Business intelligence guidebook: from data integration to analytics

Description

Intro -- Cover image -- Title page -- Table of Contents -- Copyright -- Foreword -- How to Use This Book -- Acknowledgments -- Part I. Concepts and Context -- Chapter 1. The Business Demand for Data, Information, and Analytics -- Just One Word: Data -- Welcome to the Data Deluge -- Taming the Analytics Deluge -- Too Much Data, Too Little Information -- Data Capture versus Information Analysis -- The Five Cs of Data -- Common Terminology from our Perspective -- Part II. Business and Technical Needs -- Chapter 2. Justifying BI: Building the Business and Technical Case -- Why Justification is Needed -- Building the Business Case -- Building the Technical Case -- Assessing Readiness -- Creating a BI Road Map -- Developing Scope, Preliminary Plan, and Budget -- Obtaining Approval -- Common Justification Pitfalls -- Chapter 3. Defining Requirements-Business, Data and Quality -- The Purpose of Defining Requirements -- Goals -- Deliverables -- Roles -- Defining Requirements Workflow -- Interviewing -- Documenting Requirements -- Part III. Architectural Framework -- Chapter 4. Architecture Framework -- The Need for Architectural Blueprints -- Architectural Framework -- Information Architecture -- Data Architecture -- Technical Architecture -- Product Architecture -- Metadata -- Security and Privacy -- Avoiding Accidents with Architectural Planning -- Do Not Obsess over the Architecture -- Chapter 5. Information Architecture -- The Purpose of an Information Architecture -- Data Integration Framework -- DIF Information Architecture -- Operational BI versus Analytical BI -- Master Data Management -- Chapter 6. Data Architecture -- The Purpose of a Data Architecture -- History -- Data Architectural Choices -- Data Integration Workflow -- Data Workflow-Rise of EDW Again -- Operational Data Store -- Chapter 7. Technology & Product Architectures.;This book arms you with the knowledge you need to design rock-solid business intelligence and data integration processes. 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. It 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. --