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Fuzzy Data Matching in SQL [RU]
![504b369cea6c81935ae474d1de4eb211.jpg](https://i123.fastpic.org/big/2024/0720/11/504b369cea6c81935ae474d1de4eb211.jpg?r=1)
: If you were given two different but related data sets, what tools would you use to find matches? What if all you had was access to the database via SQL SELECT? Jim Lehmer offers best practices, techniques, and tricks to help you import, cleanse, compare, evaluate, and make sense of diverse data using SQL.
DBAs, programmers, business analysts, and data scientists will learn how to identify and remove duplicates, parse strings, extract data from XML and JSON, generate SQL using SQL, organize data, and prepare data sets, as well as apply data quality and ETL approaches to find similarities and differences between different expressions of the same data.
The examples in the book are full of real-world techniques and include working code.
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