Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Chapter 6 The Data Warehouse Jason C. H. Chen, Ph.D. Professor of MIS School of Business Administration Gonzaga University Spokane, WA Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining 6.1 Operational Databases Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Data Modeling and Normalization One-to-One Relationships One-to-Many Relationships Many-to-Many Relationships Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Data Modeling and Normalization First Normal Form Second Normal Form Third Normal Form Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.1 A simple entity- relationship diagram Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining The Relational Model Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining 6.2 Data Warehouse Design Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.2 A data warehouse process model Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Entering Data into the Warehouse Independent Data Mart ETL (Extract, Transform, Load Routine) Metadata Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Structuring the Data Warehouse: The Star Schema Fact Table Dimension Tables Slowly Changing Dimensions Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.3 A star schema for credit cared purchases Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining The Multidimensionality of the Star Schema Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.4 Dimensions of the fact table shown in Figure 6.3 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Additional Relational Schemas Snowflake Schema Constellation Schema Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.5 A constellation schema for credit card purchases and promotions Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Decision Support: Analyzing the Warehouse Data Reporting Data Analyzing Data Knowledge Discovery Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining 6.3 On-line Analytical Processing Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining OLAP Operations Slice A single dimension operation Dice A multidimensional operation Roll-up Aggregation, a higher level of generalization Drill-down A greater level of detail the reverse of a roll-up Rotation View data from a new perspective Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.6 A multidemensional cube for credit card purchases Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Concept Hierarchy A mapping that allows attributes to be viewed from varying levels of detail. Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.7 A concept hierarchy for location Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.8 Rolling up from months to quarters Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining 6.4 Excel Pivot Tables for Data Analysis Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Creating a Simple Pivot Table Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.9 A pivot table template Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Steps 1,2 (p.198) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Steps 2, 3 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 3 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 4 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 5 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 6 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 7 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Result of Step 7 (p.198) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.10 A summary report for income range Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.10 A summary report for income range Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.9 A pivot table template Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 1, 2(bottom of p.198) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 3 (top) and steps 1,2 3 (p.199) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 4 (p.199) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 4 (p.199) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Steps 1,2 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 2 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 3 (p.200) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 3 - continued (p.200) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 3 - continued (p.200) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 3 - continued (p.200) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 3 - result (p.200) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.11 A pie chart for income range Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Pivot Tables for Hypothesis Testing Younger cardholders purchase credit card insurance whereas more senior cardholders do not. Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.12 A pivot table showing age and credit card insurance choice Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Method 1 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.13 Grouping the credit card promotionn data by age Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.14 PivotTable Layout Wizard Method 2- Steps 1,2,3 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Method 2- Step 4 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Steps 4,5 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 6 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 7 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 8 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Result of Method 2 The average age for credit card insurance = no is approximately 41.42, whereas the average age for credit card insurance = yes is approximately 32.33 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Creating a Multidimensional Pivot Table Investigate relationships between the magazine, watch, and life insurance promotions relative to customer gender and income range. Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.15 A credit card promotion cube Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Steps 1,2,3 (p. 206) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Steps 3 (after dragging life insurance promotion to DropData Items Here. ) Continue dragging watch promotion and magazine promotion to DropData Items Here. Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 3 (result) Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Step 4 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Decision Making steps 1-3, p.207 A total of two customers took advantage of the life insurance and magazine promotions but did not purchase the watch promotion. Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Figure 6.16 A pivot table with page variables for credit card promotions Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining Result of p.207 Dr. Chen, Data Mining A/W & Dr. Chen, Data Mining