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So now we move on to tables.

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This is the real heart of SQL.

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Yes, we make a new database.

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We use a database that's important to know.

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But like I said previously, we do that occasionally, but then we constantly work with tables and the

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data inside of tables within a given database.

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So we have this empty shell of a database or maybe multiple empty shells of databases.

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They have nothing in them.

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Tables are what we need to put in those databases so that we can hold data.

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So you may have heard the term table before.

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A database is really just a bunch of tables.

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Now, when I say database, that only applies to a relational database.

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If we're talking about something like MongoDB, that's not a relational database.

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So it doesn't use tables, but all the SQL flavored database variance, they all consist of a bunch

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of tables and tables are what hold our data.

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They describe the format and the shape of our data, and then they hold collections of data that follows

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that shape.

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So a more technical definition would be a table is a collection of related data held in a structured

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format within a database.

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Now that structured part is very important.

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Also, the fact that it's a collection of data is very important.

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So let's say that we were working with cats data.

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We're building a pet shelter or a vet database or something.

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This would be one way to structure my information.

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I could say this is what a cat looks like in our database.

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This is the cat's table.

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Every cat has a name.

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Every cat has a breed, every cat has an age.

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I'm defining the structure.

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That's the first part of a table, and it will start empty.

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This one is not empty.

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And then we insert data into the table following that structure.

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So every cat has a name, a breed, and an age.

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So some basic terminology we call the headings or the headers of each table columns.

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So this table has three columns.

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Now I'm visualizing it here right as an actual table.

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It's not stored this way.

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It's stored as some compressed thing that looks nothing like human readable code, but it will be displayed

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to me nicely in the same way that we see this right here.

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Print it out.

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It looks like a table.

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But again, this is just a slide diagram that I'm drawing for you.

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This has nothing to do with SQL on its own.

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Okay, so we have our columns name, breed and age, and then we have the rows.

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Those are the actual entries, the actual data in the table.

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So we have one row here.

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Blue is a Scottish fold.

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She's one year old.

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We have Rocket who's a Persian cat, three years old and so on.

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These are all rows, their entries into this table.

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But the first step is to get this table empty.

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But with a structure we're telling SQL.

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Okay, here's our cat's table.

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It has these three different columns, the three pieces, and then once that's done, we can insert

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data in.

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So databases in general consist of lots of tables.

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Well, I say that referring to a large application or even just a basic application you might work with.

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There's going to be lots of different entities and almost every entity will have its own table.

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So there might be a user's table, a friend's table, a photos table.

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If we are making some sort of Instagram clone or something, a comment table and all sorts of stuff

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for advertising and for tracking users and user behavior, you could have hundreds of different tables

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so it can get a little crazy.

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Here are some simple ish examples.

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This is some of the tables that exist in the Wikipedia SQL database.

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Now, this is coming from Wikipedia.

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It could be out of date, but we'll see things like a user.

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Every user has a name and a password and an email and a whole bunch of other things.

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But then we have pages, Wikipedia pages, right?

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And Wikipedia revisions because people can revise pages.

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There's different sites, there's logs that are written images and files and all sorts of other things.

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We don't have to worry about tags, lots of information here that is stored all in separate tables.

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Now, of course, most of these tables are connected or related in some ways, like pages and users

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or revisions and users.

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Who's making the revision?

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Well, some user is so there's some connection, but we're not worrying about that just yet.

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Here's another example.

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This is an old very out of date attempt at modeling the table structure of a website like Facebook.

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We have things like basic information for a user sex.

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If they're interested in men and women, you can tell this is out of date.

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I guess that they even break it down that way.

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Looking for friendship, relationship.

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All right.

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Basic information, contact information.

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But then we have things like a profile, an account, a credit card, different events.

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We have photos.

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All these different entities are.

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Senate with their own tables and again, lots of lines connecting them together.

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So we are not starting there.

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We're starting with good old cats, three columns, a couple of rows, but we have to learn how to make

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a table.

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And before we can create a table, we have to talk about data and the different types, the different

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categories of data we can work with.