As soon as the data comes
in from a source, consider dropping any columns that are not required
for subsequent transformations in the flow. You can drop columns and
make aggregations early in the process flow instead of later. This
prevents the extraneous detail data from being carried along between
all transformations in the flow. You should work to create a structure
that matches the ultimate target table structure as closely as possible
early in the process flow. Then, you can avoid carrying extra data
along with the process flow.
To drop
columns in the output table for a SAS Data Integration Studio transformation,
click the
Mapping tab and remove the extra
columns from the
Target table area on the
tab. Use derived mappings to create expressions to map several columns
together. You can then build your own transformation output table
columns to match your ultimate target table and map.
Finally,
you can control column mapping and propagation at a job level, at
a transformation level, or even at a column level. Column propagation
is the ability to automatically propagate columns through the intermediate
tables in a process flow to the target table. If you do not need to
map or propagate some of the columns in a flow, use one of the following
options:
-
Automatically map columns and
Automatically propagate columns options
at
ToolsOptionJob Editor (for new jobs)
-
Map Columns and
Propagate Columns in the pop-up menu
for a job or transformation (for selected jobs and transformations)
-
Map all columns,
Map selected columns,
Propagate
from sources to targets,
Propagate from targets
to sources, and
Propagate columns on the
Mappings tab for a job or transformation
(for selected jobs and transformations)