A Manager's Guide to Data Warehousing / Edition 1

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Overview

Aimed at helping business and IT managers clearly communicate with each other, this helpful book addresses concerns straight-on and provides practical methods to building a collaborative data warehouse . You’ll get clear explanations of the goals and objectives of each stage of the data warehouse lifecycle while learning the roles that both business managers and technicians play at each stage. Discussions of the most critical decision points for success at each phase of the data warehouse lifecycle help you understand ways in which both business and IT management can make decisions that best meet unified objectives.
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Product Details

  • ISBN-13: 9780470176382
  • Publisher: Wiley
  • Publication date: 5/26/2009
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 480
  • Product dimensions: 7.40 (w) x 9.20 (h) x 1.10 (d)

Meet the Author

Laura L. Reeves, coauthor of The Data Warehouse Lifecycle Toolkit, has over 23 years of experience in end-to-end data warehouse development focused on developing comprehensive project plans, collecting business requirements, designing business dimensional models and database schemas, and creating enterprise data warehouse strategies and data architectures.

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Table of Contents

Introduction xxiii

Part One The Essentials of Data Warehousing 1


Chapter 1 Gaining Data Warehouse Success 3

The Essentials of Data Warehousing 3

What Is a Data Warehouse? 4

Differences Between Operational and DW Systems 4

The DataWarehousing Environment 4

What Is a Data Model? 6

Understanding Industry Perspectives 7

Design and Development Sequence 8

Why Build a Data Warehouse? 11

The Value of Data Warehousing 12

The Promises of DataWarehousing 15

Keys to Success 16

Developing and Maintaining Strong Business and Technology Partnerships 17

Identifying True Business Requirements 17

Shifting to a Global Perspective 18

Overcoming Unrealistic Expectations 19

Providing Clear Communication 20

Treating Data As a Corporate Asset 21

Effectively Leveraging Technology 21

Roadblocks to Success 22

Believing the Myth: ‘‘If You Build It, They Will Come’’ 22

Falling into the Project Deadline Trap 23

Failing to Uphold Organizational Discipline 23

Lacking Business Process Change 24

Narrowing the Focus Too Much 25

Resting on Your Laurels 27

Relying on the Technology Fix 27

Getting the Right People Involved 28

Finding Lost Institutional Knowledge 29

Summary 30

Chapter 2 The Executive’s FAQ for Data Warehousing 31

Question:What is the business benefit of a data warehouse? 32

Answer 32

Question: How much will it cost? 33

Answer 33

Question: How long will it take? 34

Answer 35

Question: How can I ensure success? 36

Answer 36

Question: Do other companies really build these in 90 days? 37

Answer 37

Question: How will we know we are doing this right? 38

Answer 38

Question:Why didn’t this work last time?What is different this time? 39

Answer 39

Question: Do we have the right technology in place? 39

Answer 40

Question: Are we the only company with data warehouse problems? 40

Answer 41

Question:Will I get one version of the truth? 41

Answer 42

Question:Why can’t we just use our current systems? 43

Answer 44

Question:Will the data warehouse replace our old systems? 45

Question:Who needs to be involved? 45

Question: Do we know where we are going? How will we know when we get there? 46

Answer 46

Question: How do we get started and stay focused? 47

Answer 47

Summary 48

Part Two The Business Side of Data Warehousing 49

Chapter 3 Understanding Where You Are and Finding Your Way 51

Assessing Your Current State 51

What Is Your Company’s Strategic Direction? 52

What Are the Company’s Top Initiatives? 54

How Healthy Is Your Data? 55

Does the Business Place Value on Analysis? 56

Reflecting on Your Data Warehouse History 57

Understanding Your Existing Reporting Environment 58

Finding the Reporting Systems 59

Compiling an Inventory 60

Identifying the Business Purpose 61

Discovering the Data You Already Have 63

Understanding the People 65

Tracking Technology and Tools 65

Understanding Enterprise Resources 66

Netting It All Out 68

Introducing the Case Studies 70

The Call Center Data Warehouse Project 70

In Real Life 70

Giant Company 71

Agile, Inc. 72

Summary 72

Chapter 4 Successful IT–Business Partnerships 75

What a Partnership Really Means 75

What the Business Partners Should Expect to Do 76

Business Executives and Senior Management 78

The Executive Business Sponsor 78

Business Managers 81

The Business Champion 82

Business Analysts 83

Helping the Business Analyst Deal with Change 85

Business User Audience 86

Project Manager 86

What You Should Expect from IT 88

CIO/IT Executive Sponsor 89

Data Warehouse Manager 89

Business Systems Analyst 90

Source System Analyst 91

Data Modeler/Data Architect 92

ETL Developer(s) 93

Business Intelligence Application Developer 94

Other Supporting Roles 95

Tips for Building and Sustaining a Partnership 95

Leveraging External Consulting 97

Building Strong Project Teams 98

Effective Communication 99

Netting Out Key Messages 99

Presenting in Business Terms 100

Meeting Preparation 101

Presentation Tips 102

When to Communicate 103

Partnerships Beyond a Project 104

The Decision-Making Process 104

Executive Steering Committee 104

DW Business Support Team 106

Enterprise Considerations 107

In Real Life 107

A Glimpse into Giant, Co. 107

Insight from Agile, Inc. 108

Summary 109

Chapter 5 Setting Up a Successful Project 111

Defining the Project 111

Setting Up the Project Charter 112

Documenting Project Scope 117

Developing a Statement of Work 117

How Much Will It Cost? 120

Project Approval 122

Starting the Project 122

Launching the Project 123

Managing a Successful Project 124

Issue Tracking 124

Using Project Change Control 125

Discussing Change in Business Terms 126

Managing Expectations 128

In Real Life 129

Structured Projects with Giant 129

Freedom for Creativity at Agile, Inc. 130

Summary 131

Chapter 6 Providing Business Requirements 133

What Requirements Are Needed? 134

Peeling Back the Layers of Requirements Gathering 134

Who Provides Input? 137

Who Gathers the Requirements? 137

Providing Business Requirements 138

Strategic Requirements 138

Broad Business Requirements 140

Business Analyses 143

Business Data Requirements 145

Systems and Technical Requirements 147

Communicating What You Really Need 149

What Else Would Help the Project Team? 150

Data Integration Challenges 151

Assess Organizational Motivation 151

Complete Picture of the Data 152

What If No One Is Asking? 152

Practical Techniques for Gathering Requirements 153

Interview Session Characteristics 153

Individual Interviews 153

Group Interviews 153

Project Team Participation 154

Interview Tips 154

Who Needs to Be Included? 155

Setting a Good Example 156

Preparing for Interview Sessions 157

Conducting the Interview Sessions 157

Capturing Content: Notes vs. Tapes 157

Running the Interview 158

Concluding the Interview 158

Putting the Pieces Together 158

Individual Interview Documentation 159

Responsibilities 159

Business Themes 159

Business Data 160

Consolidated Requirements Documentation 161

Executive Summary 161

Consolidated Business Themes 162

Candidate Business Analyses 162

Consolidated Business Data Requirements 162

Identification of Non-Data Warehouse Requirements 163

Common Requirements Gathering Challenges 163

Sifting Through Reports 163

Listing Data Elements 164

Developing Functional Specifications 164

Moving Beyond Immediate 164

Lack of Requirements 165

The Cynic 165

Setting Attainable Goals 166

Exploring Alternatives 167

Setting Priorities 168

In Real Life 170

A Glimpse into Giant Company 170

Insight from Agile, Inc. 170

Summary 171

Part Three Dealing with the Data 173

Chapter 7 Modeling the Data for your Business 175

The Purpose of Dimensional Models 176

Ease of Use 176

Query Performance 177

Understanding Your Data 177

What Is a Dimensional Model? 178

Dimensions 178

Facts 180

Using Both Parts of the Model 180

Implementing a Dimensional Model 181

Diagramming Your Dimensional Model 182

The Business Dimensional Model 182

Business Dimensions 183

Fact Groups 184

A Call Center Case Study 186

Call Center Dimensions 187

Date Dimension 187

Time Dimension 187

Customer Dimension 189

Employee Dimension 191

Call Dimension 191

Call Outcome Dimension 194

Employee Task Dimension 195

Call Center Fact Groups 196

Calls Fact Group 196

Call Center Time Tracking Fact Group 196

Call Forecast Fact Group 198

Working with the Model 199

Business Dimensional Model Index 200

Enterprise Considerations 200

Conformed Dimensions 200

Conformed Facts 202

Practical Guidelines 202

Guidelines for a Single Dimension 202

Guidelines for a Single Fact Group 203

Characteristics of the Model across the Enterprise 204

Business Participation in the Modeling Process 205

Creating the First Draft 205

Preparing for Modeling Sessions 205

Brainstorming the Framework 206

Drafting the Initial Dimensions 206

Drafting the Initial Fact Groups 207

Documenting the Model 208

Logging Questions and Issues 208

Building the Business MeasuresWorksheet 209

Preliminary Source to Target Data Map 211

Completing or Fleshing Out the Model 211

Working Through the Issues 211

Completing the Documentation 212

Working Through All the Data Elements 212

Refining the Model 213

Business Reviews of the Model 213

Small Business Reviews 214

When Are You Done? 214

Gaining Final Commitment 215

Expanding Business Data Over Time 215

Enhancing Dimensions 215

Adding More Fact Groups 215

Reflecting on Business Realities: Advanced Concepts 216

Supporting Multiple Perspectives: Multiple Hierarchies 216

Tracking Changes in the Dimension: Slowly Changing

Dimensions 216

Depicting the Existence of a Relationship: Factless Fact Tables 218

Linking Parts of a Transaction: Degenerate Dimensions 219

Pulling Together Components: Junk Dimensions 221

Multiple Instances of a Dimension: Role Playing 222

Other Notation 224

Dimension Connectors 224

Clusters of Future Attributes 225

Notation Summary 225

Taking the Model Forward 225

Translating the Business Dimensional Model 226

Dimension Table Design 226

Translating Fact Groups 227

Physical Database Design 228

In Real Life 228

A Glimpse into Giant Co. 229

Insight from Agile, Inc. 229

Summary 230

Chapter 8 Managing Data As a Corporate Asset 231

What Is Information Management? 232

Information Management Example—Customer Data 235

IM Beyond the Data Warehouse 239

Master Data Management 240

Master Data Feeds the Data Warehouse 242

Finding the Right Resources 242

Data Governance 243

Data Ownership 243

Who Really Owns the Data? 244

Your Responsibilities If You Are ‘‘the Owner’’ 246

What are IT’s Responsibilities? 247

Challenges with Data Ownership 247

Data Quality 248

Profiling the Data 249

How Clean Does the Data Really Need to Be? 250

Measuring Quality 250

Quality of Historical Data 251

Cleansing at the Source 253

Cleaning Up for Reporting 254

Managing the Integrity of Data Integration 254

Quality Improves When It Matters 256

Example: Data Quality and Grocery Checkout Scanners 257

Example: Data Quality and the Evaluation of Public Education 257

Realizing the Value of Data Quality 258

Implementing a Data Dictionary 259

The Data Dictionary Application 259

Populating the Data Dictionary 261

Accessing the Data Dictionary 263

Maintaining the Data Dictionary 263

Getting Started with Information Management 264

Understanding Your Current Data Environment 264

What Data Do You Have? 265

What Already Exists? 266

Where Do You Want to Be? 267

Develop a Realistic Strategy 268

Sharing the Information Management Strategy 269

Setting Up a Sustainable Process 270

Enterprise Commitment 270

The Data Governance Committee 270

Revising the Strategy 271

In Real Life 271

A Glimpse into Giant, Co. 272

Insight from Agile, Inc. 272

Summary 274

Part Four Building the Project 275

Chapter 9 Architecture, Infrastructure, and Tools 277

What Is Architecture? 278

Why Do We Need Architecture? 278

Making Architecture Work 281

Data Architecture 282

Revisiting DW Goals 283

Components of DW Data Architecture 285

A Closer Look at Common Data Warehouse Architectures 286

Bottom-Up Data Architecture 286

Top-Down Data Architecture 290

Publish the Data: Data Marts 294

Adopting an Architecture 295

Technical Architecture 297

Technical Architecture Basics 298

Components of Technical Architecture 299

Infrastructure 300

Technical Architecture in Action 300

What You Need to Know about Technical Architecture 301

Navigating the Technology Jungle 302

Weighing Technology Options 303

Best of Breed 303

End-to-End Solutions 303

Deciding Not to Buy a Tool 304

Finding the Right Products 304

Requests for Information or Proposals 305

Business Participation in the Selection Process 305

Understanding Product Genealogy 306

Understanding Value and Evaluating Your Options 306

Cutting through the Marketing Hype 308

The Value of References 309

Making ArchitectureWork for You 310

Just-In-Time Architecture 311

In Real Life 311

Architecture at Giant 311

Agile Ignores the Need for Architecture 312

Summary 313

Chapter 10 Implementation: Building the Database 315

Extract, Transform, and Load (ETL) Fundamentals 315

What Work Is Being Done? 315

ETL System Functionality 317

Extraction 318

Transformation 318

Load 322

The Business Role in ETL 323

Why Does the Business Need to Help? 323

Defining Business Rules 324

Defining Expected Results—The Test Plan 325

Development Support 326

Testing the ETL System—Is the data Right? 326

Why Does It Take So Long and Cost So Much? 327

Balancing Requirements and Data Reality 329

Discovering the Flaws in Your Current Systems 330

Applying New Business Rules 331

Working Toward Long-Term Solutions 332

Manually Including Business Data 333

Tracking Progress—AreWe There Yet? 333

What Else Can You Do to Help? 334

Encouragement and Support 334

Ensuring Continued Business Participation 335

Proactive Communication 336

In Real Life 337

Building the Data Warehouse at Giant, Co. 337

Agile, Inc., Builds a Data Warehouse Quickly 338

Summary 339

Chapter 11 Data Delivery: What you Finally See 341

What Is Business Intelligence? 341

Business Intelligence without a DW 342

BI in Action 343

Tabular Reports 343

Parameter-Driven Reports 343

Interactive Reports—Drilling Down and Across 344

Exception Reports 344

Other BI Capabilities 345

Complex Analysis 345

BI Building Blocks 346

Data Content—UnderstandingWhat You Have 346

Navigation—Finding What You Need 347

Presentation—How Do YouWant to See Results? 347

Delivery—How Do You Receive the Results? 351

Supporting Different Levels of Use 352

Construction of the BI Solution 354

Planning for Business Change 354

Design—What Needs to Be Delivered? 355

Development 357

Testing BI Applications and Validating Data 358

Additional Responsibilities 359

Security—Who Can Look t the Data? 359

System Controls—Who Can Change What? 360

Planning a Successful Launch 361

Marketing the Solution 361

Learning to Use the Data without a Technical Degree 362

Learning about the Data 362

Learning about the BI Tool/Application 362

Ensuring That the Right Help Is Available 363

In Real Life 364

BI at Giant Company 364

Agile, Inc. Dives into BI 365

Summary 366

Part Five Next Steps—Expanding On Success 367

Chapter 12 Managing the Production Data Warehouse 369

Finishing the Project 369

Recapping the BI Application Launch 369

Post-Implementation Review 370

Looking Back—Did you Accomplish Your Objectives? 371

Adopting the Solution 371

Tracking Data Warehouse Use 372

Getting the Rest of the Business Community on Board 372

Business Process Change 374

Changing How Data Is Used 374

Streamlining Business Processes 374

Encouraging Change 375

The Production DataWarehouse 375

Staffing Production Activities 376

Maintaining the Environment 376

Keeping Up with Technology 376

Monitoring Performance and Capacity Planning 378

Maintaining the Data Warehouse 380

Maintaining the ETL System 380

Maintaining the BI Application 381

Tracking Questions and Problems 382

Fixing Bugs 384

When the DataWarehouse Falls Short 384

Common Causes for a StalledWarehouse 385

Jump-Starting a Stalled Data Warehouse 388

Conducting an Assessment 388

DeterminingWhat Can Be Salvaged 389

Developing a Plan to Move On 390

Aligning DW Objectives with Business Goals 391

Getting It Right This Time 392

Launching the Improved Data Warehouse and BI Solution 393

In Real Life 394

Lack of Support for the Production DW at Giant Co. 394

Unleashing BI at Agile, Inc. 395

Summary 396

Chapter 13 Achieving Long-Term Success 397

Planning for Expansion and Growth 397

Exploring Expansion Opportunities 398

Prioritization of Feedback 399

Managing Enterprise DWResources 400

Creating an Enterprise Data Warehouse Team 400

The Centralized Enterprise Data Warehouse Team 401

The Virtual Enterprise Data Warehouse Team 401

Enterprise DW Team Responsibilities 403

Funding the Enterprise DW Team 404

Pushing into the Future 405

Embedded Business Intelligence 405

Operational Business Intelligence 406

Real-Time DataWarehousing 407

Unstructured Data 408

Monitoring Industry Innovation 409

Moving Toward Business Value 410

Measuring Success One Step at a Time 410

Adjusting Expectations to Reality 412

Keeping the Momentum Going 413

Celebrating Progress 416

Success Can Be Attained 417

Conclusion 419

Glossary 421

Index 429

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