data flow is used to extract, transform and load data from the source to the target system. all the transformations, loading and formatting occurs in dataflow.

once you define a data flow in a project, this can be added to a workflow or an etl job. data flow can send or receive objects/information using parameters. data flow is named in format df_name.

example of data flow

let us assume that you want to load a fact table in dw system with data from two tables in the source system.

data flow contains the following objects −

• two source table
• join between two tables and defined in query transform
• target table

there are three types of objects that can be added to a data flow. they are −

• source
• target
• transforms

step 1 − go to the local object library and drag both the tables to work space.

step 2 − to add a query transformation, drag from the right tool bar.

step 3 − join both the tables and create a template target table by right clicking the query box → add new → new template table.

step 4 − enter the name of the target table, data store name and owner (schema name) under which the table is to be created.

step 5 − drag the target table in front and join it to the query transform.

passing parameters

you can also pass different parameters in and out of the data flow. while passing a parameter to a data flow, objects in data flow reference those parameters. using parameters, you can pass different operations to a data flow.

example − suppose you have entered a parameter to a table about last updated. it allows you to extract only rows modified since the last update.