Output #1
This may seem like another blog post nobody cares about, and it probably is. But that’s okay. I don’t need this to be viral. I don’t need this to be special. This is just a way to create output about what I’m learning. I struggle with information intake and low information output, and if I’ve learned anything, it’s that the output is what actually provides me with proof that I’m moving forward.
I’ve dabbed with a lot of stuff. And I consistently interrupt with the next new shiny object. Content creation, blockchain, SEO, Cloud, Data science, and now AI. I’m easily attracted to novelty. But that’s all it ever becomes, novelty consumption, no depth. And I get bored almost as quickly as I jump into it. I start something else, and so the loop goes on.
This time, I want to try to do things differently.
Learn something. Fail at it. Fail again. And fail better. Funnily enough, it’s in SQL. This was the first field I got interested i,n which was a little out of my field. I can see how it complements my academic formation, but once I faced the friction of getting code wrong, I just dropped it and moved on to something else, probably blockchain or SEO.
I started the Associate Data Analyst in SQL Track at Datacamp. I remember having encountered SQL already a few years ago, but I was stuck studying and finishing my thesis in the middle, and dropped out. But I knew that working in content creation and journalism, Data analysis would help.
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As of now, I’m at the Intermediate SQL course. Passed the beginner bi already (Yay!) Here’s what I’ve learned so far:
- Databases and tables aren’t the same thing
- SQL is a language for relational databases
- The coding language, the clauses themselves, are preferably written in caps
- Clauses I’ve learned so far are: SELECT, FROM, WHERE, LIMIT, and COUNT.
Databases and tables aren’t the same thing
From what I’ve understood at this point, databases are more like the storage of data itself, and tables are the units in which those databases are made up.
SQL is a language for relational databases
Relational databases store data in a tabular format (rows and columns) with defined relationships between different tables.
Clauses: SELECT, FROM, WHERE, LIMIT, and COUNT
The keywords used in SQL are called clauses, like most words in programming.
- SELECT: this is the keyword for establishing which column you’ll be referring to. To select all, you can add an asterisk (*)
- COUNT: this is the keyword that counts unique values within a specific field. That field is actually the column we’re digging into and needs to go in parentheses. Ex: SELECT * COUNT(Stars)
- FROM: this is the keyword for choosing the table you’re going to work with. This usually goes in the middle of the SQL expression.
- WHERE: this is the keyword for filtering specific items. Here we use mathematical operators to filter out the result of what we’re looking for: <, >, ≥, ≤, or =. And it’s not only numbers. We can filter out words by creating a string with single quotes (‘ ’). In this quote is what we’re looking to match.
- LIMIT: this is the keyword that should go at the end of the whole code, establishing the number of results you want to get back. Then of course, you close the request with a semi-colon (;).
Final thoughts
That’s all I got for now. Looking to move forward in the SQL journey and analyze large datasets my own way. Not sure if this will help anyone, but if it does, I wish you the best on your journey into SQL.
