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.

2

: 00:00:04

SQL is incredibly easy and

insanely complex at the same time.

3

: 00:00:09

And let me explain.

4

: 00:00:11

SQL is like an iceberg.

5

: 00:00:13

In fact, there is a famous sequel

meme with an iceberg with a different

6

: 00:00:17

layers of SQL that you could

possibly learn in your data career.

7

: 00:00:20

And honestly, the first half,

the first little bit of the

8

: 00:00:24

iceberg is really easy to learn.

9

: 00:00:25

The commands that you need to

learn as a data analyst are

10

: 00:00:29

really not that hard to learn.

11

: 00:00:30

They're easy to get a hold of

eventually, and there's really only

12

: 00:00:33

17 of them that you need to know.

13

: 00:00:35

We'll talk about those here in a second.

14

: 00:00:37

But the crazy thing is

it's also insanely complex.

15

: 00:00:41

There's like a bajillion different

commands you could know in

16

: 00:00:44

sequel, and there's so many

different levels and layers to it.

17

: 00:00:47

There's a bunch of stuff

that I don't even know.

18

: 00:00:49

So for example, if we look at this

iceberg meme right here, like you'll

19

: 00:00:52

see that the easy things are at the top.

20

: 00:00:54

The order buy and the group

buy, and the limit and the null

21

: 00:00:58

and joins and stuff like that.

22

: 00:00:59

And then it gets more and

more complex as you go down.

23

: 00:01:03

Like for instance, even in the

third layer, lateral joins, I've

24

: 00:01:06

never even used lateral joins.

25

: 00:01:08

Cursors never used those as well.

26

: 00:01:10

Triggers I have used a little bit, but

my point here is it goes so far down

27

: 00:01:13

where it's like in this second to last

layer down here, like with the narwhal,

28

: 00:01:18

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

29

: 00:01:20

So my point here is you can make it

like me, senior data analyst, who's

30

: 00:01:24

worked in the field for 10 years,

who teaches people data analytics.

31

: 00:01:27

And you could not even

scratch a service of sql.

32

: 00:01:29

And that's perfectly okay because I know

the first two to three decently, well, the

33

: 00:01:33

first two at least, and it solves like I

would say, 90% of data analysts problems.

34

: 00:01:38

And we'll actually talk

about that here in a second.

35

: 00:01:40

What is a SQL problem or a data

problem that someone, a data

36

: 00:01:44

analyst actually solves with sql?

37

: 00:01:45

Because not all of SQL commands

are made for data analysts.

38

: 00:01:50

So in my opinion, if you're just getting

started, you can get by with like 17 SQL

39

: 00:01:54

commands and they are the following ready.

40

: 00:01:56

Number one, select number

two from number three.

41

: 00:02:00

Where?

42

: 00:02:01

Number four.

43

: 00:02:02

Group by number five.

44

: 00:02:04

Order by number six.

45

: 00:02:05

Like number seven, count.

46

: 00:02:08

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

average number 10, some number 11, case

47

: 00:02:15

when number 12, join number 13 distinct.

48

: 00:02:19

Number 14, having number 15

with number 16 partition by,

49

: 00:02:25

and number seven, uh, 17 concat.

50

: 00:02:28

Now there's some other ones you possibly

could use as well, like Union is another

51

: 00:02:32

one that probably is used pretty often.

52

: 00:02:34

Um, maybe you could ar argue like

some sort of rank would be useful,

53

: 00:02:38

um, or some sort of like day

function or something like that.

54

: 00:02:40

But my point here is there's really

not that much to get started with.

55

: 00:02:45

Like if you can get those 17 things down,

you can land a day job a hundred percent.

56

: 00:02:48

And I honestly think you can

learn those 17 things in like

57

: 00:02:52

three weeks if I'm being honest.

58

: 00:02:54

And that's how fast I teach them.

59

: 00:02:55

Inside of my bootcamp.

60

: 00:02:56

You know, I run data Alex

Accelerator, it's a bootcamp.

61

: 00:02:59

We teach SQL and we do it in two weeks.

62

: 00:03:01

The sequel portion, and I think that's

good enough to land your first data job.

63

: 00:03:04

If I'm being honest.

64

: 00:03:05

Now, that's about 30 hours of work

probably, but I literally think

65

: 00:03:09

if you spend 30 hours on this,

you can learn it pretty easily.

66

: 00:03:11

By the way, if you found this list

helpful, I send out a weekly newsletter

67

: 00:03:14

with tips just like this, and you

can join 30,000 other aspiring data

68

: 00:03:18

analysts to get these weekly tips in

your email@datacareerjumpstart.com

69

: 00:03:23

slash newsletter, or there is a

link in the show notes down below.

70

: 00:03:26

But sign up because I send awesome

stuff like this every single week.

71

: 00:03:29

That actually brings me to my second

point, which is that you don't have

72

: 00:03:32

to have all your SQL syntax memorized.

73

: 00:03:35

It's basically impossible.

74

: 00:03:36

Like I showed you, there are so many

different commands that you could be

75

: 00:03:39

learning so many different commands that

you could be using, and you might be

76

: 00:03:44

using Excel, you might be using Tableau,

you might be using Power bi, might

77

: 00:03:46

using Python, all on top of SQL as well.

78

: 00:03:49

And those have different syntaxes

and so it's really hard to remember

79

: 00:03:52

all the different syntaxes, so you

don't have to have it memorized.

80

: 00:03:54

It's not a problem if you forget.

81

: 00:03:56

I forget all the freaking time it happens.

82

: 00:03:58

N nearly like.

83

: 00:04:00

Every day, to be honest, probably

more than I should tell you guys

84

: 00:04:03

on YouTube, but I'm forgetful.

85

: 00:04:05

I've never been a good memorizer.

86

: 00:04:06

And the cool thing is you don't have,

you definitely don't have to have

87

: 00:04:09

it memorized for the job, right?

88

: 00:04:10

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

like someone over your shoulder like

89

: 00:04:12

making sure you know how to do this.

90

: 00:04:14

Now, you should obviously know the basics.

91

: 00:04:15

That's, that's a given, like

select from group by those

92

: 00:04:19

where those types of things.

93

: 00:04:20

You should definitely know the backbone of

sequel, probably by, by heart or by hand.

94

: 00:04:25

Um, but like the more complex

stuff, the more syntax stuff, you

95

: 00:04:28

definitely don't have to know.

96

: 00:04:29

Um, where this might not be true is in

an interview, in an interview for some

97

: 00:04:33

reason in the data world, we just love

to, Hey, do you have this memorized?

98

: 00:04:38

No, you suck.

99

: 00:04:39

You're never gonna get hired.

100

: 00:04:40

You reject you.

101

: 00:04:41

Like that's just how it is.

102

: 00:04:42

I don't know why it is.

103

: 00:04:43

I hate interviews like that, but

there are some sequel interviews

104

: 00:04:46

that do kind of treat you that way.

105

: 00:04:48

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

know that you don't know enough to do the

106

: 00:04:50

job, but I don't agree with that interview

process, but that's just how it is.

107

: 00:04:53

So just telling you that to be prepared,

uh, especially in today with like a

108

: 00:04:57

lot of these editors that will actually

like, kind of fill in the syntax

109

: 00:05:01

for you or suggest syntax for you.

110

: 00:05:03

With chat, GBT, with Claude, with

Google, like you really can figure out

111

: 00:05:08

what you need to do or, or how to do

what you wanna do in a moment's notice.

112

: 00:05:11

And so memorization, the need

for it is just going down.

113

: 00:05:14

I don't think you need to be memorizing

something and you shouldn't feel bad

114

: 00:05:16

if you don't have things memorized.

115

: 00:05:18

Number three, there's actually a

ton of beginner sequel commands that

116

: 00:05:22

you may learn in an online tutorial

that are absolutely useless and

117

: 00:05:25

you should really never use them.

118

: 00:05:27

Or rather you won't use

them in your career.

119

: 00:05:29

And the reason is.

120

: 00:05:30

Is data analysts.

121

: 00:05:31

We do a lot with databases, right?

122

: 00:05:33

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

90% of the time, we don't actually

123

: 00:05:37

create, alter or delete databases.

124

: 00:05:40

We aren't really managing databases.

125

: 00:05:42

We're querying databases,

which, querying is a funny word.

126

: 00:05:44

It basically means you're

asking questions to the data.

127

: 00:05:47

That's your job as data analysts is

to query the data in the database.

128

: 00:05:50

And so really data

engineers, data architects.

129

: 00:05:53

Uh, maybe an analytics engineer.

130

: 00:05:54

Their job is to more create the database

structure and everything like that.

131

: 00:05:58

Your job as data analyst is just

to answer business questions with

132

: 00:06:01

the data that they provide you.

133

: 00:06:03

And so there's certain things and certain

tutorials that will tell you that you

134

: 00:06:05

need to know some commands, like insert

or delete or update grant or provoke,

135

: 00:06:10

and you don't need to know those.

136

: 00:06:11

You don't need to know those at all.

137

: 00:06:13

That's like more data engineering and

they often call those DCL and DML,

138

: 00:06:17

which stands for data control language

and data manipulation language.

139

: 00:06:21

And basically, in my opinion, you

don't need those at all within sql.

140

: 00:06:25

If you're gonna be a data analyst,

at least not at the beginning.

141

: 00:06:27

Like don't waste your time.

142

: 00:06:28

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

like Google SQL tutorial, one of the first

143

: 00:06:31

things they're gonna teach you is like,

okay, this is how you create a a table.

144

: 00:06:34

This is how you delete a table.

145

: 00:06:35

This is how you update a row.

146

: 00:06:37

Do insert into to populate your database.

147

: 00:06:39

And those are good things to know.

148

: 00:06:40

I'm not saying like that's

a bad thing to know.

149

: 00:06:42

I'm just saying if you're in a

crunch for time, which we all are

150

: 00:06:45

today, and if you're a career pivot.

151

: 00:06:46

You don't have unlimited time, so you

have to figure out what to spend your

152

: 00:06:49

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

I wouldn't have spent time on this.

153

: 00:06:52

The fourth thing I wish I knew when I

was starting SQL is that you actually

154

: 00:06:55

don't even really have to know SQL.

155

: 00:06:57

Now.

156

: 00:06:57

SQL is really in demand, like it is the

most in demand data tool out there across

157

: 00:07:02

all the different data disciplines.

158

: 00:07:03

That being said is like everything

that you can do in sql, you

159

: 00:07:07

can kind of get away with.

160

: 00:07:09

In some other data software.

161

: 00:07:10

So for example, a group I in SQL is

really just a pivot table in Excel and

162

: 00:07:15

you can do the exact same manipulation.

163

: 00:07:17

Inside of Pandas as well with

a group by function there.

164

: 00:07:21

You can join Excel tables.

165

: 00:07:22

You can join Google Sheets, Tableau and

Power BI both have a bunch of no code

166

: 00:07:27

data manipulation tools built into their

softwares so that you can actually do

167

: 00:07:31

like a bunch of data manipulation that you

could do in SQL inside of their softwares

168

: 00:07:34

without having to write SQL code.

169

: 00:07:36

I really think you should learn sql.

170

: 00:07:37

I think it's worth your time.

171

: 00:07:39

But that being said, just know that

you can do everything that you can

172

: 00:07:43

do in SQL in a different software.

173

: 00:07:45

So if you're an Excel master, you can

probably figure out how to do whatever

174

: 00:07:49

you need to do to the data that you

would do in SQL inside of Excel.

175

: 00:07:53

You don't have to learn every single data

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

176

: 00:07:56

a hundred years old before you actually

ever feel ready to apply to any job.

177

: 00:07:59

My point here is just don't feel that

bad if you don't know sql, but you

178

: 00:08:02

should probably learn it anyways.

179

: 00:08:03

Tip number five is that you need to

have an IDE and an IDE stands for

180

: 00:08:07

Integrated Development Environment.

181

: 00:08:09

And what does that stand for?

182

: 00:08:10

Well, when I was first like

breaking into data, I knew

183

: 00:08:13

software, I knew Excel, for example.

184

: 00:08:15

Uh, and when you download Excel,

you hit download Excel, and then

185

: 00:08:18

you can, you know, click on Excel

and it opens up Excel and then you

186

: 00:08:21

can analyze data inside of Excel.

187

: 00:08:23

Well, SQL is a little bit

more complicated than that.

188

: 00:08:24

First off, there's not just like

one software that's called SQL

189

: 00:08:27

and you hit download on sql.

190

: 00:08:28

There's a bunch of different flavors

and different like sub languages of sql.

191

: 00:08:32

Um, the more popular ones are MySQL,

SQL Lights, Microsoft SQL Server.

192

: 00:08:37

Um, Snowflake's becoming more popular.

193

: 00:08:39

Uh, but my point in telling you this,

if you were to download, for instance,

194

: 00:08:42

MySQL, you wouldn't be able to just

like double click it and it would open

195

: 00:08:45

up and you can analyze data in sql.

196

: 00:08:47

You need what's called an IDE or

often SQL's called a workbench.

197

: 00:08:51

And basically this is like a secondary

or like a companion software that

198

: 00:08:54

comes with the actual download

of SQL that lets you use it in a

199

: 00:08:59

non terminal, non-car coder way.

200

: 00:09:02

So just know when you're

going to download sql.

201

: 00:09:05

You probably need to download some

sort of an IDE or some sort of a

202

: 00:09:08

workbench for you to be able to use

it, and that's a little bit confusing

203

: 00:09:11

and a little bit difficult to set up.

204

: 00:09:12

This is one of the reasons why

when I teach SQL inside of the data

205

: 00:09:15

analytics accelerator, we actually

do the first week without downloading

206

: 00:09:18

an IDE or even downloading anything.

207

: 00:09:20

We actually just use a SQL

version inside of the cloud.

208

: 00:09:23

That allows you to just get the hang

of SQL, of the actual language before

209

: 00:09:27

you have to deal with like the annoying

logistics of downloading and installing.

210

: 00:09:31

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

211

: 00:09:33

I've done it like literally a

hundred times and I hate downloading

212

: 00:09:36

SQL every single time I do.

213

: 00:09:38

It's a pain in the butt.

214

: 00:09:39

Just trust me.

215

: 00:09:39

It's not fun.

216

: 00:09:40

But hey, if I went back and I

could tell myself one thing,

217

: 00:09:43

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

218

: 00:09:45

If you're just gonna try to do it

without an id, it's not gonna work.

219

: 00:09:47

That brings me to my sixth tip,

and that is that you need to

220

: 00:09:49

use the limit function in sql.

221

: 00:09:53

If you run a SQL query, SQL will

give you back all the matching

222

: 00:09:58

rows that match your query.

223

: 00:09:59

And a lot of times if you're using

a big database, that could be,

224

: 00:10:02

you know, it could be five rows,

but it could also be 50 rows.

225

: 00:10:04

It could be 500 rows.

226

: 00:10:05

It could be 5,000 rows.

227

: 00:10:06

It could be 500,000 rows.

228

: 00:10:07

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

230

: 00:10:12

to return that, uh, especially

if you're maybe not the best at

231

: 00:10:15

optimizing queries and stuff like that.

232

: 00:10:17

So my advice to you is to make sure

you're using the limit at the end,

233

: 00:10:20

and that will actually, like if you do

limit to 10, that will only give you the

234

: 00:10:23

first 10 out of the 5 million, so that

way you can test your queries first.

235

: 00:10:27

You know, on a smaller

result base, so it's fast.

236

: 00:10:29

And then once you're sure that the

queries kind of work in the way that

237

: 00:10:32

you want, you can take that limit

to: 1000

238

: 00:10:36

And then you can make sure

that everything's still working

239

: 00:10:37

the way that you want, but you

don't have to wait very long.

240

: 00:10:40

The seventh thing I wish I knew is that

getting good at SQL doesn't equate to

241

: 00:10:44

actually getting hired because a lot

of you guys probably watching this

242

: 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

248

: 00:10:59

proficient enough at Seql.

249

: 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

251

: 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

254

: 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.

257

: 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,

264

: 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.

267

: 00:11:49

Yes, I'll give you that.

268

: 00:11:50

But it's also important not just to

get stuck in the grind of doing these

269

: 00:11:53

sequel problems over and over and

over again, thinking that's somehow

270

: 00:11:56

gonna magically get you a job.

271

: 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

273

: 00:12:01

following the full SPN method.

274

: 00:12:02

So that's of interest to you.

275

: 00:12:03

If you've never heard of the SPN

method before, I will have a link down

276

: 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

278

: 00:12:11

become a data analyst from wherever

you're at, to landing your first data

279

: 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.