Is data science getting easier?
The answer is yes, and no. This is a question that could've easily been applied to textile manufacturing in the 1890s, and could've received...
Top 5 misconceptions about data science
Data science is a well-defined, serious field of study and work. But the term ‘data science’ has become a bit of a buzzword. Yes,...
What’s the difference between a data scientist and a data analyst
It sounds like a fairly pedantic question to ask what the difference between a data scientist and data analyst is. But it isn't -...
5 things that will matter in data science in 2018
The world of data science is now starting to change quickly. This was arguably the year when discussions around AI and automation started to...
5 data science tools that will matter in 2018
We know your time is valuable. That's why what matters is important. We've written about the trends and issues that are going to matter...
Why data science needs great communicators
One of the biggest problems facing data science (and many other technical industries) today is communication. This is true on both an individual level,...
GDPR is pushing the Chief Data Officer role center stage
Gartner predicted that by 2020 90% of large organizations in regulated industries will have a Chief Data Officer role. With the recent heat around...
30 common data science terms explained
Let’s begin at the beginning. What do terms like statistical population, statistical comparison, statistical inference mean? What good is munging, coding, booting, regularization etc....
Top 7 libraries for geospatial analysis
The term geospatial refers to finding information that is located on the earth's surface. This can include, for example, the position of a cellphone...
Introducing Dask: The library that makes scalable analytics in Python easier
Python’s rise as the preferred language of choice in Data Science is unprecedented, but not really unexpected. Apart from being a general-purpose language which...