Excel Power Pivot & Power Query For Dummies. Michael Alexander
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this point, your diagram will look similar to Figure 2-9. Notice that Power Pivot shows a line between the tables you just connected. In database terms, these are referred to as joins.
FIGURE 2-9: When you create relationships, the Power Pivot diagram shows join lines between tables.
The joins in Power Pivot are always one-to-many joins. This means that when a table is joined to another, one of the tables has unique records with unique index numbers (CustomerID for example), while the other can have many records where index numbers are duplicated.
Notice in Figure 2-9 that the join lines have arrows pointing from a table to another table. The arrows in these join lines will always point to the table that has the duplicated index. In this case, the Customers table contains a unique list of customers, each having its own unique identifier. No CustomerID in that table is duplicated. The Invoice header table has many rows for each CustomerID; each customer can have many invoices.
Managing existing relationships
If you need to edit or delete a relationship between two tables in your data model, you can do so by following these steps:
1 Open the Power Pivot window, select the Design tab, and then select the Manage Relationships command.
2 In the Manage Relationships dialog box, shown in Figure 2-10, click the relationship you want to work with and click Edit or Delete.If you click Edit, the Edit Relationship dialog box (shown in Figure 2-11) appears. The columns used to form the relationship are highlighted. Here, you can redefine the relationship by simply selecting the appropriate columns. You can also use the Active check box to disable or enable the relationship.
FIGURE 2-10: Use the Manage Relationships dialog box to edit or delete existing relationships.
Every relationship must have a field that you designate as the primary key. Primary key fields are necessary in the data model to prevent aggregation errors and duplications. In that light, the Excel data model must impose some strict rules around the primary key.
You cannot have any duplicates or null values in a field being used as the primary key. So the Customers table (refer to Figure 2-9) must have all unique values in the CustomerID field, with no blanks or null values. This is the only way that Excel can ensure data integrity when joining multiple tables.
FIGURE 2-11: Use the Edit Relationship dialog box to adjust the tables and field names that define the selected relationship.
At least one of your tables must contain a field that serves as a primary key — that is, a field that contains only unique values and no blanks.
Using the Power Pivot data model in reporting
After you define the relationships in your Power Pivot data model, it’s essentially ready for action. In terms of Power Pivot, action means analysis with a pivot table. In fact, all Power Pivot data is presented through the framework of pivot tables.
In Chapter 3, you dive deep into the workings of pivot tables. For now, dip just a toe in and create a simple pivot table from your new Power Pivot data model:
1 Activate the Power Pivot window, select the Home tab, and then click the Pivot Table command button.
2 Specify whether you want the pivot table placed on a new worksheet or an existing sheet.
3 Build out the needed analysis just as you would build out any other standard pivot table, using the Pivot Field List.
The pivot table shown in Figure 2-12 contains all tables in the Power Pivot data model. Unlike a standard pivot table, where you can use fields from only one table, the relationships defined the internal data model allow you to use any of the fields from any of the tables. With this configuration, you have a powerful cross-table analytical engine in the form of a familiar pivot table. Here, you can see that you’re calculating the average unit price by customer.
FIGURE 2-12: You now have a Power Pivot-driven pivot table that aggregates across multiple tables.
In the days before Power Pivot, this analysis would have been a bear to create. You would have had to build VLOOKUP formulas to get from Customer Number to Invoice Number, and then another set of VLOOKUP formulas to get from Invoice Numbers to Invoice Details. And after all that formula building, you still would have had to find a way to aggregate the data to the average unit price per customer.
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