Data Flow

 Data Flow

The Data Flow task encapsulates the data flow engine that moves data between sources and destinations, and lets the user transform, clean, and modify data as it is moved. Addition of a Data Flow task to a package control flow makes it possible for the package to extract, transform, and load data.

A data flow consists of at least one data flow component, but it is typically a set of connected data flow components: sources that extract data; transformations that modify, route, or summarize data; and destinations that load data.

At run time, the Data Flow task builds an execution plan from the data flow, and the data flow engine executes the plan. You can create a Data Flow task that has no data flow, but the task executes only if it includes at least one data flow.

For the Data Flow, Data source, destination, and the data transformation are the major components and their functioning is highly different from a task. When Data is transformed into anything meaningful, it is done on the basis of logic how are components connected together, data management, etc.

Multiple Flows

A Data Flow task can include multiple data flows. If a task copies several sets of data, and if the order in which the data is copied is not significant, it can be more convenient to include multiple data flows in the Data Flow task. For example, you might create five data flows, each copying data from a flat file into a different dimension table in a data warehouse star schema.