It is important to have a rich and comprehensive data set for every system decision, including machine learning models. Only then can one build a robust and powerful model with desired performance. Otherwise, the developer would face the so-called GIGO (garbage in – garbage out) effect. It is an expression that says poor-quality input data provides poor-quality outputs. Although there are several data platforms automating the whole ETL (extract, transform, load) process, sometimes these solutions are overabundant, or the pre-made solutions might not meet your specific needs. (more…)