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. Instructor •. Related courses • Course By: Bill Weinman 3h 27m 20s • Course By: Bill Weinman 3h 27m 20s • Course By: Lynn Langit 3h 26m 28s • Course By: Lynn Langit 3h 26m 28s • Course By: Emma Saunders 2h 16m 22s • Course By: Emma Saunders 2h 16m 22s • Course Transcript - [Instructor] SQL has two types of commands: data manipulation commands, and data definition commands.

We're going to discuss data definition commands in this video. Data definition commands are used to define structures for organizing data in a relational database. Imagine you need to manage thousands of paper reports for your job. Now, you could just leave this in a pile and search through the pile every time you need to find a particular report.

However, it's much easier to find a paper report when they're organized in boxes by type of report and then organized within a box by date. The same idea applies to organizing data in a relational database.

We structure data using tables, which are collections of related data records, indexes, which are sets of data about the location of records, views, which are used when we repeatedly want to access the same set of data from one or more tables, and then finally schemas, which are collections of tables, indexes, views, and other data • Practice while you learn with exercise files. Watch this course anytime, anywhere. Course Contents • Introduction Introduction • • • 1. SQL as a Tool for Data Science 1. SQL as a Tool for Data Science • • • • • 2.

Basic Statistics with SQL 2. Basic Statistics with SQL • • • • • • 3. Download Timeline Template Omni Graffle Stencil there. Data Munging with SQL 3. Data Munging with SQL • • • • • 4. Filtering, Joins, and Aggregation 4. Filtering, Joins, and Aggregation • • • • • • • • • 5.

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