We learned various ways in which architecture designs for the Qlik Sense project can be taken care of.

We learned what is meant by architecture and why it is important, especially when it comes to Qlik Sense. We saw that there are two basic kinds of architectures, infrastructure architecture and data architecture. Diving in infrastructure architecture, we saw which parameters need to be considered when deciding the hardware requirement for Qlik Sense project. We also saw the basic software requirement.

Then we started with understanding the deployment architecture and its various aspects, which should be understood before starting architecture design. In this, we look at node, site, single and multi-node architecture and different persistences

Moving forward, we saw the backup and restore strategy. We looked at the various options of taking backups  of applications and the data of Qlik Sense. We also understood the entire concept using an example.

After finishing the infrastructure architecture, we looked at the data architecture and various aspects which are needed for data architecture.

We learned about QVF and QVD, and looked at the parameters of data architecture, which should be known before deciding the data architecture. Then we saw the QVD architecture with one tier, two tier, and three tier architecture. Then we saw the QVF architecture with two tier, three tier, and the hybrid architecture. We also saw an example of data architecture and understood the entire concept.

Lastly, we learnt about data flow diagrams and with help from an example, learnt how it helps us visualize the data flow of an entire project. In the next chapter, we will look at the various best practices while doing development and this will cover data modelling techniques, security aspects, and visualization best practices.

In the next chapter we look at the important aspect of development. The major work of a project goes into the development and we will look at good practices a consultant needs to follow. We will cover topics such as different ways of data extraction, best practices one should follow in data modelling, security needs and visualization strategy. We will look at how a consultant should handle tricky situations.