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How Do I Go About Building A Performance Model
There are various different ways you could to about building your system and modelling behavior for change in input parameters. In this article we’ll take a look at one of the approaches we’ve seen most commonly used.
- Step 1- Visualize the Time Series data for a given Application/Data Dimension using Exploratory Data Analysis.
- Step 2 – Explore the nature of Trend & Seasonality for a given Application/Data Dimension using Time Series Decomposition
- Step 3 – Use Time Series Forecasting techniques to understand the behavior of the given Application/Data Dimension
- Step 4 – Identify relationships between multiple Application/Data Dimensions and use the relationship to forecast potential breaking points or scalability limitations.
The steps mentioned are more of a guide to help you navigate your way around the different Statistical Modelling techniques that VisualizeIT has to offer. As we’ve mentioned before there is no hard and fast rule that you have to perform modelling using the above approach. You are free to go about using the models anyway you see fit. However, keep in mind GIGO i.e. Garbage In (Garbage input into your models) results in Garbage Out (Garbage output from your models). So be careful on the approach you take including the input data/parameters you choose for your given model.
Modelling Solution: VisualizeIT offers access to a bunch of Analytical Models, Statistical Models and Simulation Models. Access to all the Analytical (Mathematical) models is free. We recommend you try out the Analytical models at VisualizeIT which are free to use and drop us a note with your suggestions, input and comments. You can access the VisualizeIT website here and the VisualizeIT modelling solution here –VisualizeIT.