6 tips to get more out of your capacity based license

In our previous blog we described the new licensing model for Qlik Cloud Analytics. In this new model, the key metric is the amount of data analysed on your platform. All the data you load into or create on the platform is added up in bytes and measured against the capacity you have purchased. This means you are directly rewarded for setting up your Qlik environment smartly. In this blog, senior Business Intelligence consultant Lennaert van den Brink shares 6 tips on how to use your Qlik environment as efficiently as possible. Bonus: even if you don't have a capacity based license, many of these tips will help you optimise the performance of your environment!

#1 Optimise your data models

We often see that a large share of the columns being loaded is never used. That is a waste, because every one of those bits still counts. You can also often gain a lot by, for example, using autonumber for key fields. Many of the possible optimisations are worthwhile anyway because they improve the performance of your dashboard, but in the new model you also see the gains reflected in hard euros.

#2 Think carefully about how you set up your Qlik Cloud Tenant

In the old model you were not charged for duplicating files. That is why it was sometimes convenient to write QVDs to multiple spaces, for example for self-service use.

#3 Clean up your environment regularly

A dashboard or QVD that is no longer used but is still refreshed regularly counts towards your total, so get rid of it!

#4 Consider using parquet files instead of QVDs

It has recently become possible to read and write parquet files directly from Qlik script. Our internal tests at E-mergo show that in some cases the resulting parquet files are considerably smaller in file size, especially when the dataset is sorted before it is written. The downside is that these parquet files can sometimes be slower to load than QVDs (optimized load). So it is worth weighing up whether you prefer faster processing or lower consumption.

#5 Think carefully about your large apps

Ideally we would of course always load all the data, but do we really need invoice-line level detail for 10-year-old invoices? You can choose to load older data at a higher level of aggregation, or perhaps not load it at all. Do you still need that level of detail? Then you might be able to use On-demand app generation or direct query, so you still don't have to load everything into the environment.

#6 Consider pushing transformations back to the source system

If your source is a transactional system, such as a point-of-sale system, this may not be very practical. But if you load from a data warehouse, for example, it makes a difference whether you load 3 tables with SELECT * and then stitch them together in Qlik with JOIN statements and WHERE filters, or whether you already put this in the query to the source system. You can of course also ask your data warehouse developers to implement these transformations on their side.

Want to know more?

After reading this blog, would you like to find out whether the new licensing model for Qlik Cloud Analytics is a good fit for you? Get in touch with us or schedule an appointment right away!