From the course: Complete Guide to Advanced SQL Server

Analyze SQL Server data with Python - SQL Server Tutorial

From the course: Complete Guide to Advanced SQL Server

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Analyze SQL Server data with Python

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Python is a very popular programming language that's commonly used in data science, but it can be cumbersome to use with data stored in a SQL Server database. Microsoft has addressed this by allowing users to execute Python code directly on the SQL Server instance, and this is the topic that we'll be covering in Section 4. Support for the Python language is available through an add-on component called Machine Learning Services. Once it's enabled, Python code can be sent to the server for processing and information is returned to the user without having to move data out of the protected envelope of the SQL Server instance. Compare this with the typical way of processing information that involves copying large tables to external files, or transferring raw data through insecure connections, and you can see how on-server processing can be a benefit for security conscious applications. Throughout this section, I'll show you how to enable machine learning services and how to write queries that incorporate Python code to return information from the Wide World Importers database. Now, while we will be executing Python code, I do not expect that you'll have any prior knowledge with the Python programming language. I'll introduce the essential components of Python that will help you work with your data stored in SQL Server and that will give you a good foundation, should you choose to pursue additional training in the Python language to perform more advanced analyses. Okay. Let's get started.

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