Example Data Warehouse Identifying Sources 45 Which Salesperson Is Making the Most Sales? Identifying Relevant Information To answer the question, “Which salesperson is making the most sales?”, the data warehousing team decided to design a report that lists total sales by employee. The following display shows an example of such a report. Display 5.1 Total Sales by Employee Report The next step is to identify how such a report could be created. Identifying Sources The data warehouse team examined existing tables to determine if they could be used to the create the report shown in the previous display. They identified several tables that could be used. These tables are described in the following sections. Source for Staff Information The STAFF table contains information about employees, such as name, ID, department, supervisor, and salary, as shown in the following display. Display 5.2 The STAFF Table 46 Identifying Sources Chapter 5 Source for Organization Information The following ORGANIZATION table identifies the organization to which an employee belongs. Display 5.3 The ORGANIZATION Table Source for Order Information The following ORDERS table contains information about orders placed with salespersons, including date, salesperson ID, type of order, and customer. Display 5.4 The ORDERS Table Example Data Warehouse Identifying Sources 47 Source for Order Item Information The following ORDER_ITEM table contains information about orders placed with the company, and includes product ID, amount ordered, price of items, and other data. Display 5.5 The ORDER_ITEM Table Source for Customer Information The following CUSTOMER table contains information about the customers who are placing orders with the company. Information includes name, address, birthdate, and other data. Display 5.6 The CUSTOMER Table In reviewing the previous tables, the data warehousing team identified the following issues: The salesperson and salesperson ID must be correlated to determine sales. The sales totals for each order must be correlated with the correct salesperson. The sales for each salesperson must be totaled. Some information does not exist in current source tables. New columns and tables must be created. 48 Identifying Targets Chapter 5 The next step is to specify the new tables that must be created in order to produce the desired reports. Identifying Targets To simplify the SAS Data Integration Studio job that will be used to create the desired report, the team decided to combine certain columns from existing tables into a smaller number of new tables: A new table will be created that joins the CUSTOMER, ORDERS, and ORDER_ITEMS tables: the ORDER_FACT table. A new table will be created that joins the STAFF and ORGANIZATION tables: the ORGANIZATION_DIM table. In order to answer the question of who made the most sales, the two new tables will be combined to create a third new table on which the report will be based. The third new table will be called Total_Sales_by_Employee. By combining tables, the warehouse team can easily answer the specified question, as well as create a diverse range of reports to answer other business questions. Details about each new table are provided in the following sections. Target That Combines Order Information The ORDER_FACT table is created by joining the CUSTOMER, ORDERS, and ORDER_ITEMS tables. The new table will include all order data, including salesperson ID, customer, price, and quantity. Target That Combines Organization Information The ORGANIZATION_DIM table is created by joining the STAFF and ORGANIZATION tables. The new table will include all employee information including name, ID, salary, department, and managers. Target That Lists Total Sales by Employee The Total_Sales_by_Employee table is created by joining the ORDER_FACT table and ORGANIZATION_DIM table. It will be used to produce a report similar to the draft report shown in Display 5.1 on page 45. “Example: Using the Target Table Designer to Register SAS Tables” on page 140 describes how to specify metadata for the Total_Sales_by_Employee table. “Example: Creating a Job That Joins Two Tables and Generates a Report” on page 150 describes the job that uses the Total_Sales_by_Employee table to produce the report. Creating the Report For an example of the report can be created in SAS Data Integration Studio, see “Example: Creating a Job That Joins Two Tables and Generates a Report” on page 150. Example Data Warehouse Identifying Sources 49 What Are the Time and Place Dependencies of Product Sales? Identifying Relevant Information To answer the question, “What are the time and place dependencies of product sales?”, the data warehousing team decided to design a report that reports sales across a time dimension and a geographic dimension. The following display shows an example of such a report. Display 5.7 Time and Place Dependencies for Sales Report The next step is to identify how such a report could be created. Identifying Sources Further questioning of the executive team revealed that it would be helpful to track sales across a customer dimension and an internal organization dimension as well as across the dimensions of time and geography. Questions that require multiple dimensions to be analyzed together can often be answered with online analytical processing (OLAP). Accordingly, the data warehousing team concluded that the question, “What are the time and place dependencies of product sales?”, could be answered most efficiently with OLAP. The data warehouse team examined existing tables to determine whether they could be used as inputs to an OLAP data store that would produce reports similar to the report shown in Display 5.7 on page 49. They identified several tables that could be used. These tables are described in the following sections. Sources Related to Customers The following tables can contribute to the customer dimension of the OLAP data store: CUSTOMER table CUSTOMER_TYPE table . example of the report can be created in SAS Data Integration Studio, see “Example: Creating a Job That Joins Two Tables and Generates a Report” on page 150. Example Data Warehouse Identifying Sources. created in order to produce the desired reports. Identifying Targets To simplify the SAS Data Integration Studio job that will be used to create the desired report, the team decided to combine. Data Warehouse Identifying Sources 45 Which Salesperson Is Making the Most Sales? Identifying Relevant Information To answer the question, “Which salesperson is making the most sales?”, the data warehousing