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Business Intelligence Guidebook
From Data Integration to Analytics
Master the full BI project lifecycle including requirements, project management, data modeling, architecture, data integration, BI applications, and analytics. Learn how to build out the data architecture framework that will incorporate data warehousing and Big Data elements.
Rick Sherman (Author)
9780124114616, Elsevier Science
Paperback, published 18 November 2014
550 pages, 100 illustrations
23.5 x 19 x 3.4 cm, 0.96 kg
"Anyone tasked with business intelligence and data integration will want this outstanding introduction and guidebook…An established professional will also not be disappointed with the fresh how-to look. I highly recommend it." --Computing Reviews "The world of architecture and technology is rapidly changing and has been for a while. Fortunately we have people like Rick Sherman who stay abreast of the latest advances. This book is as close to a complete A to Z guidebook as you will find. I recommend this book for every professional's desk." --Bill Inmon, Forest Rim Technology "Rick covers a lot of ground in the BI Guidebook offering clear explanations of a wide range of BI and DW topics (e.g., technologies, methodologies). His approach makes it both a useful primer for those new to Business Intelligence as well as a great reference for more seasoned pros." --Howard Dresner, Chief Research Officer Dresner Advisory Services "Anyone looking to rollout a business intelligence initiative or shore up a fledgling one can benefit from the BI Guidebook. Rick Sherman leaves no stone unturned and takes a deep dive into a complex and diverse field. Even a seasoned BI professional will enjoy having this book as a reference within arm's reach." --William McNight "One cannot manage a business or run any organization without measurement: knowing where you'v been, where you are and where you are going. But while BI is the key enabler for such quantitative enterprise management, it remains one of the more complicated areas of information technology. BI encompasses a wide range of expertise from the technical mastery of building data models to the psychological finesse of resolving conflicts between IT and business people. This is why educating the market on best practices is so important, and why Forrester encourages reading and studying books that arm people with the knowledge they need to tackle the myriad challenges of implementing BI projects. This book, particularly, confirms Forrester’s position that data is a vital tool and a corporate asset that should have direct impact on enterprise top and bottom lines, as well as balance sheets." --Boris Evelson, Vice President, Principal Analyst, Forrester Research, Inc.
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.
Concepts and Context 1 Introduction Business and Technical Needs 2 Justifying BI (Building Business and Technical Case 3 Defining Requirements - Business, Data and Quality Architectural Framework 4 Architecture Introduction 5 Information Architecture 6 Data Architecture 7 Technology and Product Architectures Data Design 8 Foundational Data Modeling 9 Dimensional Modeling 10 Advanced Dimensional Modeling Data Integration Design 11 Data Integration Processes 12 Data Integration Design & Development BI Design 13 BI Applications 14 BI Design & Development 15 Advanced Analytics 16 Data Shadow Systems Organization 17 People, Process and Politics 18 Project Management 19 Centers of Excellence
Subject Areas: Database programming [UMT], Information technology: general issues [UB], Knowledge management [KJMV3]
