Query Non-traditional Data with T-SQL
Query Non-traditional Data with T-SQL
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 52m | 152 MB
Instructor: Gerald Britton
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 52m | 152 MB
Instructor: Gerald Britton
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.
What you'll learn
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.
Query Non-traditional Data with T-SQL
