Query Non-traditional Data with T-SQL

Learn to query and manipulate non-tabular data in SQL Server. Extract values from JSON, analyze changes with temporal tables, ingest external sources, and handle dynamic or sparse structures-without needing external tools or code.
Modern SQL Server applications often store data in formats that don't fit neatly into relational tables-like JSON documents, historical audit trails, delimited lists, or even external CSVs. Querying and transforming that data with T-SQL requires specialized skills. In this course, Query Non-traditional Data with T-SQL, you'll learn to work confidently with flexible, semi-structured, and evolving datasets using only SQL Server. First, you'll explore how to ingest JSON, CSV, and other semi-structured files using native T-SQL tools. Next, you'll learn how to extract and transform embedded data, such as arrays, key-value structures, or delimited values, into usable relational format. Finally, you'll analyze how data changes over time using temporal tables and reconstruct point-in-time state or recover deleted information. When you're finished with this course, you'll have the skills and knowledge of querying non-traditional data in SQL Server needed to support modern applications, reporting systems, and real-world data pipelines-all using just Transact SQL on SQL Server
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