Check out Propmodo’s great piece on real estate data and standards!
“In the real estate world, we have addresses, block and lot identifiers, and GPS coordinates. But these don’t always accurately identify a property. Address resolution is a tricky thing. According to Brett Friedman, head of sales and marketing for Cherre, “you have to make sure the real estate related entities (lot, building, unit, etc.) match across data sets before you can begin to think about appending data fields to a particular address or looking at the bigger picture. In a complex market like New York City, you encounter challenges such as alternate addresses, vanity addresses, entrances on different streets or avenues, or units described inconsistently.” Friedman says that in New York City, these “edge cases” where addresses between two different records might not match are the norm, and you’re in fact making the data lake dirtier by not resolving the entities as a first step in your process.”
You’re barraged by real estate data sales pitches every day. Buzzwords like AI, Moneyball, or Bring-Your-Own-Data Visualization layers. But you rarely hear about implementations that drive ROI. That’s because most sales pitches are bullsh*t.
“The World As a Service: A peek into the future technology is creating.”
You won’t want to miss James Whittaker’s keynote at the inaugural Cherre Data Summit on May 19 in NYC: “The World As a Service: A peek into the future technology is creating.”
14 reasons your data project has failed (including reasons you’ve never heard before)
By Raj Bhatti, SVP Client Solutions
Twenty-five years ago was the first time I heard a senior business leader say,
