Verfügbarkeit: The data warehouse lifecycle toolkit

The data warehouse lifecycle toolkit:

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Bibliographische Detailangaben
Hauptverfasser:	Kimball, Ralph 1944- (VerfasserIn), Ross, Margy 1959- (VerfasserIn), Thornthwaite, Warren 1957- (VerfasserIn), Mundy, Joy 1961- (VerfasserIn), Becker, Bob (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Indianapolis Wiley 2008
Ausgabe:	2. ed.
Schlagworte:	Datenverarbeitung Business intelligence > Data processing Data warehousing Database design Data-Warehouse-Konzept
Online-Zugang:	Inhaltsverzeichnis
Beschreibung:	Auf dem Cover: "practical techniques for building data warehouse and business intelligence systems"
Beschreibung:	XXXIV, 636 S. Illustrationen
ISBN:	0470149779 9780470149775

Internformat

MARC


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adam_text	Contents at a Glance Chapter 1 Introducing the Kimball Lifecycle 1 Chapter 2 Launching and Managing the Project/Program 15 Chapter 3 Collecting the Requirements 63 Chapter 4 Introducing the Technical Architecture 109 Chapter 5 Creating the Architecture Plan and Selecting Products 179 Chapter 6 Introducing Dimensional Modeling 233 Chapter 7 Designing the Dimensional Model 287 Chapter 8 Designing the Physical Database and Planning for Performance 327 Chapter 9 Introducing Extract, Transformation, and Load 369 Chapter 10 Designing and Developing the ETL System 425 Chapter 11 Introducing Business Intelligence Applications 473 Chapter 12 Designing and Developing Business Intelligence Applications 505 Chapter 13 Deploying and Supporting the DW/BI System 541 Chapter 14 Expanding the DW/BI System 579 xi Contents Acknowledgments IX Introduction xxxi Chapter 1 Introducing the Kimball Lifecycle 1 Lifecycle History Lesson 1 Lifecycle Milestones 3 Program/Project Planning 4 Program/Project Management 4 Business Requirements Definition 5 Technology Track 5 Technical Architecture Design 5 Product Selection and Installation 6 Data Track 6 Dimensional Modeling 6 Physical Design 6 ETL Design and Development 7 Business Intelligence Application Track 7 BI Application Design 7 BI Application Development 7 Deployment 7 Maintenance 8 Growth 8 Using the Lifecycle Roadmap 8 Lifecycle Navigation Aids 9 Lifecycle Vocabulary Primer 9 Data Warehouse versus Business Intelligence 10 ETL System 11 Business Process Dimensional Model 12 Business Intelligence Applications 13 Conclusion 14 xiii xiv Contents Chapter 2 Launching and Managing the Project/Program 15 Define the Project 16 Assess Your Readiness for DW/BI 16 Strong Senior Business Management Sponsor(s) 16 Compelling Business Motivation 17 Feasibility 17 Factors Not Considered Readiness Deal Breakers 18 Address Shortfalls and Determine Next Steps 18 Strong Sponsor, Compelling Business Need, and Quality Data 19 Poor Quality Data 19 Weak Business Sponsor or IT-Only Sponsor 19 Too Much Demand from Multiple Business Sponsors 20 Well Meaning, But Overly Aggressive Business Sponsor 21 Legacy of Underperforming, Isolated Data Silos 21 Develop the Preliminary Scope and Charter 22 Focus on a Single Business Process 22 The Role of Rapid Application Development 24 Document the Scope/Charter 25 Build the Business Case and Justification 27 Determine the Financial Investments and Costs 27 Determine the Financial Returns and Benefits 28 Combine the Investments and Returns to Calculate ROI 30 Plan the Project 31 Establish the Project Identity 31 Staff the Project 32 Front Office: Sponsors and Drivers 33 Coaches: Project Managers and Leads 34 Regular Lineup: Core Project Team 35 Special Teams 38 Free Agents 39 Convert Individual Talent into a Team 40 Develop the Project Plan 40 Develop the Communication Plan 43 Project Team 44 Sponsor and Driver Briefings 45 Business User Community 45 Communication with Other Interested Parties 46 Manage the Project 46 Conduct the Project Team Kickoff Meeting 47 Monitor Project Status 48 Project Status Meetings 48 Project Status Reports 49 Maintain the Project Plan 50 Consolidate the Project Documentation 50 Contents xv Manage the Scope 50 Track Issues 51 Control Changes 52 Manage Expectations 53 Recognize Project Trouble Signs 53 Manage the Program 54 Establish Governance Responsibility and Processes 54 Elevate Data Stewardship to Enterprise Level 56 Leverage Methods and Architectural Best Practices 57 Conduct Periodic Assessments 57 Communicate, Communicate, Communicate 58 Conclusion 58 Managing the Effort and Reducing Risk 58 Assuring Quality 59 Key Roles 59 Key Deliverables 59 Estimating Considerations 60 Website Resources 60 Task List 61 Chapter 3 Collecting the Requirements 63 Overall Approach to Requirements Definition 64 Interviews versus Facilitated Sessions 66 Methods to Avoid for Collecting Requirements 67 Prepare for the Interview 68 Identify the Interview Team 68 Lead Interviewer 68 Scribe 68 Observers 70 Research the Organization 70 Select the Interviewees 71 Business Interviewees 71 IT and Compliance/Security Interviewees 72 Develop the Interview Questionnaires 73 Schedule the Interviews 73 Sequence the Interviews 73 Establish the Interview Time and Place 75 Prepare the Interviewees 76 Review Interviewing Ground Rules 77 Remember Your Interview Role 78 Assume You Will Learn 78 Verify Communications 78 Be Conversational 79 Maintain Interview Schedule Flexibility 79 Manage Expectations Continuously 80 Conduct the Interview 80 Program Business Interviews 82 xvi Contents Chapter 4 Program IT Interviews 83 Program Compliance/Security Interviews 83 Wrap Up the Interview 84 Determine the Success Criteria 84 Say Thanks and See You Later 85 Review the Interview Results 85 Synthesize Around Business Processes 86 Prepare and Publish Requirements Deliverables 87 Interview Write-Ups 88 Program Requirements Findings Document 88 Prioritize and Agree on Next Steps 91 Culminate with a Review and Prioritization Meeting 91 Close the Loop 93 Adjustments for Project Level Requirements 93 Project Level Approach 93 Prepare for the Project Requirements Interview 94 Select the Interviewees 95 Prepare the Interviewees 95 Conduct the Interviews 97 Review Existing Reports and Analyses 98 Wrap Up the Interview 99 Dig into the Data 99 Review the Interview Results 100 Prepare and Publish Project Deliverables 100 Agree on Next Steps and Close the Loop 101 Deal with Challenging Interviewees 101 Abused User 101 Overbooked/Substitute User 102 Comatose User 102 Overzealous User 102 Know-It-All User 103 Clueless User 103 Nonexistent User 103 Conclusion 104 Managing the Effort and Reducing Risk 104 Assuring Quality 105 Key Roles 105 Key Deliverables 105 Estimating Considerations 106 Website Resources 106 Task List 107 Introducing the Technical Architecture 109 The Value of Architecture 110 Technical Architecture Overview 112 Flow from Source System to User Screen 113 Common Architecture Features 115 Contents xvii Metadata Driven 115 Flexible Services Layers 117 Evolution of Your DW/BI Architecture 118 Back Room Architecture 119 General ETL Requirements 119 Build versus Buy 120 Back Room ETL Flow 121 Source Systems 121 Enterprise Resource Planning Systems 123 Operational Data Stores 124 Reporting Operational Data Stores 125 Master Data Management 125 XML Sources 126 Message Queues, Log Files, and Redo Files 126 Proprietary Formats 126 Extract 127 Clean and Conform 127 Deliver 127 ETL Management Services 128 Additional Back Room Services and Trends 129 Data Service Providers 129 Functional Service Providers 129 Data Delivery Services 129 ETL Data Stores 130 ETL System Data Stores 130 Lookup and Decode Tables 130 Data Quality Data Stores 131 ETL Metadata 131 Back Room Summary 132 Presentation Server Architecture 133 Business Requirements for Information 133 Detail Atomic Data 134 Aggregates 134 Aggregate Navigation 136 Design Disciplines within the Presentation Server 138 Adjusting the Presentation Server Architecture 138 Organizational Considerations 139 Presentation Server Metadata 140 Presentation Server Summary 141 Front Room Architecture 141 BI Application Types 141 BI Management Services 143 Shared Services 143 Vendor Specific Architectural Choices 150 BI Data Stores 151 Stored Reports 151 xviii Contents Application Server Caches 151 Local User Databases 151 Disposable Analytic Data Stores 152 Results from Analytic Applications 152 Downstream Systems 153 Data Store Security 153 Desktop Tool Architecture Approaches 154 BI Metadata 154 Front Room Summary 155 Infrastructure 156 Infrastructure Drivers 156 Back Room and Presentation Server Infrastructure Factors 157 Parallel Processing Hardware Architectures 159 Symmetric Multiprocessing (SMP) 159 Massively Parallel Processing (MPP) 161 Non-Uniform Memory Architecture (NUMA) 161 Clusters 161 Warehouse Appliances 162 Partitioning Hardware 163 Considerations Common to All Parallel Architectures 163 Hardware Performance Boosters 163 Disk Issues 163 Memory 164 CPUs 165 Secondary Storage 165 Database Platform Factors 165 Characteristics of Relational Engines 165 Characteristics of OLAP Engines 166 Front Room Infrastructure Factors 167 Application Server Considerations 167 Desktop Considerations 168 Connectivity and Networking Factors 169 Infrastructure Summary 170 Metadata 170 Value of Metadata Integration 171 Impact Analysis 171 Audit and Documentation 171 Metadata Quality and Management 171 Options for Metadata Integration 172 Single Source DW/BI System Vendors 172 Core Vendor Product 172 Do It Yourself 173 Metadata Summary 173 Security 173 Security Vulnerabilities 174 Threats to Physical Assets 174 Contents xix Threats to Information and Software Assets 175 Threats to Business Continuance 176 Network Threats 176 Security Summary 177 Conclusion 178 Chapter 5 Creating the Architecture Plan and Selecting Products 179 Create the Architecture 180 Architecture Development Process 180 Develop the Application Architecture Plan 183 Step 1 — Form an Architecture Task Force 183 Step 2 — Gather Architecture-Related Requirements 184 Step 3 — Create a Draft Architectural Implications Document 184 Step 4 — Create the Architecture Model 185 Step 5 — Determine the Architecture Implementation Phases 186 Step 6 — Design and Specify the Subsystems 187 Step 7 — Create the Application Architecture Plan Document 187 Step 8 — Review the Draft 187 Example Application Architecture Plan Outline and Model 188 Select Products 191 Keep a Business Focus 191 Major DW/BI Evaluation Areas 192 Evaluate Options and Choose a Product 192 Step 1 — Understand the Purchasing Process 193 Step 2 — Develop the Product Evaluation Matrix 193 Step 3 — Conduct Market Research 194 Step 4 — Narrow Your Options to a Short List 196 Step 5 — Evaluate the Candidates 197 Step 6 — Recommend a Product 201 Step 7 — Trial 201 Step 8 — Contract Negotiations 201 Considerations for the Back Room and Presentation Server 202 Hardware Platform 202 DBMS Platform 203 ETL Tool 204 Considerations for the Front Room 205 Manage the Metadata 207 Appoint the Metadata Manager 207 Create the Metadata Strategy 208 Secure the System 210 Secure the Hardware and Operating System 211 Secure the Development Environment 211 Secure the Network 211 Network Components 212 xx Contents Chapter 6 Encryption 214 Authenticate the Users 215 Secure the Data 215 Provide Open Access for Internal Users 215 Itemize Sensitive Data 216 Minimize or Mask Sensitive Data 216 Secure the Data Access 217 Monitor Usage and Ensure Compliance 220 Plan for Backup and Recovery 220 Create the Infrastructure Map 221 Install the Hardware and Software 224 Conclusion 226 Managing the Effort and Reducing Risk 226 Assuring Quality 227 Key Roles 227 Key Deliverables 228 Estimating Considerations 228 Creating the Architecture Plan 228 Selecting Products 229 Metadata 229 Security 229 Website Resources 229 Task List 230 Introducing Dimensional Modeling 233 Making the Case for Dimensional Modeling 234 What Is Dimensional Modeling? 234 What about Normalized Modeling? 235 Benefits of Dimensional Modeling 237 Dimensional Modeling Primer 238 Fact Tables 238 Fact Table Keys 240 Fact Table Granularity 240 Dimension Tables 241 Dimension Table Keys 243 Conformed Dimensions 244 Four-Step Dimensional Design Process 246 Step 1 — Choose the Business Process 246 Step 2 — Declare the Grain 246 Step 3 — Identify the Dimensions 247 Step 4 — Identify the Facts 247 Enterprise Data Warehouse Bus Architecture 248 Planning Crisis 248 Bus Architecture 249 Value Chain Implications 250 Common Matrix Mishaps 252 Taking the Pledge 253 Contents xxi More on Dimensions 253 Date and Time 253 Surrogate Date Keys 254 Time of Day 255 Date/Timestamps 255 Multiple Time Zones 256 Degenerate Dimensions 256 Slowly Changing Dimensions 257 Type 1: Overwrite the Dimension Attribute 257 Type 2: Add a New Dimension Row 258 Type 3: Add a New Dimension Attribute 258 Mini-Dimensions: Add a New Dimension 259 Hybrid Slowly Changing Dimension Techniques 261 Role-Playing Dimensions 262 Junk Dimensions 263 Snowflaking and Outriggers 265 Handling Hierarchies 268 Fixed Hierarchies 268 Variable Depth Hierarchies via Bridge Tables 268 Many-Valued Dimensions with Bridge Tables 270 More on Facts 273 Three Fundamental Grains 273 Transaction Fact Tables 273 Periodic Snapshot Fact Tables 274 Accumulating Snapshot Fact Tables 274 Facts of Differing Granularity and Allocation 276 Multiple Currencies and Units of Measure 278 Factless Fact Tables 280 Consolidated Fact Tables 281 Fables and Falsehoods About Dimensional Modeling 282 Fables Caused by Focusing on Departmental Reports 282 Fables Caused by Premature Summarization 284 Fables Caused by Overvaluing Normalization 285 Conclusion 286 Chapter 7 Designing the Dimensional Model 287 Modeling Process Overview 288 Get Organized 289 Identify Design Participants 289 Revisit the Requirements 292 Use Modeling Tools 293 Establish Naming Conventions 295 Provide for Source Data Research and Profiling 296 Obtain Facilities and Supplies 297 Recall the Four-Step Modeling Process 297 Step 1 — Choose the Business Process 298 Step 2 — Declare the Grain 298 xxii Contents Step 3 — Identify the Dimensions 299 Step 4 — Identify the Facts 301 Design the Dimensional Model 301 Build the High Level Dimensional Model 302 Conduct the Initial Design Session 302 Document the High Level Model Diagram 303 Identify the Attributes and Metrics 304 Develop the Detailed Dimensional Model 305 Identify the Data Sources 305 Establish Conformed Dimensions 309 Identify Base Facts and Derived Facts 310 Document the Detailed Table Designs 311 Update the Bus Matrix 314 Identify and Resolve Modeling Issues 314 Review and Validate the Model 316 Perform IT Data Model Review 318 Review with Core Users 319 Present to the Business Users 319 Finalize the Design Documentation 320 Embrace Data Stewardship 321 Conclusion 322 Managing the Effort and Reducing Risk 323 Assuring Quality 323 Key Roles 323 Key Deliverables 324 Estimating Considerations 324 Website Resources 324 Task List 325 Chapter 8 Designing the Physical Database and Planning for Performance 327 Develop Standards 328 Follow Naming Conventions 329 To Null or Not to Null? 330 Place Staging Tables 330 Develop File Location Standards 331 Use Synonyms or Views for User Accessible Tables 331 Primary Keys 332 Foreign Keys 334 Develop the Physical Data Model 335 Design the Physical Data Structure 335 Finalize the Source-to-Target Map 336 Star versus Snowflake 338 Use a Data Modeling Tool 340 Develop Initial Sizing Estimates 340 Build the Development Database 343 Design Processing Data Stores 343 Chapter 9 Contents xxiii Develop the Initial Index Plan 344 Indexing and Query Strategy Overview 345 B-Tree Index 345 Clustered Index 345 Bitmapped Index 346 Other Index Types 346 Star Schema Optimization 347 Indexing Dimension Tables 347 Indexing Fact Tables 348 Indexing for Loads 349 Indexing for OLAP 349 Analyze Tables and Indexes after the Load 349 Design the OLAP Database 350 OLAP Data Granularity and Drillthrough 350 Perfecting the OLAP Dimensions 351 Defining OLAP Calculations 352 Build the Test Database 352 Design Aggregations 353 Deciding How to Aggregate 353 Deciding What to Aggregate 354 Maintaining Aggregations 355 Finalizing Indexes 357 Design and Build the Database Instance 357 Memory 358 Block Size 358 Save the Database Build Scripts and Parameter Files 358 Develop the Physical Storage Structure 359 Compute Table and Index Sizes 359 Develop the Partitioning Plan 360 Set up Storage 361 Fault Tolerance 362 Storage Area Networks 362 Configuration of Volumes and Drives 362 Conclusion 363 Managing the Effort and Reducing Risk 364 Assuring Quality 364 Key Roles 365 Key Deliverables 365 Estimating Considerations 365 Website Resources 366 Task List 367 Introducing Extract, Transformation, and Load 369 Round Up the Requirements 370 Business Needs 370 Compliance 371 Data Quality 371 xxiv Contents Security 372 Data Integration 372 Data Latency 373 Archiving and Lineage 373 User Delivery Interfaces 373 Available Skills 374 Legacy Licenses 374 The 34 Subsystems of ETL 374 Extracting Data 375 Subsystem 1 — Data Profiling 375 Subsystem 2 — Change Data Capture System 376 Subsystem 3 — Extract System 378 Cleaning and Conforming Data 380 Improving Your Data Quality Culture and Processes 380 Subsystem 4 — Data Cleansing System 381 Quality Screens 382 Responding to Quality Events 383 Subsystem 5 — Error Event Schema 383 Subsystem 6 — Audit Dimension Assembler 385 Subsystem 7 — Deduplication System 386 Subsystem 8 — Conforming System 386 Delivering Data for Presentation 387 Subsystem 9 — Slowly Changing Dimension Manager 387 Type 1: Overwrite 389 Type 2: Create a New Row 390 Type 3: Add a New Column 391 Hybrid: Combination of Types 391 Subsystem 10 — Surrogate Key Generator 392 Subsystem 11 — Hierarchy Manager 393 Subsystem 12 — Special Dimensions Manager 393 Subsystem 13 — Fact Table Builders 395 Transaction Grain Fact Table Loader 396 Periodic Snapshot Fact Table Loader 396 Accumulating Snapshot Fact Table Loader 397 Subsystem 14 — Surrogate Key Pipeline 398 Subsystem 15 — Multi- Valued Dimension Bridge Table Builder 400 Subsystem 16 — Late Arriving Data Handler 400 Subsystem 17 — Dimension Manager System 402 Subsystem 18 — Fact Provider System 402 Subsystem 19 — Aggregate Builder 403 Subsystem 20 — OLAP Cube Builder 404 Subsystem 21 — Data Propagation Manager 404 Managing the ETL Environment 405 Subsystem 22 — Job Scheduler 406 Subsystem 23 — Backup System 407 Contents xxv Backup 407 Archive and Retrieval 408 Subsystem 24 — Recovery and Restart System 409 Subsystem 25 — Version Control System 410 Subsystem 26 — Version Migration System 410 Subsystem 27 — Workflow Monitor 411 Subsystem 28 — Sorting System 412 Subsystem 29 — Lineage and Dependency Analyzer 412 Subsystem 30 — Problem Escalation System 413 Subsystem 31 — Parallelizing/Pipelining System 414 Subsystem 32 — Security System 415 Subsystem 33 — Compliance Manager 415 Subsystem 34 — Metadata Repository Manager 417 Real Time Implications 417 Real Time Triage 417 Real Time Tradeoffs 419 Real Time Partitions in the Presentation Server 421 Transaction Grain Real Time Partition 421 Periodic Snapshot Real Time Partition 422 Conclusion 423 Chapter 10 Designing and Developing the ETL System 425 ETL Process Overview 425 Getting Started 426 Develop the ETL Plan 428 Step 1 — Draw the High Level Plan 428 Step 2 — Choose an ETL Tool 429 Step 3 — Develop Default Strategies 430 Step 4 — Drill Down by Target Table 432 Ensure Clean Hierarchies 432 Develop Detailed Table Schematics 434 Develop the ETL Specification Document 435 Develop a Sandbox Source System 436 Develop One-Time Historic Load Processing 437 Step 5 — Populate Dimension Tables with Historic Data 438 Populate Type 1 Dimension Tables 438 Dimension Transformations 439 Dimension Table Loading 443 Load Type 2 Dimension Table History 445 Populate Date and Other Static Dimensions 446 Step 6 — Perform the Fact Table Historic Load 447 Historic Fact Table Extracts 447 Fact Table Transformations 448 Fact Table Loading 454 Test, Test, and Test Again 455 Develop Incremental ETL Processing 456 Step 7 — Dimension Table Incremental Processing 456 xxvi Contents Dimension Table Extracts 456 Identify New and Changed Dimension Rows 457 Process Changes to Dimension Attributes 458 Step 8 — Fact Table Incremental Processing 459 Fact Table Extract and Data Quality Checkpoint 460 Fact Table Transformations and Surrogate Key Pipeline 461 Late Arriving Facts and the Surrogate Key Pipeline 462 Incremental Fact Table Load 463 Speed Up the Load Cycle 464 Step 9 — Aggregate Table and OLAP Loads 465 Step 10 — ETL System Operation and Automation 466 Schedule Jobs 466 Handle Predictable Exceptions and Errors Automatically 467 Handle Unpredictable Errors Gracefully 467 Maintain Database Objects 468 Develop and Test ETL Automation 468 Conclusion 469 Managing the Effort and Reducing Risk 469 Assuring Quality 470 Key Roles 470 Key Deliverables 471 Estimating Considerations 471 Website Resources 471 Task List 472 Chapter 11 Introducing Business Intelligence Applications 473 Importance of Business Intelligence Applications 474 Analytic Cycle for Business Intelligence 476 Stage 1: Monitor Activity 476 Stage 2: Identify Exceptions 477 Stage 3: Determine Causal Factors 477 Stage 4: Model Alternatives 478 Stage 5: Take Action and Track Results 478 More Implications of the Analytic Cycle 479 Types of Business Intelligence Applications 479 Direct Access Query and Reporting Tools 480 Query Formulation 481 Analysis and Presentation Capabilities 483 User Experience 485 Technical Features 486 Standard Reports 487 Analytic Applications 488 Pre-Built Analytic Applications 489 Read /Write Analytic Applications 490 Dashboards and Scorecards 490 Operational Business Intelligence 493 Data Mining 494 Contents xxvii Data Mining Overview 494 Data Mining in the Applications Architecture 498 Navigating Applications via the BI Portal 499 Density Considerations 501 Navigation Structure Based on Business Processes 502 Additional Portal Functions 502 Application Interface Alternatives 503 Conclusion 504 Chapter Ί 2 Designing and Developing Business Intelligence Applications 505 Business Intelligence Application Resource Planning 506 Role of the BI Application Developer 506 Who Does the BI Applications Job? 506 Lifecycle Timing 507 Business Intelligence Application Specification 508 Create Application Standards and Templates 508 Determine Naming Standards 508 Create the Application Templates 509 Create Dashboard and Analytic Application Templates 512 Determine the Initial Application Set 512 Identify Report Candidates 512 Consolidate the Candidate List 514 Prioritize the Report List 514 Develop Detailed Application Specifications 515 Specify Application Content 517 Design the Navigation Framework and Portal 519 Review and Validate the Applications and Model 520 Review with the Business 521 Business Intelligence Application Development 522 Prepare for Application Development 522 Install and Test the BI Tools 522 Validate Your BI Application Interface Strategy 523 Set Up User Security 523 Set Up the Report Process Metadata System 524 Build the Applications 524 Follow the Core Process 525 Design and Develop Analytic Applications 527 Design and Develop Operational BI Applications 527 Include Data Mining Models 529 Validate the Data and Data Model 530 Create the Navigational BI Portal 530 Set Up Report Scheduling 532 Test and Verify the Applications and Data 532 Complete the Documentation 534 Plan for Deployment 534 Business Intelligence Application Maintenance 534 xxviii Contents Chapter 13 Conclusion 535 Managing the Effort and Reducing Risk 535 Assuring Quality 536 Key Roles 536 Key Deliverables 537 Estimating Considerations 537 BI Application Specification 537 Development 538 Website Resources 538 Task List 539 Deploying and Supporting the DW/BI System 541 System Deployment 542 Pre-Deployment Testing 543 System Testing Procedures 543 Data Quality Assurance Testing 546 Operations Process Testing 547 Live Testing 548 Performance Testing 549 Usability Testing 552 Desktop Readiness and Configuration 553 Deployment 554 Relational Database Deployment 554 ETL Deployment 556 OLAP Database Deployment 556 Report Deployment 557 Documentation and Training 558 Core Documentation 558 Business Process Dimensional Model Descriptions 558 Table and Column Descriptions 559 Report Descriptions 559 Additional Documentation 559 User Training 560 Design and Approach 560 Develop Training Materials 561 Create a Training Database 562 Plan for the Level of Effort 562 Maintenance and Support 563 Manage the Front Room 563 Provide User Support 563 Maintain the BI Portal 565 Manage Security 566 Monitor Usage 566 Report on Usage 567 Manage the Back Room 567 Support Data Reconciliation 568 Execute and Monitor the ETL System 568 Contents xxix Monitor Resources 569 Manage Disk Space 570 Tune for Performance 570 Backup and Recovery 571 Long Term Archiving 573 Conclusion 573 Managing the Effort and Reducing Risk 574 Assuring Quality 575 Key Roles 575 Key Deliverables 575 Estimating Considerations 576 Task List 577 Chapter 14 Expanding the DW/BI System 579 Manage the Existing Environment 579 Reach the Business Users 580 Manage Up 580 Measure and Market Your Success 581 Evaluate ROI 581 Monitor Success and Service Metrics 583 Proactively Market the Data Warehouse 584 Communicate Constantly 584 Prepare for Growth and Evolution 585 Assess Your Current Environment 586 Prioritize Opportunities for Growth 587 Prioritize Minor Enhancements 587 Prioritize Major Initiatives 587 Manage Iterative Growth 588 Conclusion 590 Managing the Effort and Reducing Risk 590 Assuring Quality 590 Key Roles 591 Key Deliverables 591 Estimating Considerations 591 Glossary 593
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author	Kimball, Ralph 1944- Ross, Margy 1959- Thornthwaite, Warren 1957- Mundy, Joy 1961- Becker, Bob
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id	DE-604.BV023646322
illustrated	Illustrated
indexdate	2024-08-05T08:40:47Z
institution	BVB
isbn	0470149779 9780470149775
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-017242668
oclc_num	173640986
open_access_boolean
owner	DE-523 DE-M347 DE-473 DE-BY-UBG DE-634 DE-11 DE-384 DE-861 DE-2070s DE-859 DE-573 DE-863 DE-BY-FWS DE-526 DE-M158 DE-703 DE-1052
owner_facet	DE-523 DE-M347 DE-473 DE-BY-UBG DE-634 DE-11 DE-384 DE-861 DE-2070s DE-859 DE-573 DE-863 DE-BY-FWS DE-526 DE-M158 DE-703 DE-1052
physical	XXXIV, 636 S. Illustrationen
publishDate	2008
publishDateSearch	2008
publishDateSort	2008
publisher	Wiley
record_format	marc
spellingShingle	Kimball, Ralph 1944- Ross, Margy 1959- Thornthwaite, Warren 1957- Mundy, Joy 1961- Becker, Bob The data warehouse lifecycle toolkit Datenverarbeitung Business intelligence Data processing Data warehousing Database design Data-Warehouse-Konzept (DE-588)4406462-7 gnd
subject_GND	(DE-588)4406462-7
title	The data warehouse lifecycle toolkit
title_auth	The data warehouse lifecycle toolkit
title_exact_search	The data warehouse lifecycle toolkit
title_full	The data warehouse lifecycle toolkit Ralph Kimball ...
title_fullStr	The data warehouse lifecycle toolkit Ralph Kimball ...
title_full_unstemmed	The data warehouse lifecycle toolkit Ralph Kimball ...
title_short	The data warehouse lifecycle toolkit
title_sort	the data warehouse lifecycle toolkit
topic	Datenverarbeitung Business intelligence Data processing Data warehousing Database design Data-Warehouse-Konzept (DE-588)4406462-7 gnd
topic_facet	Datenverarbeitung Business intelligence Data processing Data warehousing Database design Data-Warehouse-Konzept
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017242668&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
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