Summary
In this tutorial we looked at using regular expressions with alphabetic, numerical and special character data while looking at some applied examples where regular expressions may be a tool that we can use. We’ve also reviewed the inverse of regular expressions: expressions that look for data where it doesn’t fit a character type. From ETL to data parsing to identifying strict limits, whether we’re trying to identify data, or precisely limit data, we can use regular expressions if the situation calls for it.
Take the time to walk through each of the examples to get a better understanding of how you can use regular expressions when working with SQL Server using T-SQL.
Tim consults for FinTek Development and teaches the course Automating ETL on Udemy. He’s worked with technology since high school, helping his school win its first TCEA award and continues to work in automation, data architecture, back-end development, and smart contract architecture. Tim enjoys testing new technologies early in the diffusion of innovation curve and was an early adopter of NoSQL and smart contract development. He has a blog at http://www.fintekdev.com/ and helps contribute to local technical and financial events in Texas.
