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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 BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable, and essential for delivering vital Big Data into the hands of business decision-makers. After reading this book, you will be able to design the overall architecture for functioning data warehousing, business intelligence, and data-integration systems. You will have the information you need to plan, budget, and manage a successful business intelligence program through its entire lifecycle, and build and implement data integration and BI systems that are cost-effective, on-time, and increase the business ROI of Big Data. Finally, you'll give your career a boost by demonstrating 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 application to various real-life situations* Companion website includes exercises and problem-solution sets with vendor agnostic data modeling examples, as well as a sample syllabus and slides for instructors