Advanced SQL for Data Scientists

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Created by: Dan Sullivan

Produced in 2017

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Course Description

There is an increasing need for data scientists and analysts to understand relational data stores. Organizations have long used SQL databases to store transactional data as well as business intelligence related data. If you need to work with SQL databases, this course is designed to help you learn how to perform common data science tasks, including finding, exploration, and extraction within relational databases.

The course begins with a brief overview of SQL. Then the five major topics a data scientist should understand when working with relational databases: basic statistics in SQL, data preparation in SQL, advanced filtering and data aggregation, window functions, and preparing data for use with analytics tools.

Advanced Level

Time: 1h 24m

Instructor Details

Dan Sullivan

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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.