140: What’s the Future of Data Analysts with AI?

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Will AI replace me as a data analyst.

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That is a question I've been

getting a lot of recently.

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And in today's episode,

I wanted to dig into.

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If I actually think that's

going to be the case.

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Once again, guys, welcome back to the data

career podcast, the number one podcast

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for your landing, your first data job.

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I'm your host, Avery Smith.

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And I run a company called data

career jumpstart where I help

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people land their first data job.

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So let's talk about this whole AI,

maybe taking the place of data analysts.

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Is it going to happen?

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Has it already happened?

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Let's get into some thoughts.

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All right.

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So AI is not coming.

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It is here.

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You guys with revolutionary new products

like ChatgPT GPT4 MidJourney It's

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very clear that AI is all over the

place, but what does that mean to you

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as someone who is in the data world

or trying to land their first data

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job, are you going to be replaced?

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For a career you're trying so hard to work

into and you can't even break into yet.

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Is it going to be obsolete?

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I actually got a message on LinkedIn this

week that asked something very similar.

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They said that they've been hearing more

and more about AI and ChatGPT 4 I came

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across this newsletter the other day that

said that data analyst might be replaced.

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And I begin to wonder about future job

security for junior data analysts like me.

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Simply because this is moving so quickly.

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I just wonder what your

thoughts were on this.

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So I thought I'd make this podcast

episode to kind of talk through

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what I think about ChatGPT Uh, LLMs.

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AI, everything in general.

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Is it coming for you?

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My answer is no.

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My answer is no.

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And the reason is, is AI is just a tool.

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You know, we really think

of AI is really scary.

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Like these robots that could

potentially take over the world.

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And, you know, maybe it will

be that eventually, but right

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now all AI is, is a hammer.

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It still needs the human

to actually do something.

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Now there are really cool

things like auto GBT.

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If you've never heard of that before.

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Pause the podcast, you can look it up.

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I'm not the most well versed on it.

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So I'm not going to try to explain it in

depth in this episode, but basically it's

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like where you have multiple AI agents.

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So imagine chat GPT talking

to another chat CPT, which is

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talking to another chat GPT.

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And it can basically, instead

of having a human talk to

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GBT it's chatty PT, talking to Chatsworth.

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GPT, and it becomes a

little bit more autonomous.

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I think there's another one

called auto GPT, um, as well.

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And these are basically talking

back and forth to one another,

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a little bit more autonomously.

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So it is like maybe becoming more of.

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A self propelling tool.

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But for the most part, AI is just a tool.

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It's just like a hammer.

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It's like a saw you still

need a human to operate it.

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So will our tasks change as data

analysts and data practitioners?

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Yes, probably as they always have.

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I mean, imagine the data analysts before

computers were invented now, I don't know

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if that was, if they were really a thing

back then, probably not, but imagine

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what they would be doing would be a lot

different than what we'd be doing today.

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You know, for example, they'd be

doing a lot of hand calculations.

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Maybe they'd be using that.

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Like, what's that weird

invention, like the Abacus, right.

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To keep track of all

these different things.

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And now we have Excel.

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Now we have SQL Those are

tools that did not exist.

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Did you know, these people who

these mathematicians did, they

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lose their job when Excel came out?

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No.

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Did their job nature change?

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Yes, probably.

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They probably started to

having to use the tool.

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So in my opinion, this is

just a hammer and everyone

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should start using the hammer.

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There's no reason whether you're trying to

land your first data job or whether you're

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an experienced data professional that

you should not be using some form of AI.

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You need to be otherwise, they're

going to get left with the times.

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This is a new tool.

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It's going to be revolutionary

and you should feel enabled.

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In fact, you should feel emboldened

by this because all of a sudden, the

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barrier to break into data analytics

has even dropped a little bit further.

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Because a lot of the

technical requirements can be

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fulfilled with CQL or sorry.

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Can be fulfilled with chat, GPT and AI.

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And what I mean by that is.

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It's basically all, all chatty

bitchy and AI really is, is a

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more effective Google, right?

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Like in the past, if you didn't

know how to do something in

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CQL, you could Google it.

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And within a few clicks, you

could probably find your answer.

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Really I'll chat.

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GPT is, is a more effective Google.

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And I'm not even going

to say more effective.

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I'm going to say faster, but it's not

necessarily guaranteed to be right.

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A hundred percent of the time.

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So you do have to be a little bit

concerned and worried about that.

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But really we've been

doing this for years.

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We've been posting stuff and questions

on stack overflow and getting help.

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We've been Googling stuff,

finding different EHRs and finding

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the answer inside of Google.

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So really what I see chat GBT

is coming into play is it's just

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going to make us more effective.

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It's a tool that's going

to make us more effective.

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And for you, as someone who wants

to break into the data world, you

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should feel really excited because

now it's going to be a little bit

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easier to break into the field.

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You don't have to be memorizing all SQL.

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You don't have to, you know, memorize

all this different statistics

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stuff you could ask Chachi.

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GPT and pretty reliably get an answer.

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Right, but that is a little bit scary.

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Cause every thinking, well,

that makes me obsolete.

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But once again, a tool has

to be wielded by a human.

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And humans are really good at

knowing when we should do tasks.

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W how we should do this task

and what those tasks should be.

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Now we can use AI.

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To kind of expedite that whole

journey, the whole process.

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But it still requires a good human

brain to link the business to the AI.

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It will not be the case in the future.

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I think so.

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We'll, we'll chat GBT and AI get

better and need humans less probably.

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But until that happens, let's not fret.

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What's going to happen at

midnight when it's only 9:00 AM.

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Right.

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And we can get good at using AI.

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We can get good at using chatty PT today.

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And then we're going to have job security.

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All right, we're going

to have job security.

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So AI will not take your job,

but a human that uses AI might.

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And so to be future-proof all

you need to be is a human that

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knows how to use AI really well.

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And what does that mean for you?

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Like what can you do

today to get good at that?

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I think you just go onto chat

GBT and start playing around.

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Start trying to ask different questions,

you know, try to ask different SQL

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questions or different Python questions,

or maybe even some Excel questions.

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And just start messing around.

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All right.

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You can kind of get a feel for

what it can do and what it can't

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do, what some limitations are,

but don't be worried about it.

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If you have never opened it up

before, if you've never tried

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doing data analytics on it.

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I don't don't fret.

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There's some tasks that Chatsy

beauty is fantastic for.

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And there's other tasks that Chatswood

beauty is actually not very good at, for

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example, if you S chat GPT to add, like,

let's just say 3 million, 246,392 plus 7

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million, 564,123 or something like that.

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Jeff.

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It's a simple math problem, right?

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Computers are really good at that.

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Judgey beauty will most

likely get that problem wrong.

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And the reason is.

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It doesn't know how to do math.

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It just knows how to read

what math has been done.

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And so it's usually when, if you, if you

were to put that in chat to PT right now,

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they'll probably get the first numbers.

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Right.

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And the last numbers.

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Right.

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But like the hundred thousands

will probably be all jumbled up

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because chatty BT has used written

math to understand when these

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numbers are added to these numbers.

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You know, then we should probably start

with these numbers and we should probably

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end with these numbers, but it's actually

not that good at doing the middle section.

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So for instance, it's obviously

not going to take the job in any

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sort of large number arithmetic.

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Now, computers are better

at humans than adding.

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If we can tell the computer what we need,

but that brings me to my next point.

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Is that the bridge between the tech and

the domain or the tech in the business?

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Is still going to be

largely covered by humans.

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Humans are what.

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Humans are more capable to see what's

going on in the real world and relate

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it to math related to statistics

related to data and make those

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connections and also make those choices.

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Right, because at the end of the

day, humans, most of society is

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still a human decision made society.

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We're making business decisions.

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You know, even when I was at

Exxon mobile, when we had AI

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tools, they weren't really AI.

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They were very data, sciency

machine learning tools.

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It would suggest stuff, but

it's still down to the human to

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make those decisions overall.

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Because once again, it's a tool it's

not going to replace us and less.

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We don't use it at all.

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So I encourage all of you guys to go

play with GPT, go test for yourself.

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Go try it out.

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Don't be afraid of it.

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It's going to be okay.

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Your job's not going anywhere

and life's going to continue on.

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That being said, if you want help

in your data journey landing,

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that first data job hit me up.

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I run a program called

data analytics accelerator.

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It's a 10 week bootcamp that will

help you land your first data job.

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Uh, by helping you build nine

portfolio projects, learning the

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most important skills and teaching

you how to network effectively with

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recruiters, hiring managers and peers.

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So that you can land that data job fast.

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If you're interested in that you can

click on the link down below once again.

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Thank you guys for listening to the show.

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See you soon.