SQL Server Management Studio
Index and Statistics
The course is part of this learning path
Information is at the heart of most software systems and the lifeblood of many organizations, so you want the database that stores this information to be efficient and reliable. But as we know, things happen; sometimes bad things. One of the ways that we can prevent bad things from happening is to know about them in advance like the old saying says, "To be forewarned is to be forearmed."
Azure SQL in its many forms has an abundance of features that help you to monitor the state of your databases and database server. Ranging from prebuilt automated monitoring that is augmented with artificial intelligence through to dynamic management views, SQL Server monitors and logs all aspects of the database engine’s operation and configuration. Intelligent Insights and Azure SQL analytics enable you to easily access the wealth of diagnostic and performance data in an easily digestible format.
This course introduces you to the different database monitoring and notification technologies available, how they work, and how to use them. If you have any feedback relating to this course, feel free to contact us at firstname.lastname@example.org.
- Understand the key elements of database monitoring
- Learn about the features of Intelligent Insights, Azure's AI-based database monitoring service
- Create graphical reports using SQL Server Management Studio
- Understand how wait statistics can show you where threads have to wait and how this can be used to monitor performance
- View and fix index fragmentation
- Monitor database storage
- Implement notification alerts on various database platforms
This course is aimed at database administrators or anyone who wants to learn how to implement systems that can find potential issues that may disrupt the delivery of their database services.
To get the most out of this course, you should have experience with SQL Server Management Studio, be familiar with reading and writing SQL, and have an understanding of basic database architecture and administration tasks, like indexes and backups.
Course Related SQL Scripts
One of the main pillars of the scientific method and experimentation is the concept of the control group. The control group is a state or population that is isolated from the experiment, by comparing the control group with the experimental group scientists can determine if variables they are manipulating have had any effect.
You can think of a database in operation as an ongoing experiment with dozens of variables being manipulated simultaneously. While there are absolute values or states like the database has completely stopped functioning, for the most part, we need a control group to compare the current state, or in our case, the diagnostic data with, to decide if some adverse change has happened.
In real-world terms, this relates to a scenario that I'm sure many of you are familiar with where a user will complain about the system being slow. So, you ask, "How slow?" They reply, "It used to be fast and now it's slow." This is not helpful, and if only there was some way to quantify slowness. This is where baseline measurements come into play.
Hallam is a software architect with over 20 years experience across a wide range of industries. He began his software career as a Delphi/Interbase disciple but changed his allegiance to Microsoft with its deep and broad ecosystem. While Hallam has designed and crafted custom software utilizing web, mobile and desktop technologies, good quality reliable data is the key to a successful solution. The challenge of quickly turning data into useful information for digestion by humans and machines has led Hallam to specialize in database design and process automation. Showing customers how leverage new technology to change and improve their business processes is one of the key drivers keeping Hallam coming back to the keyboard.