Please join us for the presentation "When Low-Quality Data Strikes: Fuzzy Tools Provide Clarity in Matching and Deduplication" with Jared Kuehn. A description of the talk: "You have a high-quality dataset, appropriately keyed, groomed, and trusted by business users. Then you're asked to merge in a new, low-quality dataset. It may contain a different key structure, numerous text fields with typos, or optional fields that are empty on most records. How would you find as many accurate matches as possible? You can define multiple matching algorithms to handle the various discrepancies you find, but it can be difficult and time consuming to prevent missing matches. In this session, I will showcase how you can solve problems like this using the fuzzy tools natively available in SQL Server. I will explain how a fuzzy approach compares to other options such as exact match algorithms, weighing the pros and cons. Finally, I will demonstrate how to set up the groundwork to incorporate fuzzy tools into a data flow solution. By the end of this session, you should have another tool in your toolbelt that can aid you in any matching or data deduplication scenario." Thank you!