Advanced SQL for Query Tuning and Performance Optimization

COURSE DESCRIPTION

SQL queries can be fast and highly efficient, but they can also be slow and demand excessive CPU and memory resources. For many SQL programmers, occasional bouts with long-running queries and poor performance are simply par for the course. But by gaining a better understanding of how databases translate SQL queries into execution plans, you can take steps to avoid these issues. In this course, this course shows developers how to analyze query execution plans and use data modeling strategies to boost query performance. It describes how SQL queries are executed; highlights different types of indexes and how they factor in query tuning; covers several methods for performing joins; and discusses how to use partitioning and materialized views to improve performance.

Audience

This course is for just about anyone responsible for the performance of the system. Database administrators, certainly, are targeted because they’re responsible for setting up the systems, creating the infrastructure, and monitoring it over time. Developers are too, because who else is going to generate all the well-formed and highly performant T-SQL code Database developers, more than anyone, are the target audience, if only because that’s what I do for work. Anyone who has the capability to write T-SQL, design tables, implement indexes, or manipulate server settings on the SQL Server system is going to need this course/tutorial to one degree or another. Therefore

Who should take up this MS SQL certification training course?

• Software Developers and IT Professionals
• SQL and Database Administrators
• Project Managers
• Business Analysts and Managers
• Business Intelligence Professionals
• Big Data and Hadoop Professionals
• Those aspiring for a career in SQL Development

Topics include:

• How SQL executes queries
• Working with PostgreSQL tools for tuning
• Bitmap and hash indexes
• Using different types of indexes to improve performance
• Challenges with joining tables
• When to use partitioning to improve performance
• Collecting statistics about data in tables