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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, Dan Sullivan shows developers how to analyze query execution plans and use data modeling strategies to boost query performance. Dan 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.

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Instructor Details

Dan Sullivan

Dan Sullivan, PhD, is an enterprise architect and big data expert.

Dan specializes in data architecture, analytics, data mining, statistics, data modeling, big data, and cloud computing. In addition, he holds a PhD in genetics, bioinformatics, and computational biology. Dan works regularly with Spark, Oracle, NoSQL, MongoDB, Redis, R, and Python. He has extensive writing experience in topics including cloud computing, big data, Hadoop, and security.

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