analytics
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Justifying BI—Building the Business and Technical Case
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Defining Requirements—Business, Data and Quality
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Architecture Framework
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Information Architecture
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Data Architecture
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Technology & Product Architectures
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Foundational Data Modeling
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Dimensional Modeling
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Business Intelligence Dimensional Modeling
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Data Integration Design and Development
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Data Integration Processes
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Business Intelligence Applications
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BI Design and Development
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Advanced Analytics
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Data Shadow Systems
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People, Process and Politics
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Project Management
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Centers of Excellence
