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LinkedIn Learning

SQL Server 2017: What's New

via LinkedIn Learning

Overview

See what's new and notable in SQL Server 2017, including Linux compatibility and Python scripting.

SQL Server 2017 is the start of the new annual release strategy by Microsoft. SQL developers no longer have to wait two or three years for enhancements. See what's new and notable in the 2017 release, in this overview with Adam Wilbert. See the new Linux compatibility in action, as Adam shows how to install SQL Server on Ubuntu, and learn how to use the machine learning services package, which includes R and Python scripting. Then find out how to use graph databases to model many-to-many relationships as nodes and edges. Adam also reviews the smaller enhancements like automatic query performance tuning and the new dynamic management views.

Syllabus

Introduction
  • Welcome
  • What you should know
1. Run SQL Server on Linux
  • Creating a SQL Server 2017 virtual machine
  • Connecting to a VM with PuTTY
  • Installing SQL Server on Linux
  • Differences in SQL Server on Linux
  • Running SQL Server in a Docker container
2. Execute External Python Scripts
  • Machine Learning Services
  • Installing Python
  • Manipulating data with Python
3. Process Data with Graph Databases
  • What is a graph database?
  • Defining nodes and edges
  • Querying graph data
4. Other Enhancements and Additions
  • Resuming online index rebuilds
  • Automatic query performance tuning
  • New dynamic management views
Conclusion
  • Next steps

Taught by

Adam Wilbert

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