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ETL with Azure Cookbook
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ELT is very similar to ETL, but with a crucial difference: the order of the transform and load steps are inverted. This is very useful with big data in the cloud or when we do not have an ETL tool on-premises. This recipe will be much simpler than the previous one, as we'll implement ELT using a database, so no tools are involved here except for calling the ELT task.
It also relies on the previous recipe, Creating a simple ETL package, since we're going to use the SalesLT.CustomerFullName table data to implement the ELT pattern.
There are essentially two parts to this recipe:
This recipe assumes that you have installed SSMS, Visual Studio 2019, and SSIS.
Let's dig into the recipe:

Figure 2.32 – SSMS AdventureWorksLT database context
ALTER TABLE SalesLT.Customer ADD FullName NVARCHAR(350)

Figure 2.33 – SSMS Object Explorer FullName column
a) Connection: cmgr_etlinazurecookbook.database.windows.net.AdventureWorksLT.ETLAdmin
b) SQL SourceType: Direct input
c) SQL Statement:
UPDATE c SET FullName = cfn.FullName FROM SalesLT.Customer AS c INNER JOIN SalesLT.CustomerFullName as cfn ON c.CustomerID = cfn.CustomerID;
Click on OK to close the editor and go back to the control flow.
SELECT [CustomerID] ,[FullName] ,[NameStyle] ,[Title] ,[FirstName] ,[MiddleName] ,[LastName] ,[Suffix] ,[CompanyName] ,[SalesPerson] ,[EmailAddress] ,[Phone] FROM [SalesLT].[Customer]
The result should look like the following screenshot:
Figure 2.34 – SSMS Query Editor result
This recipe showed you the pattern of ELT. Data was extracted from the source first, then loaded into the database (as we saw in the previous recipe, Creating a simple ETL package). We then transformed the SalesLT.Customer data by using already loaded data.