Imagine you just bought a corner block at 1 Smith Street. But your postal address is registered as 10 John Street because the mailbox faces that street. To top it off, make it a duplex where one part is rented out as 1A or 1B, and suddenly what’s really one home looks like many different properties in the data.

In this talk, we’ll explore why data sources often don’t agree — and what data engineers do to bring them back together. We’ll look at entity resolution (aka “is this the same house?”), how to blend data from different sources, and why addresses don’t always equal properties. No property or data knowledge required — just real-world examples and a peek into how data modelling can help untangle the mess.