As a continuation to my previous article, How to use Python in SQL Server 2017 to obtain advanced data analytics, a little bit of curiosity about Deep Learning with Python integration in SQL Server led me to write this latest article.
With Python running within SQL Server, you can bring the existing data and the code together. Data is accessible directly, so there’s no need to extract query data sets, moving data from storage to the application. It’s a useful approach, especially considering issues of data sovereignty and compliance, since the code runs within the SQL Server security boundaries, triggered by a single call from T-SQL stored procedures.
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Data Interpolation and Transformation using Python in SQL Server 2017
See Also,
- How to use Python in SQL Server 2017 to obtain advanced data analytics
- An overview of Python vs PowerShell for SQL Server Database Administration
- Why would a SQL Server DBA be interested in Python
Please share your thoughts in the comments section. I would love to hear and learn from you as well.
Thanks for reading my space!