how to make barcode in vb.net 2010 Part I in Software

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Consider the orders process again. The order_facts table only records rows for orders that have taken place. If a particular customer does not order a particular product from a particular salesperson on a particular day, no row is recorded. This is a good thing. If every combination of dimension values were represented in the fact table, it would quickly accumulate a huge number of rows.
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PART I Fundamentals
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PRODUCT product_key product product_description sku unit_of_measure brand brand_code brand_manager category category_code
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SALESPERSON salesperson_key salesperson salesperson_id territory territory_code territory_manager region region_code region_vp CUSTOMER customer_key customer customer_id headquarters_state billing address billing_city billing_state billing_zip sic_code industry_name ORDER_INFO Degenerate dimensions order_info_key order_type_code order_type_description credit_flag reorder_flag solicited_flag initial_order_flag
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ORDER_FACTS product_key salesperson_key day_key customer_key order_info_key quantity_ordered order_dollars cost_dollars margin_dollars order_id order_line id
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DAY day_key full_date day_of_week_number day_of_week_name day_of_week_abbr day_of_month holiday_flag weekday_flag weekend_flag month_number month_name month_abbr quarter quarter_month year year_month year_quarter fiscal_period fiscal_year fiscal_year_period
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Figure 3-5 Degenerate dimensions define the grain of this fact table
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The data in dimension tables originates in operational systems. In a dimensional data warehouse or stand-alone data mart, it comes directly from the operational system. In a Corporate Information Factory, it is first moved to the enterprise data warehouse, and then to a dimensional data mart. Once information makes its way into a dimension table, it may change in the operational source. For example, a customer s date of birth is updated to correct an error, or a customer s address is updated when they move. Because the downstream star schema uses a surrogate key as the primary key of each dimension table, it does not have to handle changes the same way the source does. The operational system may track the change history of each data element, or it may simply overwrite with the changed values. Regardless, the star schema can respond to each change in whatever manner makes most sense for measuring the overall business process. In every dimensional design, it is crucial to identify how changes in source data will be represented in dimension tables. This phenomenon is referred to as slowly changing dimensions. This term gets its name from the relatively slow rate at which dimensions accumulate changes,
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3 Stars and Cubes 45
at least when compared with fact tables, which accumulate rows at a rapid pace. A variety of responses to changed data elements are possible. In some cases, there may be no analytic value in preserving history. In other cases, it may be critical that historic data be maintained. Figure 3-6 shows a customer record in an order entry system at three different points in time. The record in question is that of customer_id 9900011, which happens to be someone named Sue Johnson. Notice that on January 1, 2007, her date of birth is indicated as March 2, 1961, and she lives in the state of Arizona (AZ). Later, her date of birth has been changed from a date in 1961 to 1971. Still later, this same customer has moved; her state of residence is now California (CA). This operational system has handled both changes in the same way: by overwriting the record for customer_id 9900011. Suppose that this operational system feeds a dimension table in a star schema that tracks orders. Analytic requirements may call for the changes to be treated differently. In the case of Sue s date of birth, the business may consider the change history to be insignificant. As in
January 1, 2007 customer_id: cust_name: cust_birth_date: address_state: (more attributes) 9900011 Johnson, Sue 3/2/1961 AZ ...
January 31, 2007 customer_id: cust_name: cust_birth_date: address_state: (more attributes) 9900011 Johnson, Sue 3/2/1971 AZ ... Sue s date of birth has changed.
May 5, 2009 customer_id: cust_name: cust_birth_date: address_state: (more attributes) 9900011 Johnson, Sue 3/2/1971 CA ... Sue s state has changed.
Figure 3-6
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