Business intelligence guidebook : from data integration to analytics / Rick Sherman ; foreword by Claudia Imhoff.

Format:

Book

Author/Creator:

Sherman, Rick, author.

Imhoff, Claudia, author of introduction, etc.

Language:

English

Subjects (All):

Business intelligence.

Physical Description:

1 online resource (551 p.)

Edition:

1st edition

Place of Publication:

Waltham, Massachusetts : Morgan Kaufmann, 2015.

Language Note:

English

System Details:

text file

Summary:

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. 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. Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.

Contents:

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-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-RISE OF EDW AGAIN

OPERATIONAL DATA STORE

REFERENCES.

CHAPTER 7 - TECHNOLOGY &amp

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-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

ADVANCED DIMENSIONS AND FACTS

DIMENSIONAL MODELING RECAP

CHAPTER 10 - BUSINESS INTELLIGENCE DIMENSIONAL MODELING

INTRODUCTION

HIERARCHIES

OUTRIGGER TABLES

SLOWLY CHANGING DIMENSIONS

CAUSAL DIMENSION

MULTIVALUED DIMENSIONS

JUNK DIMENSIONS

VALUE BAND REPORTING

HETEROGENEOUS PRODUCTS

ALTERNATE DIMENSIONS

TOO FEW OR TOO MANY DIMENSIONS

PART V - DATA INTEGRATIONDESIGN

CHAPTER 11 - DATA INTEGRATION DESIGN AND DEVELOPMENT

GETTING STARTED WITH DATA INTEGRATION

DATA INTEGRATION ARCHITECTURE

DATA INTEGRATION REQUIREMENTS

DATA INTEGRATION DESIGN

DATA INTEGRATION STANDARDS

LOADING HISTORICAL DATA

DATA INTEGRATION PROTOTYPING

DATA INTEGRATION TESTING

CHAPTER 12 - DATA INTEGRATION PROCESSES

INTRODUCTION: MANUAL CODING VERSUS TOOL-BASED DATA INTEGRATION

DATA INTEGRATION SERVICES

PART VI - BUSINESSINTELLIGENCEDESIGN

CHAPTER 13 - BUSINESS INTELLIGENCE APPLICATIONS

BI CONTENT SPECIFICATIONS

REVISE BI APPLICATIONS LIST

BI PERSONAS

BI DESIGN LAYOUT-BEST PRACTICES.

DATA DESIGN FOR SELF-SERVICE BI

MATCHING TYPES OF ANALYSIS TO VISUALIZATIONS

CHAPTER 14 - BI DESIGN AND DEVELOPMENT

BI DESIGN

BI DEVELOPMENT

BI APPLICATION TESTING

CHAPTER 15 - ADVANCED ANALYTICS

ADVANCED ANALYTICS OVERVIEW AND BACKGROUND

PREDICTIVE ANALYTICS AND DATA MINING

ANALYTICAL SANDBOXES AND HUBS

BIG DATA ANALYTICS

DATA VISUALIZATION

REFERENCE

CHAPTER 16 - DATA SHADOW SYSTEMS

THE DATA SHADOW PROBLEM

ARE THERE DATA SHADOW SYSTEMS IN YOUR ORGANIZATION?

WHAT KIND OF DATA SHADOW SYSTEMS DO YOU HAVE?

DATA SHADOW SYSTEM TRIAGE

THE EVOLUTION OF DATA SHADOW SYSTEMS IN AN ORGANIZATION

DAMAGES CAUSED BY DATA SHADOW SYSTEMS

THE BENEFITS OF DATA SHADOW SYSTEMS

MOVING BEYOND DATA SHADOW SYSTEMS

MISGUIDED ATTEMPTS TO REPLACE DATA SHADOW SYSTEMS

RENOVATING DATA SHADOW SYSTEMS

PART VII - ORGANIZATION

CHAPTER 17 - PEOPLE, PROCESS AND POLITICS

THE TECHNOLOGY TRAP

THE BUSINESS AND IT RELATIONSHIP

ROLES AND RESPONSIBILITIES

BUILDING THE BI TEAM

TRAINING

DATA GOVERNANCE

CHAPTER 18 - PROJECT MANAGEMENT

THE ROLE OF PROJECT MANAGEMENT

ESTABLISHING A BI PROGRAM

BI ASSESSMENT

WORK BREAKDOWN STRUCTURE

BI ARCHITECTURAL PLAN

BI PROJECTS ARE DIFFERENT

PROJECT METHODOLOGIES

BI PROJECT PHASES

BI PROJECT SCHEDULE

CHAPTER 19 - CENTERS OF EXCELLENCE

THE PURPOSE OF CENTERS OF EXCELLENCE

BI COE

DATA INTEGRATION CENTER OF EXCELLENCE

ENABLING A DATA-DRIVEN ENTERPRISE

Index.

Notes:

Bibliographic Level Mode of Issuance: Monograph

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9780124115286

0124115284

OCLC:

894555128