Databases Reference
In-Depth Information
The resulting table will turn our 1,256,075 rows into only 100,091. A brief example of
what just happened is shown in the following screenshot:
Notice how the totals remain the same for both tables.
A smaller table will occupy fewer resources (RAM and CPU) and, therefore,
calculations will be faster. If the performance gain attained with data aggregation
doesn't mean reducing business value and/or functionality for the end user, then
it's a winning approach any day.
The Transformation output
We have loaded the base QVD containing flight data and transformed it by applying
aggregations, now what? Well, the next steps would be to store the transformed
table, using the
store
command, into a new QVD file that will reside in the
3.QVDs\
Transformed
folder.
After that, a new data model could be created in the Presentation Layer based on the
Airline Operations
document, but using the newly aggregated QVD and without
the
Origin
and
Destination
dimensions. This new QlikView document is intended
to serve the users who only need summarized information about the
Airline
Operations
document.
