According to the Polaris website, it states that the higher the sparsity of the data, the better the memory efficiency.
What exactly does this “memory efficiency” refer to?
Does it simply refer to the model size?
@kimur1111
Model size is determined on the amount of non Default data (Trues, numbers, text, list formatted line items that are not blank). Polaris performs very well with sparse data, so it is only calculating on intersections that have "valid" (non null) data.
The more sparse data means that polaris as engine allocates memory only for non- default data , so if there are large blanks , memory is only allocated for inntrsection where data is there , hence polaris is considered better
We are looking for Anaplan end-users to provide feedback on their experiences with the Excel add-in. Interested individuals will respond to this 5-minute survey to help us understand personal needs and behavior when using the add-in. The feedback provided by survey takers is essential to the roadmap of Anaplan's products.…
Estimated Level of Effort:4-8 Hours of Model Building Level of Difficulty: Beginner Recommended Training: L2 Model Builder Training Persona: Casual Model Builder Potential ROI: Decreased planning time Increased accuracy of targets/spreads You Might Also Like: * Historical Snapshotting Top-Down Allocations Whether it's…
This item has been identified as an outstanding known issue. A workaround is provided until the issue is officially fixed. Issue For versions 1.6, 1.7 and 1.8 of the PowerPoint Add-in elevated privileges are required to install the add-in through command line and for the "all users" option. Workaround * Installing through…
