Beginner SQL for Data Analytics - No Coding Experience Req'd

Download and set up the required tools: the MySQL database, the Sublime Text editor, and a graphical user interface to write, run, and export SQL queries to Excel.

Discover how the where clause filters SQL results with comparison operators, enabling you to pull only matching records from a salary data table.

Learn how to refine where clauses using and and or to filter data, with examples like zip codes 80002 or 80003, and salaries above 55000 in Boston.

Learn to filter data with and/or in SQL using where clauses to pull customers by zip codes from the customer table, and select first name, last name, and zip code.

Use the in operator to pull a range of data by grouping multiple or conditions. For example, pull ID numbers and locations from salary data table for Boston or Denver.

Learn how to use the sql in statement to filter by multiple values and employ between for numeric ranges, demonstrated with selecting customers by zip codes.

Show how to query customer data using select from where and order by, filter by a zip range, and sort by last name descending for clean data export and analysis.

Explore how the having clause filters grouped data in SQL, using group by and count to include only cities with more than one employee.

Create a query to list inactive customers by joining customer, sales, date tables, filtering last purchase before 2017, and outputting id, first name, last name, email, and last purchase date.

Join the sales and date tables on date_id, then group by year and by quarter to sum revenue for each period.

Connect sales and product tables on product id, pull category, and compute total revenue by armor and weapon using sum and where with in, then group by category.

Learn to create and drop temporary tables in SQL to store intermediate results, reference them later, and use them with joins to compute revenue and analyze survey data.

Create and name a temporary table to consolidate product data, join the survey and sales by product tables, and produce per-product revenue and average score results.