Simulated Data, Real Learnings : Simulating Systems | by Jarom Hulet | Apr, 2024

Part 4 — Simulating to Understand Systems

Towards Data Science
from by Zhang Kaiyv


Simulation is a powerful tool in the data science tool box. In this article, we’ll talk about how simulating systems can help us formulate better strategies and make better decisions.

The specific topics of this article are:

  1. What is system simulation?
  2. System simulation optimization
  3. System simulation risk assessment

This is the fourth part in multi-part series that discusses simulation in data science. The first article covered how simulation can be used to test machine learning approaches, the second covered using simulation to estimate the power of a designed experiment and the third article discusses how we can make strategies by simulating scenarios.

Here are the links to those articles:


The first article spends a lot more time defining simulation. Reference that for a more in-depth conversation on what simulation is. To avoid redundancy, I’ll just give a quick definition here:

Data simulation is the creation of fictitious data that mimics the properties of the real-world.

Okay, with that out of the way, let’s talk about system simulation!


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