Print version record.

Includes bibliographical references and index.

""Front Cover""; ""Business Intelligence Guidebook""; ""Copyright""; ""Contents""; ""Foreword""; ""How to Use This Book""; ""CHAPTER SUMMARIES""; ""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""; ""REFERENCES""; ""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�a�?BUSINESS, DATA AND QUALITY""; ""THE PURPOSE OF DEFINING REQUIREMENTS""; ""GOALS""; ""DELIVERABLES""; ""ROLES""; ""DEFINING REQUIREMENTS WORKFLOW""; ""INTERVIEWING""; ""DOCUMENTING REQUIREMENTS""

""Part iii -- architecturalframework""""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�a�?RISE OF EDW AGAIN""; ""OPERATIONAL DATA STORE""; ""REFERENCES""; ""CHAPTER 7 -- TECHNOLOGY & PRODUCT ARCHITECTURES""; ""WHERE ARE THE PRODUCT AND VENDOR NAMES?""; ""EVOLUTION NOT REVOLUTION""; ""TECHNOLOGY ARCHITECTURE""; ""PRODUCT AND TECHNOLOGY EVALUATIONS""; ""PART IV -- DATA DESIGN""; ""CHAPTER 8 -- FOUNDATIONAL DATA MODELING""; ""THE PURPOSE OF DATA MODELING""

""DEFINITIONS�a�?THE DIFFERENCE BETWEEN A DATA MODEL AND DATA MODELING""""THREE LEVELS OF DATA MODELS""; ""DATA MODELING WORKFLOW""; ""WHERE DATA MODELS ARE USED""; ""ENTITY-RELATIONSHIP (ER) MODELING OVERVIEW""; ""NORMALIZATION""; ""LIMITS AND PURPOSE OF NORMALIZATION""; ""CHAPTER 9 -- DIMENSIONAL MODELING""; ""INTRODUCTION TO DIMENSIONAL MODELING""; ""HIGH-LEVEL VIEW OF A DIMENSIONAL MODEL""; ""FACTS""; ""DIMENSIONS""; ""SCHEMAS""; ""ENTITY RELATIONSHIP VERSUS DIMENSIONAL MODELING""; ""PURPOSE OF DIMENSIONAL MODELING""; ""FACT TABLES""; ""ACHIEVING CONSISTENCY""

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.