Complete SQL Bootcamp for Data Science, Analytics, Marketing

Explore a range of databases, including MySQL, PostgreSQL with JSON support, MongoDB, and SQLite, and learn about Hadoop, Hive, Cassandra, and SPARC on Hadoop.

Discover how a relational database stores data as related tables of rows and columns, linking users, orders, and products.

Download the course data from GitHub, create a database, and run the import to populate the user_actions table, while generate_actions.py creates the CSV with name, product, action, price.

Learn sql query structure by selecting all columns from the user actions table, filtering with where clauses, and applying operators as equals, is not, and, or, ending with a semicolon.

Master SQL create table syntax by defining a table name and column types (text, varchar, integer, real, blob, date time) in a comma-separated list, ending with a semicolon.

Demonstrates importing data from a CSV into a SQLite database on Windows, mirroring the Mac workflow, using mode, import, and verify commands with the user_actions table.

Discover how to modify a table's structure by adding a new column with alter table, enabling future data and queries, and understand the option to create a new table instead.

Drop a column in SQLite version 3.35.0 by using alter table drop column, demonstrated on a sample table with first name, last name, and email, then verify with schema.

Introduce a suggestion box concept for feedback on the course, inviting learners to share background, course context, difficulty, missing topics, and requests for future courses.

Learn how indexing speeds up lookups in relational databases using plain, unique, composite, and primary key indexes, including auto increment behavior in orders and users tables.

Demonstrate how indexing the name field speeds queries on a large user_actions dataset, showing timing improvements after rebuilding the table and loading big actions data.

Master the basics of modifying data in a table by inserting, updating, and deleting rows. Learn practical syntax and examples using an orders table, including handling defaults and conditions.

Contrast MVC architecture with data, UI, and server code, and explain CRUD—create, read, update, delete—mapped to HTTP methods POST, GET, PUT, DELETE for SQL and NoSQL databases.

Learn how to join and merge two tables—the user actions and the users table—using inner, full outer, left outer, and right outer joins, with on clauses and multi-column options.

Perform an inner join between user actions and the users table to retrieve name, product, and location, importing users and qualifying the name to avoid ambiguity.

Explore essential SQL functions for analytics, including count, distinct, sum, min, max, and avg, with practical examples like filtering for mango purchases and summing prices.

Learn to group by the product to total its price, then order by revenue descending and use limit to show the top 3 products.

Analyze funnels to identify drop-offs and improve conversion, compute year-over-year revenue by month using a time-formatting function, and rank sales by location with joins across actions and users tables.

Learn to load an extra dataset in tab-separated values, switch the mode to tabs, create tables for ordered_items and customers, import data, handle headers, and clean erroneous rows.

Leverage the IN keyword to replace long OR chains with a single array of values in parentheses, and use NOT IN for exclusions in SQL.

Learn to filter prices between 100 and 200 using the between keyword, explore not between to exclude ranges, and compare with greater-than and less-than operators.

practice interview-style sql using the ordered items and customers tables with inner joins and group by to identify distinct items in oregon and the most popular item in colorado.

Ask questions in the Q&A to clarify gaps and stay on track. Meet the prerequisites and implement everything from theory to code to succeed in this state-of-the-art SQL bootcamp.

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