It is often said that data is the new oil, but this analogy misses a critical difference: oil has inherent value once refined, while data only reveals insights when we ask the right questions - and sometimes the answers we need aren't even in our dataset. When we draw conclusions from incomplete or misunderstood data, business decisions can go terribly wrong.
There might be a clear pattern in the data leading to confident action - but what if our interpretation of that pattern is fundamentally flawed?
In this session we will explore the cognitive, temporal, and structural challenges that face every data analysis project. We'll examine how easily biases creep in, why timing impacts results far more than we expect, and why a seemingly straightforward analysis can hide dangerous complexity.
Whether you're running the analysis or making decisions based on it, you'll leave with a deeper understanding of when the information in front of us might not tell the whole story. You'll learn why domain knowledge is absolutely vital, what questions to ask before trusting conclusions, and why humility is essential to finding the key driver.
Join me for 50 minutes at the intersection of data, psychology, and curiosity - where good analysis begins with knowing what we don't know.
22-25 April 2026 