what sequence should you order four of the listed components for the data flow task?

DRAG DROP
You are creating a SQL Server Integration Services (SSIS) package to populate a fact table
from a source table. The fact table and source table are located in a Windows Azure SQL
Database. The source table has a price field and a tax field. The OLE DB source uses the
data access mode of Table.
You have the following requirements:
The fact table must populate a column named TotalCost that computes the sum of the price
and tax columns.
Before the sum is calculated, any records that have a price of zero must be discarded.
You need to create the SSIS package in SQL Server Data Tools.
In what sequence should you order four of the listed components for the data flow task? (To
answer, move the appropriate components from the list of components to the answer area
and arrange them in the correct order.)

Answer: See the explanation

Explanation:
Box 1: OLE DB Source
Box 2: Conditional split
Box 3: Derived Column
Box 4: Ole DB Destination

Note:
* SQL Server Integration Services provides three different types of data flow components:
sources, transformations, and destinations. Sources extract data from data stores such as

tables and views in relational databases, files, and Analysis Services databases.
Transformations modify, summarize, and clean dat
a. Destinations load data into data stores or create in-memory datasets.
* The Conditional Split transformation can route data rows to different outputs depending on
the content of the data. The implementation of the Conditional Split transformation is similar
to a CASE decision structure in a programming language. The transformation evaluates
expressions, and based on the results, directs the data row to the specified output.
* The Derived Column transformation creates new column values by applying expressions to
transformation input columns. An expression can contain any combination of variables,
functions, operators, and columns from the transformation input. The result can be added as
a new column or inserted into an existing column as a replacement value.