If you’ve been around in the data space for any length of time, chances are you’ve heard of something called SQL. It’s quite a common buzzword you’ll hear in the data space. It’s easy to think that SQL is just another program, one in a list of many you’ll only have to interact with once or twice.
If you’re thinking like that, you would be VERY wrong. SQL – short for Structured Query Language – is one of the most common querying languages in the world. It’d be a challenge to find a company larger than a single store that doesn’t use SQL in some format under the hood, and it’s relatively approachable for humans to understand it, as well. If you need proof of how ubiquitous it is, here’s a screenshot of tableau, showing all the server types it can connect to. The ones in black squares? They’re SQL-based, and they make up nearly half of all the server types Tableau is prepared for.
So yeah. SQL is… stunningly important.
In the context of Data Analysis, the main thing you’ll be doing with the Structured Query Language is… well, Querying. By using the querying language
In this, I’m going to be going over some of the basics when it comes to SQL querying – namely, the structure of Select Functions. In the second part, I’ll go into more fancy things you can do with it, including subselects, joins, and more.
The Pieces of a Select Function
A select query returns a table Most Select queries consist of up to six simple parts:
- SELECT <column1>, <column2>
- FROM <table>
- WHERE <filtering condition>
- GROUP BY <grouping column>
- HAVING <filtering condition 2>
- ORDER BY <column>
SELECT is where you put in the columns you want from your query