We guarantee best practices are followed during data modelling as our team of experienced Qlik experts have faced hundreds of complex data challenges over the years. We will draw on this experience when helping you design the correct data model because we understand the importance of getting this right.
Every project is different but some of the main areas that often pose a problem when data modelling are:
Data Volumes
By understanding the core Qlik technology, we use many techniques to reduce the footprint of the data. Reducing file size and memory usage allows for more responsive applications – even across data sets with many millions of rows.
Consolidating Systems
Bringing different sets of transactions together from different source systems can pose some tricky data modelling challenges. We can ensure consistent results that don’t affect performance. We have developed a set of core principles that can be applied across all solutions to minimise the impact of consolidating data while maximising the results.
Security
As Qlik experts, we understand the different ways security can be applied when developing a Qlik application. We appreciate the significance of implementing the correct architecture to fully secure the data and make sure that users only see what they are permitted to see.
Performance
A well-designed data model will allow for sub-second response times. Avoiding some of the common pitfalls is an important step in delivering a fast, reliable solutions. Our team are fully trained and skilled in understanding how best to build a fast-performing Qlik application.
If you would like to know more about our Qlik data modelling techniques and how ometis can help you, get in touch with our team of experts today.
