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ORDER_FACTS day_ key 2012 product_ customer_ sales_ key key group_key 3721 4791 1 order_ dollars 1,000
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Ann Davis Henry Perez
East East
Figure 9-4 A bridge table associates any number of salespeople with an order
9 Multi-Valued Dimensions and Bridges 201
This design has obvious implications for the ETL process. As noted, the process must create and manage groupings. Each time a collaboration occurs, it will be necessary to come up with a group_key in order to load the fact. If the group has collaborated in the past, the same group_key can be used for the new fact. If it is a new collaboration, a group key must be assigned, and appropriate rows must be added to the sales_group table. Unlike the simplification option, this approach can accommodate groups of any size. If three salespeople collaborate on an order, a group_key is created for the collaboration and three rows are added to the group one for each member. If a group of 15 works together, a group is created and 15 rows are added. A group is also needed when a sale takes place involving only one salesperson. The group table will contain one row, associating the group_key with the single group member. Every fact will refer to a group. This solution makes it easy to address some of the questions that posed challenges under the design that simplified the relationship. Computing total order dollars for a salesperson is easy; the salesrep table is constrained for the salesperson in question, and joined to the group table, which in turn joins to the fact table. Total sales for each salesperson can be accomplished in the same way, grouping data by salesperson_name.
You may have noticed that the relationship between the fact table and the bridge table in Figure 9-4 is many-to-many. That is not a mistake. If Ann and Henry collaborate again, the same group number can be used. Group number 1 will have multiple rows in the fact table, one for each order, and multiple rows in the group table, one for Ann and one for Henry. This works just fine most of the time but can confuse software tools which assume every join will leverage a primary key foreign key association. We will look at what to do if your modeling, database, or reporting tool balks at this relationship shortly. First, though, it is necessary to address a more important issue.
Bridges and Double-Counting
While the bridge table offers increased flexibility and simplifies many reporting challenges, there is a downside (there s always a downside). By allowing a fact to refer to multiple rows in a dimension table, you open the door to the possibility of double-counting, triplecounting, or worse. NOTE For the sake of simplicity, this book uses double-counting to describe any situation where a fact may be counted more than once. As you will see, in any particular situation, the error may be more severe. In Figure 9-3, for example, the same order is associated with both Ann and Henry. If you query orders by region, the same order will be counted twice once for Ann and once for Henry. If three salespeople had collaborated, the order would be triple-counted, and so forth. Countermeasures can be employed to reduce the possibility of double-counting, but sometimes it is precisely what is wanted.
Part III
TIP Compared to a solution that simplifies a many-to-many relationship, using a bridge table offers increased flexibility and simplifies reporting challenges.
PART III
Dimension Design
When Double-Counting Is Wanted It may seem nonsensical at first, but sometimes this double-counting is actually a good thing. For example, it may be useful to have a report that shows order_dollars by salesperson. Such a report shows the sales volume associated with each salesperson. In this case, Ann and Henry s joint order should be counted in both their results. This kind of report provides insight into the impact that a particular member of the dimension table has on the facts. Similar examples might include producing a report showing the total claim dollars by party, the total number of office visits per medical diagnosis, and so on. While the fact may be counted more than once, it is legitimately associated with each dimension instance. On the other hand, it would be a serious error to take that information and produce a grand total. Ann and Henry may each have participated in $1,000 worth of orders, but this does not mean that total order dollars are $2,000. Unfortunately, it is all too easy with most reporting tools to request a grand total.
TIP When a bridge table is present, each fact may be associated with more than one dimension row. This makes double-counting a very real possibility. Sometimes this is intended, but it is easy to err in constructing a query or producing totals in a report. Avoiding grand totals is not sufficient to stay out of trouble. It is necessary to group query results by individual members of the dimension table. This is sometimes referred to as the grain of the dimension table. Grouping results at any other level of summarization may result in double-counting. For example, Ann and Henry have the same region value in the salesrep table. The following query joins order_facts to salesrep via the bridge, and groups by region:
SELECT salesrep.region, sum (order_facts.order_dollars) FROM salerep, sales_group, order_facts WHERE order_facts.sales_group_key = sales_group.sales_group_key AND sales_group.salesrep_key = salesrep.salesrep_key GROUP BY salesrep.region
When the RDBMS executes this query, it will find two rows in the salesrep for the single order booked by Ann and Henry. In order to join the rows, it will repeat the order, once for Ann and once for Henry. After that, the aggregation by region will be computed. This causes Ann and Henry s joint order to be counted twice within region East. TIP The only safe way to construct an impact report is to group by a column in the dimension that will have a unique value for each member of the group. Most often, this will be the natural key.
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