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Using the Wal-Mart Model
1st Edition - August 18, 2000
Author: Paul Westerman
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At 70 terabytes and growing, Wal-Mart's data warehouse is still the world's largest, most ambitious, and arguably most successful commercial database. Written by one of the key… Read more
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At 70 terabytes and growing, Wal-Mart's data warehouse is still the world's largest, most ambitious, and arguably most successful commercial database. Written by one of the key figures in its design and construction, Data Warehousing: Using the Wal-Mart Model gives you an insider's view of this enormous project. Continuously drawing from this example, the author teaches you the general principles and specific techniques you need to understand to be a valuable part of your organization's own data warehouse project, however large or small. You'll emerge with a practical understanding of both the business and technical aspects of building a data warehouse for storing and accessing data in a strategically useful way.
What further sets this book apart is its focus on the informational needs of retail companies-including both market and organizational issues that affect the data's collection and use. If retail is your field, this book will prove especially valuable as you develop and implement your company's ideal data warehouse solution.
* Written by a member of the team of four engineers who designed and built the Wal-Mart Data Warehouse database, a team whose database design was recognized internally in 1991 by Wal-Mart with the company's Team Innovational Technical award.* Provides essential information for project managers, consultants, data warehouse managers, and data architects.* Takes an in-depth look at a wide range of technical issues, including architecture, construction approaches, tool selection, database system selection, and maintenance.* Addresses issues specific to retail business: vendors, inventory, sales analysis, geography, article categories, and more.* Explains how to determine business requirements at the outset of the project-and how to develop return on investment analyses after the warehouse has been brought online.
FOREWORDACKNOWLEDGMENTSCHAPTER 1 - WHAT IS DATA WAREHOUSING?EVOLUTION LEADING UP TO THE DATA WAREHOUSE Executive Information Systems Direct SQL Access Data Warehouse Data Mart Enterprise Data Warehouse Operational Data Store Data Warehouse is a ToolAPPLYING THE DATA WAREHOUSE CONCEPTBEYOND ENTERPRISE DATA WAREHOUSECHAPTER 2 - PROJECT PLANNINGBEFORE YOU START Clear Focus on the Business Business Sponsorship Long-Term Vision Short-Term Plan Assigning a Responsible Leader Effective Communications Providing Something New Partnership PlanningPLANNING FOR THE PROJECT LIFE CYCLE Analytical Phase Gathering and documenting the business requirements Logical Design of the Database and Processes Determine the Source of the Data Determine Technical Readiness Select Tools Create an Implementation Timeline and Resources Required Construction Phase Post-ProductionCHAPTER 3 - BUSINESS EXPLORATIONTHE BUSINESS EXPLORATION PROCESS Defining the Goals Gathering the Business Questions Prioritizing the Business Questions Defining the Business QuestionsCHAPTER 4 - BUSINESS CASE STUDY AND ROI ANALYSISBUSINESS CASE STUDY Business User Visions One-to-one Discussions Business Users Profiles Potential Pay-back Accumulated Potential Pay-back Summary Projected Investment Costs with ROI Forecast Resource PlanROI ANALYSIS Data Warehouse Background One-to-one Discussions Business Users Profiles Actual Pay-back Actual Accumulated and Projected Pay-back Summary Investment Costs with ROI Conclusion Next Step Implementation PlanCHAPTER 5 - ORGANIZATIONAL INTEGRATIONCHAPTER 6 - TECHNOLOGYTHE FRONT-END TOOLTHE DATABASE TOOL Database Compatibility Database Maintenance Reliability Minimal Indexing Dynamic Reorganization Database Linear GrowthCHAPTER 7 - TECHNOLOGY - DATABASE MAINTENANCECAPTURING, EXTRACTING, AND TRANSFERRING THE SOURCE DATAUPDATE FREQUENCYLOADING THE DATA WAREHOUSE Initial Load Append Load Processes Update Processes Delete ProcessesBACKUP/RECOVERYMESSAGINGCHAPTER 8 - TECHNICAL CONSTRUCTION OF THE WAL-MART DATA WAREHOUSEPRE-CONSTRUCTIONTHE FIRST IMPLEMENTATION The Database Design The Update Process GUI ApplicationCHAPTER 9 - POST-IMPLEMENTATION OF THE WAL-MART DATA WAREHOUSETHE ROI SURROUNDED BY CHAOSINTEGRATING OPERATIONAL APPLICATIONS Replenishment Distribution via Traits Perpetual InventoryCHAPTER 10 - STORE OPERATIONS SAMPLE ANALYSESBASIC STORE OPERATIONS INFORMATION NEEDSSTORE SALES Store Sales Data Elements Store Sales Sample ReportCOMPARABLE STORE SALES Comparable Store Sales Data Elements Comparable Store Sample ReportFLASH STORE SALES Flash Store Sales Data Elements Flash Store Sales Sample ReportDEPARTMENTAL STORE SALES Departmental Store Sales Data Elements Departmental Store Sales Sample ReportPLANNED SALES Planned Sales Data Element Planned Sales Sample ReportCOMPETITIVE STORE SALES Competitive Store Sales Data Elements Competitive Store Sales Sample ReportCHAPTER 11 - MERCHANDISING SAMPLE ANALYSESBASIC MERCHANDISING INFORMATION NEEDSBASIC ARTICLE POS ANALYSIS Basic Article POS Data Elements Basic Article Sample ReportTOP 25, BOTTOM 25 ANALYSIS Top 25, Bottom 25 Data Elements Top 25, Bottom 25 Sample ReportARTICLE INVENTORY ANALYSIS Article Inventory Data Elements Article Inventory Sample ReportARTICLE SELLING VS. PLANNED SELLING Article Selling vs. Planned Data Elements Article Selling vs. Planned Sample ReportFAST SELLING ARTICLE ANALYSIS Fast Selling Data Elements Fast Selling Sample ReportSLOW SELLING ARTICLES Slow Selling Data Elements Slow Selling Sample ReportVENDOR PERFORMANCE ANALYSIS Vendor Performance Data Elements Vendor Performance Sample ReportCATEGORY PERFORMANCE ANALYSIS Category Performance Data Elements Category Performance Sample ReportARTICLE SELLING BY GEOGRAPHIC LOCATIONS Article Selling by Geographic Locations Data Elements Article Selling by Geographic Locations Sample ReportCOMPARATIVE ARTICLE SALES Comparative Article Sales Data Elements Comparative Article Sales Sample ReportSTORE AND ARTICLE GROUPING Store and Article Grouping Data Elements Store and Article Grouping Sample ReportBASIC AFFINITY SELLING Basic Affinity Selling Data Elements Basic Affinity Selling Sample ReportOUT-OF-STOCK ANALYSIS Out-of-Stock Data Elements Out of Stock Sample ReportCONCLUSIONAPPENDIX A - RETAIL FORMULAS INVENTORY FORMULAS KEY PERCENTAGE RELATIONSHIPS MARGIN & PROFIT FORMULASBIBLIOGRAPHY
No. of pages: 297
Published: August 18, 2000
Imprint: Morgan Kaufmann
eBook ISBN: 9780080503721
Paul Westerman is a Global Marketing Manager for Compaq Computers, Inc. He began his retail career with Wal-Mart, where he was one of the four people responsible for designing and building the Wal-Mart data warehouse-still the world's largest. Since then, Paul has played a key role in many very large data warehouses projects around the world-in the retail industry, telephone industry, and other areas-and has spoken to audiences around the world about the benefits of applying the data warehouse technology to business. He holds a BS in Computing and Information Sciences from Oklahoma State University.