196: I wish I knew this before I learned SQL

Speaker: 00:00:00

Here are the seven things I wish I

knew before learning SQL number one.

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: 00:00:04

SQL is incredibly easy and

insanely complex at the same time.

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: 00:00:09

And let me explain.

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: 00:00:11

SQL is like an iceberg.

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: 00:00:13

In fact, there is a famous sequel

meme with an iceberg with a different

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layers of SQL that you could

possibly learn in your data career.

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: 00:00:20

And honestly, the first half,

the first little bit of the

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: 00:00:24

iceberg is really easy to learn.

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: 00:00:25

The commands that you need to

learn as a data analyst are

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: 00:00:29

really not that hard to learn.

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: 00:00:30

They're easy to get a hold of

eventually, and there's really only

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: 00:00:33

17 of them that you need to know.

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: 00:00:35

We'll talk about those here in a second.

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But the crazy thing is

it's also insanely complex.

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There's like a bajillion different

commands you could know in

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sequel, and there's so many

different levels and layers to it.

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: 00:00:47

There's a bunch of stuff

that I don't even know.

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: 00:00:49

So for example, if we look at this

iceberg meme right here, like you'll

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see that the easy things are at the top.

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The order buy and the group

buy, and the limit and the null

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and joins and stuff like that.

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: 00:00:59

And then it gets more and

more complex as you go down.

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: 00:01:03

Like for instance, even in the

third layer, lateral joins, I've

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: 00:01:06

never even used lateral joins.

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: 00:01:08

Cursors never used those as well.

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: 00:01:10

Triggers I have used a little bit, but

my point here is it goes so far down

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: 00:01:13

where it's like in this second to last

layer down here, like with the narwhal,

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I don't even know any of that at all.

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So my point here is you can make it

like me, senior data analyst, who's

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worked in the field for 10 years,

who teaches people data analytics.

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: 00:01:27

And you could not even

scratch a service of sql.

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And that's perfectly okay because I know

the first two to three decently, well, the

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first two at least, and it solves like I

would say, 90% of data analysts problems.

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And we'll actually talk

about that here in a second.

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: 00:01:40

What is a SQL problem or a data

problem that someone, a data

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analyst actually solves with sql?

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: 00:01:45

Because not all of SQL commands

are made for data analysts.

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So in my opinion, if you're just getting

started, you can get by with like 17 SQL

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commands and they are the following ready.

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Number one, select number

two from number three.

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Where?

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: 00:02:01

Number four.

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Group by number five.

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: 00:02:04

Order by number six.

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: 00:02:05

Like number seven, count.

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: 00:02:08

Number eight, max in min, uh, number nine,

average number 10, some number 11, case

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when number 12, join number 13 distinct.

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Number 14, having number 15

with number 16 partition by,

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: 00:02:25

and number seven, uh, 17 concat.

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: 00:02:28

Now there's some other ones you possibly

could use as well, like Union is another

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one that probably is used pretty often.

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: 00:02:34

Um, maybe you could ar argue like

some sort of rank would be useful,

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: 00:02:38

um, or some sort of like day

function or something like that.

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: 00:02:40

But my point here is there's really

not that much to get started with.

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Like if you can get those 17 things down,

you can land a day job a hundred percent.

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And I honestly think you can

learn those 17 things in like

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three weeks if I'm being honest.

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And that's how fast I teach them.

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Inside of my bootcamp.

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You know, I run data Alex

Accelerator, it's a bootcamp.

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We teach SQL and we do it in two weeks.

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The sequel portion, and I think that's

good enough to land your first data job.

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If I'm being honest.

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Now, that's about 30 hours of work

probably, but I literally think

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: 00:03:09

if you spend 30 hours on this,

you can learn it pretty easily.

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: 00:03:11

By the way, if you found this list

helpful, I send out a weekly newsletter

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: 00:03:14

with tips just like this, and you

can join 30,000 other aspiring data

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: 00:03:18

analysts to get these weekly tips in

your email@datacareerjumpstart.com

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: 00:03:23

slash newsletter, or there is a

link in the show notes down below.

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: 00:03:26

But sign up because I send awesome

stuff like this every single week.

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That actually brings me to my second

point, which is that you don't have

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to have all your SQL syntax memorized.

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It's basically impossible.

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Like I showed you, there are so many

different commands that you could be

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learning so many different commands that

you could be using, and you might be

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using Excel, you might be using Tableau,

you might be using Power bi, might

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using Python, all on top of SQL as well.

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And those have different syntaxes

and so it's really hard to remember

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all the different syntaxes, so you

don't have to have it memorized.

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It's not a problem if you forget.

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I forget all the freaking time it happens.

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N nearly like.

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Every day, to be honest, probably

more than I should tell you guys

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on YouTube, but I'm forgetful.

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I've never been a good memorizer.

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And the cool thing is you don't have,

you definitely don't have to have

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it memorized for the job, right?

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When you're at the job, there's not

like someone over your shoulder like

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making sure you know how to do this.

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Now, you should obviously know the basics.

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That's, that's a given, like

select from group by those

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where those types of things.

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You should definitely know the backbone of

sequel, probably by, by heart or by hand.

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Um, but like the more complex

stuff, the more syntax stuff, you

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definitely don't have to know.

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Um, where this might not be true is in

an interview, in an interview for some

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reason in the data world, we just love

to, Hey, do you have this memorized?

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No, you suck.

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You're never gonna get hired.

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You reject you.

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Like that's just how it is.

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I don't know why it is.

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I hate interviews like that, but

there are some sequel interviews

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that do kind of treat you that way.

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I think it's basically like if you don't

know that you don't know enough to do the

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job, but I don't agree with that interview

process, but that's just how it is.

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So just telling you that to be prepared,

uh, especially in today with like a

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lot of these editors that will actually

like, kind of fill in the syntax

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for you or suggest syntax for you.

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With chat, GBT, with Claude, with

Google, like you really can figure out

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what you need to do or, or how to do

what you wanna do in a moment's notice.

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And so memorization, the need

for it is just going down.

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I don't think you need to be memorizing

something and you shouldn't feel bad

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if you don't have things memorized.

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Number three, there's actually a

ton of beginner sequel commands that

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you may learn in an online tutorial

that are absolutely useless and

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you should really never use them.

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Or rather you won't use

them in your career.

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And the reason is.

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Is data analysts.

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We do a lot with databases, right?

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But really, most of the time, I'd say

90% of the time, we don't actually

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create, alter or delete databases.

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We aren't really managing databases.

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We're querying databases,

which, querying is a funny word.

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It basically means you're

asking questions to the data.

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That's your job as data analysts is

to query the data in the database.

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And so really data

engineers, data architects.

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Uh, maybe an analytics engineer.

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Their job is to more create the database

structure and everything like that.

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Your job as data analyst is just

to answer business questions with

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the data that they provide you.

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And so there's certain things and certain

tutorials that will tell you that you

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need to know some commands, like insert

or delete or update grant or provoke,

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and you don't need to know those.

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You don't need to know those at all.

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: 00:06:13

That's like more data engineering and

they often call those DCL and DML,

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which stands for data control language

and data manipulation language.

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And basically, in my opinion, you

don't need those at all within sql.

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If you're gonna be a data analyst,

at least not at the beginning.

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Like don't waste your time.

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And I'm telling you, if you go to, if you

like Google SQL tutorial, one of the first

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things they're gonna teach you is like,

okay, this is how you create a a table.

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This is how you delete a table.

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This is how you update a row.

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Do insert into to populate your database.

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And those are good things to know.

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I'm not saying like that's

a bad thing to know.

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I'm just saying if you're in a

crunch for time, which we all are

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today, and if you're a career pivot.

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You don't have unlimited time, so you

have to figure out what to spend your

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time on, and I'm telling you, I wish

I wouldn't have spent time on this.

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The fourth thing I wish I knew when I

was starting SQL is that you actually

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don't even really have to know SQL.

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Now.

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SQL is really in demand, like it is the

most in demand data tool out there across

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all the different data disciplines.

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That being said is like everything

that you can do in sql, you

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can kind of get away with.

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In some other data software.

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So for example, a group I in SQL is

really just a pivot table in Excel and

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you can do the exact same manipulation.

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Inside of Pandas as well with

a group by function there.

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You can join Excel tables.

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You can join Google Sheets, Tableau and

Power BI both have a bunch of no code

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data manipulation tools built into their

softwares so that you can actually do

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like a bunch of data manipulation that you

could do in SQL inside of their softwares

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without having to write SQL code.

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I really think you should learn sql.

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I think it's worth your time.

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But that being said, just know that

you can do everything that you can

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do in SQL in a different software.

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So if you're an Excel master, you can

probably figure out how to do whatever

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you need to do to the data that you

would do in SQL inside of Excel.

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You don't have to learn every single data

tool, and if you try, you're gonna be like

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a hundred years old before you actually

ever feel ready to apply to any job.

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My point here is just don't feel that

bad if you don't know sql, but you

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should probably learn it anyways.

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Tip number five is that you need to

have an IDE and an IDE stands for

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Integrated Development Environment.

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And what does that stand for?

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Well, when I was first like

breaking into data, I knew

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software, I knew Excel, for example.

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Uh, and when you download Excel,

you hit download Excel, and then

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you can, you know, click on Excel

and it opens up Excel and then you

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can analyze data inside of Excel.

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Well, SQL is a little bit

more complicated than that.

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First off, there's not just like

one software that's called SQL

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and you hit download on sql.

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There's a bunch of different flavors

and different like sub languages of sql.

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Um, the more popular ones are MySQL,

SQL Lights, Microsoft SQL Server.

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Um, Snowflake's becoming more popular.

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Uh, but my point in telling you this,

if you were to download, for instance,

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MySQL, you wouldn't be able to just

like double click it and it would open

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up and you can analyze data in sql.

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You need what's called an IDE or

often SQL's called a workbench.

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And basically this is like a secondary

or like a companion software that

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comes with the actual download

of SQL that lets you use it in a

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non terminal, non-car coder way.

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So just know when you're

going to download sql.

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You probably need to download some

sort of an IDE or some sort of a

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workbench for you to be able to use

it, and that's a little bit confusing

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and a little bit difficult to set up.

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This is one of the reasons why

when I teach SQL inside of the data

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analytics accelerator, we actually

do the first week without downloading

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an IDE or even downloading anything.

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We actually just use a SQL

version inside of the cloud.

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That allows you to just get the hang

of SQL, of the actual language before

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you have to deal with like the annoying

logistics of downloading and installing.

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'cause that's a pain in the butt always.

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I've done it like literally a

hundred times and I hate downloading

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SQL every single time I do.

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It's a pain in the butt.

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Just trust me.

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: 00:09:39

It's not fun.

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But hey, if I went back and I

could tell myself one thing,

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I'd be, Hey, you need an id.

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If you're just gonna try to do it

without an id, it's not gonna work.

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That brings me to my sixth tip,

and that is that you need to

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use the limit function in sql.

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If you run a SQL query, SQL will

give you back all the matching

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rows that match your query.

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And a lot of times if you're using

a big database, that could be,

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you know, it could be five rows,

but it could also be 50 rows.

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It could be 500 rows.

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It could be 5,000 rows.

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: 00:10:06

It could be 500,000 rows.

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It could be 5 million rows.

229

: 00:10:09

If you're trying to return 5 million

rows, it's gonna take a long time

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to return that, uh, especially

if you're maybe not the best at

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: 00:10:15

optimizing queries and stuff like that.

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So my advice to you is to make sure

you're using the limit at the end,

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and that will actually, like if you do

limit to 10, that will only give you the

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first 10 out of the 5 million, so that

way you can test your queries first.

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You know, on a smaller

result base, so it's fast.

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And then once you're sure that the

queries kind of work in the way that

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you want, you can take that limit

to: 1000

238

: 00:10:36

And then you can make sure

that everything's still working

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: 00:10:37

the way that you want, but you

don't have to wait very long.

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The seventh thing I wish I knew is that

getting good at SQL doesn't equate to

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actually getting hired because a lot

of you guys probably watching this

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: 00:10:47

right now are applying data jobs.

243

: 00:10:49

And you're getting rejected.

244

: 00:10:50

You're getting rejected.

245

: 00:10:51

You're not even getting

like an interview, right?

246

: 00:10:53

And you're like, oh man, I just

gotta get better at sequel.

247

: 00:10:56

It's like, why, why do you think

that you, you're probably already

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: 00:10:59

proficient enough at Seql.

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: 00:11:00

Or if you're not, like I said,

you can get there in like a month.

250

: 00:11:03

So if you're gonna go like, you know,

hit leak code really hard or just

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: 00:11:06

like practice seql problems, that's

not gonna equate to landing a job.

252

: 00:11:10

It's just not, because right now you're

not getting rejected because you're

253

: 00:11:12

not gonna a sequel getting rejected for

some other reason probably that your

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: 00:11:15

resume and your LinkedIn aren't good.

255

: 00:11:17

Um, and so really when it comes

down to it, SQL is just like.

256

: 00:11:20

Maybe one 15th of landing

your first data job.

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: 00:11:23

In my opinion, it's just one

third, it's just a skill, right?

258

: 00:11:27

So I have this method, it's called the

SPN Method Skills Portfolio Network.

259

: 00:11:31

You need all three to land a data job.

260

: 00:11:32

Most people are just focused on

the S part, the skill part, and

261

: 00:11:35

SQL is just one part of the S part.

262

: 00:11:37

So it's like one 15th

of the whole equation.

263

: 00:11:40

And if you're just focusing on sql,

you're missing out on so much more,

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: 00:11:43

like your portfolio, your projects,

you're networking, your cold

265

: 00:11:45

messaging, your resume, your LinkedIn.

266

: 00:11:47

And so it's important

to get good at sequel.

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: 00:11:49

Yes, I'll give you that.

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: 00:11:50

But it's also important not just to

get stuck in the grind of doing these

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: 00:11:53

sequel problems over and over and

over again, thinking that's somehow

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: 00:11:56

gonna magically get you a job.

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: 00:11:57

Because it's honestly not.

272

: 00:11:58

And if you do wanna know what's

gonna get you a job, it's actually

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: 00:12:01

following the full SPN method.

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: 00:12:02

So that's of interest to you.

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: 00:12:03

If you've never heard of the SPN

method before, I will have a link down

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: 00:12:07

below to learn about the s PN method.

277

: 00:12:08

And I also have a link to my bootcamp,

which literally will teach you to

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: 00:12:11

become a data analyst from wherever

you're at, to landing your first data

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: 00:12:14

job, following the SPN method, step by

step, step-by-step with instructors,

280

: 00:12:17

with peers, and a lot of fun.

281

: 00:12:19

So hope to see you guys there.

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