Data Models can’t use composite keys: a table must always have exactly one column that uniquely identifies each row in the table. Other relationship types are not supported.Ī composite key is composed of more than one column. You’re also restricted to creating one-to-one and one-to-many relationships. In a Data Model, you cannot create a table relationship if the key is a composite key. If you import data from a relational database, by default Excel chooses the foreign key from one table and the corresponding primary key from the other table. However, you can use any column that has unique values for the lookup column. If a table has both a primary and alternate key, you can use either one as the basis of a table relationship. The foreign key is referred to as the source column or just column. In our example, a relationship would be defined between CustomerID in the Orders table (the column) and CustomerID in the Customers table (the lookup column). In a Data Model, the primary key or alternate key is referred to as the related column. For example, an Employees table might store an employee ID and a social security number, both of which are unique.įoreign key: a column that refers to a unique column in another table, such as CustomerID in the Orders table, which refers to CustomerID in the Customers table. Primary key: uniquely identifies a row in a table, such as CustomerID in the Customers table.Īlternate key (or candidate key): a column other than the primary key that is unique. Though there are many types of keys, these are the most important for our purpose here: Understanding the purpose of each key can help you manage a multi-table Data Model that provides data to a PivotTable, PivotChart, or Power View report. A key is typically column with special properties. In a relational database, there are several types of keys. One could be CustomerID and another CustomerNumber, as long as all of the rows in the Orders table contain an ID that is also stored in the Customers table. In the example, the column names are the same, but this is not a requirement. For example, you could relate a Customers table with an Orders table if each contains a column that stores a Customer ID. Relationships are based on columns in each table that contain the same data. If you import tables from multiple sources, you can manually create relationships as described in Create a relationship between two tables. For more information, see Automatic Detection and Inference of Relationships in this article. If you use the Power Pivot add-in to import tables from the same database, Power Pivot can detect the relationships between the tables based on the columns that are in, and can reproduce these relationships in a Data Model that it builds behind the scenes. See Create a Data Model in Excel for details. You can also use the Power Pivot add-in to create or manage the model. Relationships exist within a Data Model-one that you explicitly create, or one that Excel automatically creates on your behalf when you simultaneously import multiple tables. For example, a database that you import might represent order data by using three related Digital This is the approach used in relational databases like SQL Server. One solution to this problem is to split the data into multiple tables and define relationships between those tables. Storage is cheap, but if the e-mail address changes you have to make sure you update every row for that customer. This approach can work, but it involves storing a lot of redundant data, such as the customer e-mail address for every order. You could track all the data in a single table having a structure like Movie-Maker To see why relationships are useful, imagine that you track data for customer orders in your business. A relationship is a connection between two tables that contain data: one column in each table is the basis for the relationship. Add more power to your data analysis by creating relationships amogn different tables.
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