Data Scientist vs Data Analyst (funny!)

Introduction

Good morning, Luke!

Oh, what’s up, dead nerd?

Luke, you know I don’t like it when you call me that; I prefer data professional.

Sorry, data nerd professional!

So, what are you up to today?

Well, if you must know, I’m actually working on some really important things for boss man. I’ve been exploring a new SQL data source and finishing up a Python pipeline for an ETL process. This data will be sent into a Tableau dashboard that I’ve been mocking up.

Oh, that’s so cool! You deal with so many different tools for your job; it’s pretty impressive!

So, are you almost done with your pipeline?

Dude, you sound like our boss. No, I’m not even close to being done. It’s complex. I’m using Python; you wouldn’t even understand. You’re an R user.

Well actually, I dabble with Python quite frequently. I use it for machine learning, and I used it in my thesis. You mind if I take a look at it?

I mean, it’s a pretty complex process. I don’t think you are going to understand it. But sure, why not? Let’s give it a shot.

Why are you using tabs for your indentations and not spaces? Per PEP 8, you're supposed to use spaces!

Dude, everybody knows spaces versus tabs don’t matter! Are you going to help me with this issue or what?

Yeah, just give me a second… It looks like it’s working now.

What? What do you mean it’s working? I’ve been troubleshooting this for days!

It looked like you had some recursion issues!

What the heck is a recursion issue?

Well, to understand recursion, we first have to understand what a recursive function is. A recursive function is one that is self-defined by itself.

Okay, got it. So, does it matter? Can I get my computer back?

Yeah, okay, here you go!

Thanks! Where did you learn how to code like that? It was pretty impressive!

Well, unlike you, I had to actually teach myself how to code. I went to a few coding boot camps and did a few self-projects and hosted some stuff online to get feedback from others, but mostly it’s been all self-taught.

That’s too cool! That reminds me of my time studying back at Cornell for computer science and learning about all the different computers and languages. It was such an experiential process!

Wow, cool story, bro! Must be nice to make twice as much doing half as much work!

Yeah, yeah, it’s pretty great. I love my job!

So what would you say you do here?

Well, actually, I think I do quite a bit. I use code to build different machine learning models to model customer engagement and retention. From there, I design experiments for online platforms, and I also coordinate with our data engineers to launch these different machine learning models to the cloud.

So that’s a glorified way of saying you go to Google, copy and paste the best-looking code, and use that, huh?

No… Okay, maybe sometimes!

Nice, pound it!

Um, never mind…

Keywords

Data Science
Data Analysis
Python
SQL
ETL
Tableau
Machine Learning
Coding Boot Camps
Experiential Learning
Customer Engagement

FAQ

Q: What’s the main difference between a data scientist and a data analyst?
A: A data scientist often focuses on creating machine learning models, while a data analyst typically analyzes data and generates reports.

Q: Are Python and R interchangeable for data analysis?
A: They have different strengths. Python is often preferred for machine learning, while R is favored for statistical analysis.

Q: What’s an ETL process?
A: ETL stands for Extract, Transform, Load. It’s a process used to gather data from multiple sources, transform it for analysis, and load it into a destination, usually a database.

Q: What coding skills do you need to be a data professional?
A: Proficiency in programming languages like Python or R, knowledge of SQL for database querying, and familiarity with data visualization tools like Tableau are essential.

Q: Is self-learning coding effective?
A: Yes! Many data professionals are self-taught and find success through online courses, coding boot camps, and personal projects.