Welcome to Module 3. In this module we'll focus on data extraction from relational databases using structured query language or SQL. Up till now, we've been focused mostly on thinking about analytical problems and understanding where data comes from and how we capture and store it. Now we take our first step in actually working with and manipulating the data we need in order to execute an analysis. As an analyst the ability to extract data from a database yourself, is one of those skills that can really enhance the value you bring to an organization. It makes you more efficient and more effective, since you gain a much deeper level of understanding of the database itself and the data it contains. There are two thing about SQL that make it really great to learn in specialization like this one. First, it's incredibly simple. By the time we finished this module, you'll learn the basic commands and operations that drive 80% to 90% of the SQL coding we see in data analytics. Secondly, SQL is almost ubiquitous. While there are many other languages that companies use either directly or indirectly to support analytics, SQL is easily the most common. And there's a really good chance you'll find it in just about any organization working with databases. And even if you don't end up using SQL, you can benefit from learning the thought process that goes into writing it. It's the same thought process you'll need to go through regardless of how you get data out of your databases. By the end of this module you should be able to construct simple to moderate SQL queries using a set of basic commands. Namely select, from, where, group by, having, and order by. Combine or stack data from multiple tables using join and union commands. Enhance queries using relational, arithmetic, and logical operations, and build even more complex queries by utilizing sub queries. This will be your first chance to get your hands dirty with some actual data work. So I hope you're as excited as I am. And I hope you'll love writing SQL as much as I do.