How does the Relative dependency of dimensions affect the sparsity of data? Please help me understand with examples.
let's say you have 2 lists in the module: Employee & Products
As of today you have 100 employee selling 50 products. If you put these 2 lists in a module the cross section will have 5000 cells. In future your employee list will grow to 500 employees and products increased to 500. Now the cell count will be 250000.
This will affect model size and lead to sparsity. As creating a module by applying multiple dimensions will grow in size and cell count and also affect the performance of the model. Hence you should create combination list for which you can go to the series of articles:
https://community.anaplan.com/discussion/44493/the-truth-about-sparsity-part-1
Hi @Rdey,
If you're using the Classic engine, as Dikshant mentioned, you might consider a combination list, but keep in mind that sparsity is not your enemy. It's usually better to design the model naturally rather than overfitting lists to solve sparsity concerns.
In these scenarios (and actually in most cases other than using PlanIQ and Optimizer), models built on the Polaris engine handle sparsity very efficiently, so there's no need to overcomplicate things with combination lists.
I hope this helps. Seyma đˇđ
what are these? when do you use them? why one over another? thanks Data types string long float bool date datetime datetimetz
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