Advanced Applied SQL for Business Intelligence and Analytics

This example-driven course provides thoughtful and interactive commentary throughout. We understand the common mistakes and misconceptions you might make and help you navigate tricky SQL concepts.

Window Functions are used in detail throughout the course to solve problems dealing with finding the first order or the Nth instance of an event, computing the timing between events, and new and repeat purchase behaviors among customers. You'll run through the workflow from SQL to a localhost connection in Tableau and also analysis, all of which you'll need in your professional life. Concepts such as CASE statements, common table expressions, and subqueries will be explained via case studies. You'll generate web analytics acquisition source data using Python and then create tables to store your information.

By the end of the course, you will have gone through all the examples and coded them out, and you'll be ready to confidently tackle non-trivial problems. Supercharge your data productivity today with this course and get 100x your time investment back in the next year or two!

What You Will Learn

• Put SQL to work for Business Intelligence
• ]Develop your SQL skills to advance your career
• ]Master advanced topics such as materialized views, common table expressions, advanced data grouping, and more!
• Bring data into Excel, Tableau or other business software for further analysis and visualization
• Uncover key insights about your customers, suppliers, and business performance
• Use your database to make crucial business decisions and grow the bottom line
• ]Avoid common mistakes that cost you credibility and time

Audience

The course is for analysts and developers who have a basic understanding of SQL and interact with data and databases; it will help them understand query complexity with ease.

About The Author

Jeffrey James: Jeffrey James has been working in the analytics and data space since 2006. With roots in digital marketing and web analytics, he's applied analytical techniques to problems including customer value analysis, financial forecasting, machine learning, and process automation. He's made his share of mistakes on the way to mastery and understands the mindset of a beginner/learner.