Get the percentage of these specific campaigns that were Facebook campaigns. Join the tables together so all the information is in one place. I’m not trying to trick anyone with the WHERE clause 🙂 Don’t pay too much attention to this part for this example – we’re doing this to establish why we need all three tables, but the point of this example is to understand the joins. Let’s break it down:įilter results so we are only seeing European and Australian campaigns that had success scores above 4. To answer this question, we need to do a few things. Your boss asks you: what percentage of ad campaigns that were launched by the Europe or Australia teams and had success scores above 4 were Facebook campaigns? Check out my understanding SQL blog post for a more in-depth discussino of what SQL is and when to use it. SQL is built for stuff like this, so it will compute joins much faster. Sometimes too, your data will fit into Excel but the VLOOKUP will be so computationally taxing that Excel will simply crash or go so slow it isn’t worth it. That sounds like a lot but SQL databases can hold millions and with more and more data being generated and available every day, there’s a good chance that even at a small company you’ll be dealing with more information than can fit into Excel. Excel can only handle so many rows (a little over a million) and so many columns (a little over 16,000). Usually, you’ll be working with so much data that you have to join the tables together in SQL and can’t just pull everything into Excel and do a VLOOKUP. Understanding the definitions of the joins and how each fundamentally works is very important in SQL. Here, we have the entire nutrition1 table, and next to it the nutrition2 table but broken up so that it matches the id numbers of nutrition1 properly. Outer joins keep everything, no matter what, and line up rows that match. This page is also a great reference to keep handy in case you forget how to do something like change the data type, or import tables. TakeawaysĬongrats! If you made it here, you now have a pretty good idea of how to use SQLite Browser. It’s important to remember to change the data types as soon as you import data into SQLite Browser. Notice it now only returns 61 rows! And these are the correct rows – with total budgets over $60,000. Now go back to the Execute SQL tab and try running the query again (just click the triangle again to re-run it). Finally, change the Type dropdown for the total_budget column to integer. You can tell you’ve selected it because it should be highlighted in blue. Go back to the Database Structure tab, and click on the ad_info table. Since SQLite Browser automatically imports all columns in all tables as TEXT, we need to manually change the data type of the non-text columns. Don’t worry, we can fix this! Modify the Column Types in the Tables So it isnt’ recognizing total_budget as a number, and therefore doesn’t know how to find values greater than $60,000. Why? DB Browser imports all columns as text columns by default. We still go the same number of rows in the result (149), and there are still rows that have a total_budget of greater than $60,000.

Sqlite inner join vs left join