data science

If you are in undergrad and are contemplating a career in Data Science and Analytics, pick up tools and technologies that enjoy industry wide usage such as Tableau, PowerBI, R, Python and others that are commonly used. Learn from online courses and free YouTube resources such as freeCodeCamp. If you

Going back in time is a great way to understand what is it that one needs to do now to change course for the better. I love this trick that makes for great conversations and self-examination. One thing I will change if I can go back is to spend more

If you keep your notebook close, and your pencil even closer, and make notes and connect the dots, and you do this even for a few weeks (30-45 mins daily), at the end of a month you would have gained a whole lot of perspective and understanding.

All of a sudden, a company will go from collecting very little data to now collecting data from their website (views, clicks), employee data, manufacturing (from machines, processes, employee activity) and any other aspect of their business that needs to be improved.

Everyone learns differently. But to know what works for you, choose a system that you found successful in school or college. Often we used to sit with a resource (usually a book) and read and take notes. Do the same now. The process is the same but the resources have changed.

If you can create a list of every tool existing in data science, that list itself will be fascinating to share with others. After you have done the research to create such a list, add a few lines to summarise what each tool does and one or two pros and