When Do You Need a Machine Learning Model?

Explanations, Alteryx use cases, and more

Machine Learning (ML) just sounds cool-doesn’t it? Maybe it’s because I’m a nerd, or maybe it is cool. Regardless, you’re probably used to hearing buzz around this topic. (Or at least seeing TV and movies that play with the concepts.)

If you are not from a data science background, you might want to avoid such a technical topic. But I believe it’s essential for people who work with data to understand when machine learning is needed and when it’s not.

Whether you are a data analyst, financial analyst, BI developer, or consultant, you can understand the basics of machine learning: the use cases, the high-level processes, and the tools. And then, when you have data you want to get insights from, you will know which route to go down for that project.

What is Machine Learning?

Machine learning is a branch of artificial intelligence (AI) that focuses on using data and algorithms to create models that learn-i.e., improve accuracy over time as humans do. It sounds very complex (and it can be), but the simplest model can be a line of best fit through a plot of your data. This line of best fit has an…