All of us have heard that data cleaning is 70% of the task when it comes to building Machine Learning models. Collecting the right data, cleaning it and merging datasets is more than half the work in data modeling. Data Preparation is not only important in data modeling but equally important for all kinds of analytics work and any dashboards that you build such as using Power BI or Tableau.

There are many ways to approach “data preparation” including commercial software available specifically for data modeling. Let’s take a look at 3 approaches in this article — Alteryx, Python and Knime — and compare them.

In this article I am only going to talk about the Sample, Explore and Modify stage.

#data-preparation #ds-in-the-real-world #alteryx #knime #python