#datawithSeinfeld post 1 of 10: The Limo

Remember when George and Jerry are stuck at the airport without transportation, and they are tempted by the Limo driver holding up the "O'Brien" sign. George pretends to be O'Brien, and chaos ensues.

How does this happen? How can the actual O'Brien be confused with this self-reported O'Brien? This is a case of poor entity resolution, an important concept in data analytics.

When we have multiple data sources, how can we know whether an entity in one dataset corresponds to the same as an entity in another data set? This is an important aspect in many contexts, like:

🏪 A retailer with products from suppliers and sales data needs to determine which records refer to the same product.

🏥 A hospital juggling provider data and insurance data must pinpoint which visits or procedures are linked to the same event.

🚗 A driver with a scheduled rider and an in-person rider needs to verify if they're indeed the same individual.

In "The Limo" episode, the driver doesn't practice any entity resolution and has no way of knowing whether the scheduled O'Brien is the same entity as the O'Brien that presented in the airport. This makes for a hilarious episode, but poor entity resolution can have significant real world consequences.

Here are some basic tips for practicing good entity resolution:

1️⃣ Data Cleaning: Ensure your data is clean, standardized, and free from errors. This makes matching more accurate. (sometimes challenging with third party data providers)

2️⃣ Use of Unique Identifiers: Whenever possible, use unique IDs that can help in directly matching records.

3️⃣ Fuzzy Matching: This technique matches entities that might not be exactly the same but are likely to refer to the same thing, e.g., "J. Smith" and "John Smith."

4️⃣ Machine Learning: Advanced algorithms can be trained to recognize and match entities based on patterns in the data. This will often involve some human labeling.

5️⃣ Regular Audits: Periodically review and validate the matched entities to ensure accuracy.

Make sure you're dealing with the right O'Brien in your data, and if you need to explain entity resolution to any Seinfeld fans, check out "The Limo" episode!