Real-World Data Science

Inside tricks from the industry with real-world data science use cases

How to Lie with Data

We expect that data scientists and analysts should be objective and base their conclusions on data. Now while the name of the job implies that “data” is the fundamental material that is used to do their jobs, it is not impossible to lie with it. Quite the opposite – the data scientist is affected...

READ MORE

Top mistakes data scientists make

The rise of the data scientists continues and the social media is filled with success stories – but what about those who fail? There are no cover articles praising the fails of the many data scientists that don’t live up to the hype and don’t meet the needs of their stakeholders. The job of the...

READ MORE

How to stay out of analytic rabbit holes: avoiding investigation loops and their traps

“What if we add these variables?..” is a deadly type of a question that can ruin your analytic project. Now, while curiosity is the best friend of a data scientist, there’s a curse that comes with it – some call it analysis paralysis, others – just over-analysis, but I call these situations...

READ MORE

What makes a great data scientist?

A data scientist is an umbrella term that describes people whose main responsibility is leveraging data to help other people (or machines) making more informed decisions. The spectrum of data scientist roles is so broad that I will keep this discussion for my next post. What I really want to...

READ MORE

How to think like a data scientist to become one

We have all read the punchlines – data scientist is the sexiest job, there’s not enough of them and the salaries are very high. The role has been sold so well that the number of data science courses and college programs are growing like crazy. After my previous blog post I have received questions...

READ MORE

Hello World

Hello world. The journey begins.

READ MORE