Business Intelligence Guidebook: From Data Integration to Analytics

Business Intelligence Guidebook: From Data Integration to Analytics

by Rick Sherman
ISBN-10:
012411461X
ISBN-13:
9780124114616
Pub. Date:
11/07/2014
Publisher:
Elsevier Science
ISBN-10:
012411461X
ISBN-13:
9780124114616
Pub. Date:
11/07/2014
Publisher:
Elsevier Science
Business Intelligence Guidebook: From Data Integration to Analytics

Business Intelligence Guidebook: From Data Integration to Analytics

by Rick Sherman
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Overview

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.


Product Details

ISBN-13: 9780124114616
Publisher: Elsevier Science
Publication date: 11/07/2014
Edition description: New Edition
Pages: 550
Product dimensions: 7.30(w) x 9.10(h) x 1.00(d)

About the Author

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.

Table of Contents

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

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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.

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