Business Intelligence Guidebook

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.
- Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.

Rick Sherman is the founder of Athena IT Solutions, which provides consulting, training and vendor services for business intelligence, analytics, data integration and data warehousing. He is an adjunct faculty member at Northeastern University's Graduate School of Engineering and is a frequent contributor to industry publications, events, and webinars.

Concepts and Context 1 IntroductionBusiness and Technical Needs 2 Justifying BI (Building Business and Technical Case3 Defining Requirements - Business, Data and QualityArchitectural Framework 4 Architecture Introduction5 Information Architecture6 Data Architecture7 Technology and Product ArchitecturesData Design 8 Foundational Data Modeling9 Dimensional Modeling10 Advanced Dimensional ModelingData Integration Design 11 Data Integration Processes12 Data Integration Design & DevelopmentBI Design 13 BI Applications14 BI Design & Development15 Advanced Analytics16 Data Shadow SystemsOrganization 17 People, Process and Politics18 Project Management19 Centers of Excellence