162. Introduction to the second part of the course
If you reach this point in the course I must congratulate you on getting the SQL Habit certificate It’s crazy what we’ve been through already – we’ve covered so much material from fundamentals of relational databases to cohort analysis and window functions! Congratulations, dear colleague!
What’s next?
As I mentioned earlier, we’re done with everything an advanced SQL user need to know to answer any question with data. Some might say it’s a super power.
Are we done with learning SQL then? Not yet. Is advanced the ultimate level in SQL game? It’s a great achievement, no doubt. But there’s more.
The goal for the second part of the course is to reach the Expert Level. The word expert comes from expertize.
Expertize – great skill or knowledge in a particular field or hobby.
As we know, great skill comes from experience, from trying our newly acquired knowledge in multiple scenarios, in different contexts, making mistakes and learning from them.
This is why in the next chapters we’ll try to apply everything we’ve learned so far in different contexts and scenarios in the life of Bindle.
We’ll look at mobile apps analytics, apply SQL to analyze AB-tests or product features (like NPS survey or search). We’ll dive into monitoring and setting up alarms with data, very important scenario when data could notify us if something is broken and more.
Our first stop and the topic of this chapter – Product Analytics for mobile apps. Let’s go
SQL Habit is a course (or, as some of the students say, “business simulator”). It’s based on a story of a fictional startup called Bindle. You’ll play a role of their Data Analyst and solve real-life challenges from Business, Marketing, and Product Management.
SQL Habit course is made of bite-sized lessons (you’re looking at one atm) and exercises. They always have a real-life setting and detailed explanations. You can immediately apply everything you’ve learned at work.
“well worth the money”
Fluent in SQL in a month
Master Data Analysis with SQL with real life examples from Product Management, Marketing, Finance and more.