Data Analytics and Data Science is the science of analyzing raw data to make conclusions about that information, and to make inferences and predictions based on the data and statistical evidence. Various approaches to this include looking at what happened (descriptive analytics), why something happened (diagnostic analytics), what is going to happen (predictive analytics), or what should be done next (prescriptive analytics).

Data analytics is important because it helps businesses optimize their performances. Implementing it into the business model means companies can help reduce costs by identifying more efficient ways of doing business and by storing large amounts of data. A company can also use data analytics to make better business decisions and help analyze customer trends and satisfaction, which can lead to new and better products and services.

The Data Analyst job market is predicted to grow by 23% between now and 2031 according to the US Bureau of Labor Statistics—and companies are prepared to pay extremely competitive salaries. A job in data promises excellent career prospects, so it’s no surprise that more and more people are looking to switch into the field. Hence, it is no surprise that a newbie trying to break into this field will face fierce competition from other more seasoned players.

And one of the most important things that can help someone deal with this is.... yep, you guessed it right - building portfolio projects - and that too on topics that have real world value using tools that are widely used by professionals in this field. With that in mind, here are some of my portfolio projects that I have built to gain experience in Data Analytics that you can find in this repository.