Documentation

This article describes the transforms you can use when creating a data cube (ETL process).

The Data Cube transform is created when another data cube is dragged onto the canvas.

The Data Input transform lets you reference a warehouse data storage area containing user input data.

Enter a SQL or MDX statement to make a selection from a data connector instead of dragging native structures onto the canvas.

The OLAP Select transform is created when a cube from an OLAP database connector is dragged onto the canvas.

The SQL Select transform is created when a structure is dragged onto the canvas from a data connector that supports relational queries.

The Stored Procedure Select transform lets you retrieve data using a relational stored procedure.

The Tabular Select transform is created when you drag a structure onto the data cube canvas from a data connector that supports tabular data (e.g., Excel, XML, SQL Server table-valued functions).

The Aggregate transform allows use of aggregate functions such as sum, average, count, minimum, maximum, etc.

The Calculated Element transform lets you create new elements by writing DundasScript expressions. 

The Data Conversion transform allows you to change the data type of a column.

The Filter transform filters out rows that do not meet the configured criteria/settings.

The Join transform combines two separate tables together by matching up their rows. All of the columns from both tables can be included.

The Lookup transform replaces the values of one or more key columns with the values you choose in another table.

The Math transform lets you perform simple math functions such as Absolute, Round, and Square Root on numeric input columns.

The String transform manipulates string columns by applying string functions.

The Union transform combines the rows from two tables that have matching columns.

The Copy Element transform creates new columns by copying selected input columns and adding the new columns to the output.

The Flatten JSON transform turns rows of data containing JSON text into separate columns for each of its values.

The Flatten XML transform turns rows of data containing XML text into separate columns for each of its values.