A reading list.
Understanding one of the most important types of data analysis.
It's too often misused and misunderstood.
What you need to know and ask.
How confident are you in the relationship, and what is the risk of being wrong?
Collecting lots of data is not the hard part.
Key questions (and their follow-ups) to advance your next metrics project.
Build your analytical skills.
How the data was collected and how certain are the conclusions.
Flawed doesn't mean unusable.
The psychology of data visualization.
Companies are using big data for pricing, maintenance, and more.