Data Science

What’s a data mart and why data scientists should use one — As a data scientist, you can spend up to 80% of your time cleaning and transforming data in order to generate actionable insights and build machine learning models to create business impact. Now imagine a world where you can spend more time on analysis and model development instead of cleaning…

A succinct introduction to Git — A lot of introductions to Git are very convoluted and overcomplicated. It’s actually a very simple technology to use once you get your head around it. …

Saving Thousands Of Dollars By Turning Things Off — It’s easy to let costs run a little wild with data teams. In the last decade, the charge for many companies has been data insights and costs have taken a back seat. This has led to many companies spending hundreds of thousands if not millions on data initiatives. Even when…

Creating the Heatmap Technical Indicator in Python — Heatmaps offer a quick and clear view of the current situation. In trading, we can use them with correlations but we can also use them to detect imminent reactions or to confirm the underlying trend. This article discusses the creation of the heatmap on the values of the RSI. I…

Deep and rapid comparison in terms of 7 key aspects — There is an annoying habit of soccer fans. Whenever a young but admittedly exceptional player emerges, they compare him to legends like Messi or Ronaldo. They choose to forget that the legends have been dominating the game since before the newbies had regrown teeth. …