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 situationsCompanion website includes exercises and problem-solution sets with vendor agnostic data modeling examples, as well as a sample syllabus and slides for instructors INDICE: Part 1. Concepts and Context 1.Business Demand and Information Applications 2.Technology Landscape Part 2. Business and Technical Needs 3.Justifying BI (Building Business and Technical Case) 4.Defining Requirements - Business, Data and Quality Part 3. Architectural Framework 5. Architecture Introduction 6.Information Architecture 7.Data Architecture 8.Technology and Product Architecture Part 4. Data Design 9.Data Modeling Foundation 10.Hybrid Dimensional Modeling 11.Implementing Data Models Part 5. Data Integration Design 12.Data Integration Specifications 13.Data Integration Processes 14. Data Integration Portfolio 15.Master Data Management (MDM) Part 6. BI Design 16.BI Applications 17.BI Design 18.Advanced Analytics Part 7. Organization 19. People, Process & Politics 20. Project Methodology 21.Centers Of Excellence (COE) 22.Ongoing Operations
- ISBN: 978-0-12-411461-6
- Editorial: Morgan Kaufmann
- Encuadernacion: Rústica
- Páginas: 350
- Fecha Publicación: 26/11/2014
- Nº Volúmenes: 1
- Idioma: Inglés