The data scientist is called the sexiest job of the 21st century. If you are planning to enter the field of data science, chances are that your aim is to become a data scientist as it’s the most coveted post these days. Though some may even opt for the position of a data analyst, it’s still second in the race as the most preferred position for many aspirants is still the post of a data scientist. If playing with data and finding hidden insights where others don’t see it or find it is something that you love and want to take up as your career, you may even consider being a financial analyst, or a research analyst. Though you will come across several career choices that let you stay close to data and figures, the one that wins hands down is a data scientist. But it shouldn’t mean that just because everyone else is aiming for this post, you too should join the bandwagon. You will need to understand what the job entails, the kind of skills and aptitude you will need, the pay package you will get, the chances of furthering your career that you will have, etc. before taking your final pick.
Data analysis comes with the goal of deriving useful information from data, suggesting conclusions, and supporting critical business decision making. There’re lots of data analysis tools that can be utilized to help a business to get a competitive edge. If you’re trying to step into the field of data analysis, it’s extremely important to have a good working knowledge of the most commonly used data analysis tools. In this post, we’re going to discuss five such tools by learning which you’d be able to propel your career in data analysis.
Being a data analyst would mean you’ll have several skill-sets that one needs to work in the domain of data science. However, it doesn’t mean you can easily jump from your data analyst career into the role of a data scientist. Before discussing if being a data analyst could act as a step to becoming a data scientist, let’s take a look at what each of these professionals do.