Databases Reference
In-Depth Information
Advanced Data
Transformation
In this chapter we will dive into advanced transformation functions and techniques
available through QlikView's extraction engine. This will allow you, as a developer,
to finely process the source data and turn it into a clean design, while at the same
time keeping an efficient script.
The goals of this chapter are:
• To provide an overview of the most commonly used data architectures that
can ease QlikView's development and administration
• To describe the available functions for data aggregation
• To learn how to take advantage of some of QlikView's most powerful data
transformation functions.
Data architecture
Now that we have a decent amount of QlikView development experience under our
belt, we will introduce the concept of data architecture. This refers to the process
of structuring the different layers of data processing that exist between the source
tables and the final document(s). Having a well-designed data architecture will
greatly simplify the administration of the QlikView deployment. It also makes the
QlikView solution scalable when new applications need to be developed and when
the QlikView environment grows. There can be a lot of different data architectures,
but in this section we will discuss two of the most commonly used in QlikView
enterprise deployments.
