Why You Should Learn SQL
SQL can be scary; even its name, Structured Query Language, is enough to deter you from even trying to learn about it. Once you get down to the nitty-gritty, though, you’ll see, not only do the daily tasks you execute in Excel translate directly and easily, but SQL has a few more tricks up its sleeve.
Teaching SQL at PMG has taught me a lot, and before I begin the lesson, I love to first explain how SQL can alleviate some of those daily headaches that arise from data-intensive reporting. Headaches coming from challenges such as:
The pinwheel of death: Excel crashing because you have too much data.
Filtering the wrong data: Filtering data for the most basic needs is difficult enough, but trying to filter spend, return on investment (ROI), and other advertising metrics? We wish you good luck. For instance, sometimes you need it to be A, B, and C, but C without D and Excel is pretty limited in what it can and cannot filter.
Pulling the wrong data/wrong date range: How many times have you pulled and pivoted data only to realize you left out a critical column or pulled a slightly wrong date range?
Mistakes with Excel: If you’re making changes or adding columns, you’re directly editing your source data. So if you hardcode new data, you’ve messed with the real data, and you may never get that back, and that can cause significant problems later down the line.
Creating new columns and building a new column: Often, we’re categorizing data in the same way, over and over, every day or every week, and that can be a huge waste of time.
SQL solves all those challenges and more.
SQL is faster. Excel can handle a lot of rows, but it starts to get real slow (or worse, crashes) if you’re doing anything with them. On the other hand, you can filter, pivot, and do calculations off a million rows or more in SQL without crashing or experiencing much lag.
SQL is forgiving. Wrong date range? Wrong column? Incorrect formula? In Excel, that can sometimes mean re-pulling the data all over again or backtracking. In SQL, that’s just a few keystrokes, and you’re back in business. And because SQL is not directly editing the original table, there’s no mistake too large to fix or revert.
SQL is flexible. Data is messy, and SQL can accommodate those messes and intricacies very easily. And because you can layer functions and processes on top of each other, you can significantly reduce the number of steps it takes to get to your cleaned data.
SQL is time-saving. Thought I was going to use another f-adjective? I really did try, but much like SQL, I didn’t spend a whole lot of time on it because I have things to do, like splitting out audience names from my adset names or categorizing my campaigns into different tactics. Speaking of, SQL can do all of those things for you again and again, without having to be rewritten or having to re-do that work. A simple case statement, or split part function can do either of those tasks and the next time you need it, you just need to re-run the SQL and voila! Done.
SQL is simple. It doesn’t take a lot to get started. A simple ‘SELECT * FROM’ and you are well on your way.
There is a learning curve when it comes to SQL, but it’s pretty small, and in terms of learning a new language, it’s one of the easiest ones out there, no Duolingo necessary. I’m a big fan of w3schools, but a simple google search will provide you with more resources than I could ever list. It may take some time to get used to it.
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At first, doing it manually in Excel will feel faster, but in the long run, learning SQL will benefit you much more and save you way more time than you invest in actually learning it. So take the plunge, put in the work, and you’ll be fluent in SQL in no time; there’s no time to start like today.