Business Intelligence dashboards are becoming more and more prevalent in businesses. Building an effective dashboard following best-practices leads down a comprehensive BI process. In this post, we will try to cover 4 of the most important things to keep in mind when assembling your dashboard. Good dashboard design simplifies large amounts of data to answer important questions raised by the business. In order to answer these questions, the dashboard needs to tell a clear and defined story while expressing the meaning of the data in clear visualizations, allowing the viewer to dig into the details if necessary. Bad Example A quick Google search and we have found a plethora of terribly designed dashboards. Here is one example: Terrible dashboard design There is simply too much going on in such a small place, all at once. It is cluttered, and distracting. How to Create Beuautiful Dashboards? So how can you avoid…
Jupyter notebook is by far my all time favorite tool. It is the go-to tool for data exploration for any data scientist or data analyst out there.
There are hundreds of Python libraries aimed to make lives easier for data scientists. Some good and some bad, some large libraries covering many areas and some that only do a couple things very well. Here is a list of 5 Python libraries that every data scientist is required to have installed in their environment.
In this blog post I will lay out five (5) reasons you should consider Databricks before starting your next data science project.
There are a lot of blogs out there focusing on data science. Throughout the past few years, I have found at least a handful of blogs that I read regularly. I’ve tried my best to narrow it down to my favorite 5 blogs.