This set of training classes includes information on improving model performance by understanding and eliminating sparsity. Classes include:
Introduction to Sparsity (309)
Unnecessary model size has a large impact on your Anaplan environment from using valuable space to slowing down key processes. Sparsity is one of the biggest causes of inflated models. Understanding what sparsity is and how it impacts a model is the first step in knowing how to reduce it.
After completing this learning you will will be able to:
Define concepts such as storage capacity and workspace memory
Differentiate between model, module and line item sizes
Contrast the differences between sparse cells and dense cells
Explain how sparsity is measured in a model
This class will take approximately 5-10 minutes to complete.
Sparse cells within an Anaplan model are cells that do not contain and are not expected to contain data. The platform still needs to allocate memory space to these cells even though they are not used. The trick is being able to identify and combat these cells in existing models as well as preventing them when building new.
After completing this learning you will will be able to:
Identify sparse cells in existing models
Think critically when building new models to keep sparsity at a minimum
Utilize line item components such as Applies to, Formulas, Summary, Versions, and Time to reduce sparsity
Analyze which dimensions are necessary in a module and which could be removed
Write formulas which allow you to eliminate other line items or dimensions
Understand how numbered or subset lists can be used to reduce sparsity
Please note that understanding sparsity is important when taking this training, so we strongly recommend completing 309 Understanding Sparsity before beginning. Additionally to help you follow along we are providing to model blueprints, the before and after of one of the examples used in the training.
This class will take approximately 10-20 minutes to complete.
