Solving newcomer data science challenges with Canonical’s Data Science Stack – now in beta.
Data science is one of the most exciting topics of the last century. With its utility in industries of all kinds, it’s easy to see why it has been rated as one of the top 20 fast-growing occupations in the US, according to the Bureau of Labour Statistics. However, entering this fast-growing space isn’t’ easy: newcomers face significant challenges in setting up their environments, dealing with package dependencies, or accessing compute resources. Given these obstacles, it’s easy to see why a talent shortage persists in the data science field, and why overcoming these challenges is vital for teams and companies.
This blog will walk you through the most common challenges that data science newcomers face, review popular data science platforms, and take a look at the bigger picture of how open source is used in data science. With these insights, you will be able to more easily choose the right tools and options to simplify your work and focus on upskilling in the data science field.
Is it easy to get started on data science?
