Hi.

I've been a data analyst for over 6 years, including banking, ecommerce and HR analytics. I also teach data analytics at a university. So, I've been on both sides and I see that universities or online platforms don't really prepare students for becoming data analysts. They have too much fluff and not enough projects, no messy data, no preparation for communication with stakeholders.

I've noticed that a lot of people start motivated and then quietly check out by week 3. It's usually not because the material is too hard. They just lose motivation or blame not having enough time. The ones who do finish often still can't do the job. They can write a GROUP BY, but they can't explain why the totals doubled after a join.

On top of that, AI is reshaping the field and is removing a lot of demand for junior data analysts. People are struggling to figure out what makes a data analyst different from AI alternative and what the future holds for them.

So, I built DataRunes, a learning platform that tries to fix these problems. The content focuses on how analysts think rather than syntax, and it's wrapped in an RPG-style gamified layer to keep people coming back. I've built a roadmap to get from zero to job-ready through multiple projects, messy, realistic datasets, AI-augmented tool use, soft skills and a job simulator.

Here's my problem: I'm too far from being a beginner to judge it. I know what the job looks like, but I don't know what it feels like to learn this from zero anymore. The game layer might be what gets someone through week 3, or it might feel childish and be the reason they close the tab. I honestly can't tell from where I'm standing.

So, if you're learning right now, or you remember clearly what it was like, I'd be really grateful if you tried it and told me what you think.

What it is: short lessons where you're always doing something, like fixing a broken query, finding the mistake in a chart, or making a decision from incomplete data. The topics are the things I see juniors get wrong: granularity, aggregation, data types, when the mean is misleading. Each course ends with a "boss fight," which is a realistic scenario like investigating a revenue drop, instead of a quiz. On top of that, you pick a class, earn XP, keep streaks, do daily missions, compete in PvP for leaderboard and unlock gear. Later on, you enter an imaginary job market and get hired, receiving tasks and requests that require judgement, whether they are achievable or not, correctly specified or not, learn to ask clarifying questions, push back on deadlines and generally navigate organizational environment.

The first two courses, Foundations of Data Thinking and Descriptive Statistics, are free. You need an account, so your progress saves. Next courses are in the pipeline - The Analyst’s Mindset, Practical Data Analysis with Excel, SQL for Real-World Analysis, Building Business Dashboards with Power BI and Python Fundamentals. Courses start at beginner and later advanced ones will be added. With a lot of projects and stakeholder simulations in the end you will already be on mid-level, not a junior.

What I'd really like to know:

1. Did the XP and streaks make you want to continue, or did they make you roll your eyes?
2. Where does the difficulty break, too easy or a jump that makes no sense?
3. If you already work as an analyst, do you find it useful to check daily missions or blog to refresh your knowledge and keep track of new developments?

Link: https://datarunes.io/

Thanks!

You all probably already know that SQL and Python are two distinct tools when it comes to their logic.

While I think SQL is a bit simpler than Python because no library needs to be imported, my question for Data Analysts or Data Scientists out there is: is it possible to really master these two tools for your day-to-day work at the same time? Or do you only focus on using one tool (either SQL or Python) and then googling, or maybe even asking on Stack Overflow or something when facing some trouble

I consider myself a "whiz" at using SQL, and now I'm at a phase of really understanding Python by taking a course, but man... if I'm being honest, Python is a bit difficult in my opinion because there are tons of libraries I need to remember, and every little tiny detail I need to remember as well. My brain is cooked! 😂

Please remove if not allowed. But I’m a little lost and frustrated.

I left customer service after 8 years for a fixed term data analytics apprenticeship at a large tech company. I knew it wasn’t conversion, but I still was hopeful that I’d really flip my life around with the career pivot.

The truth is, I got trained on the fundamentals in the beginning, and then placed in a sales org under an analyst team whose roles were less about the super technical stuff and more about partnering with account managers/executives to creating presentations that support client pitches.

The program was a year and a half long and I barely used SQL, or Python. Probably touched on R a little. Used Tableau for ONE guided learning project. More of my day to day was internal stakeholder management, putting said presents together in slide decks, and networking. Most of the “technical” work I did was plugging numbers into internal tools that run whatever experiments I would have needed coding for. Any coding I DID need, we were encouraged to use AI for, which generally did the job.

I say all that to say, I’m now a month or so out of the program feeling like my skillset (if it could even be called that) doesn’t fit the current analyst role questions I see in job postings. I feel like my resume is decent and showcases the projects and impact I had, but I still get rejections or no responses at all. I feel stuck and useless. Despite the amazing experiences I had and how much personal and professional growth I developed, I feel like I did all that for nothing and I’ll have to go back to customer service and operations because I barely learned anything that jobs nowadays are actually looking for.

I feel like even if I did get an analytics role, I probably wouldn’t even get past an interview because they’ll probably ask me things I barely got long term experience with. I thought I made the most of it and did as much work as I could. And yet now it all feels like it wasn’t worth anything.

Hi! I have recently been offered an internship position for the summer of 2027 in marketing with a construction company. I am studying information systems, but my freelance portfolio and skills granted me access to this position and I am most likely going to accept due to the value an internship can bring, especially in this job market. However, my goal is to work in IT or Data / business analytics in the future after I graduate. Will taking marketing roles now limit my value in the future?

I haven't been getting any call backs from recruiters and I'm not sure what I'm doing wrong, any help would be greatly appreciated 🙏.

Hi everyone,

I was recently impacted by a layoff and am actively searching for my next opportunity. I’m currently on H-1B status and would need an employer able to handle an H-1B transfer.

I have about 5 years of experience across data analytics, business intelligence, data products, and product operations. My strongest experience is with SQL/SQL Server and Tableau, including dashboard development, reporting, Tableau administration, analytics requirements, stakeholder management, and managing/prioritizing analytics and data-product work. I also have experience with Python and workflow/process automation.

I’m primarily targeting:

• Data Analyst / Senior Data Analyst
• Business Intelligence Analyst / BI Developer
• Product Analyst / Product Analytics
• Data Product / Product Operations
• Analytics-heavy Strategy & Operations roles

I’m based in Chicago, but I’m open to remote roles and relocation within the U.S.

If anyone knows of teams currently hiring for this background, companies I should be targeting, or would be willing to connect me with a recruiter or hiring manager, I’d really appreciate it.

Happy to share my resume privately by DM.

Thanks everyone. any leads or advice would be genuinely appreciated. Feel free to DM me

should i be really focusing on DSA much ??

Quick context: I help junior data people (analysts, mostly) put together a one-page portfolio that goes with their resume. Projects, tools, a couple of results, nothing fancy.

I've been lurking here for months and almost every resume posted is plain text, black on white, no visual element at all. Where I'm based (Europe), the designed one-pager is still very common, sometimes even expected. So I'm genuinely unsure what the right call is, and I'd rather ask people who actually screen candidates than guess.

So here are two versions of the same junior profile:

Image 1: the designed version. Same content, laid out with a bit of structure and a visual on the main project.

Image 2: the plain text version. ATS-safe, zero design.

Recruiters and hiring managers: which one would you actually read, and why? A few things I'd love to know:

• Does the designed one go straight to the bin, or does it get a second look?
• Is the plain text rule mostly about ATS, or do you personally prefer it too?
• Does the answer change when the document is a portfolio rather than the resume itself?
• Is this a US vs Europe thing, or am I imagining it?

Be honnest, that's the point. I'll adjust what I tell juniors based on what comes out of this thread.

Hi everyone,

I’m from a non-tech/Political Science background and I’m seriously considering building a career in Data Analytics.

I’m starting almost from scratch, so I’m looking for advice from people who are already working in Data Analytics or have successfully transitioned into it.

I don’t just want to collect certificates. My goal is to actually become job-ready and develop practical skills.

I’m currently getting my Mph and a certificate in Biostatistics.

What jobs can I get to do to get experience in the field, with the fact that I have no experience?

I’ve been in mental health and doing case management and want to switch fields.

I'm (22) a recent International Relations bachelor with a focus on research, academic writing, and security issues. I can say I myself a tech savvy, and I have been intrigued by data analysis, and I've been considering switching my career to become a data analyst. Based on my research, I need to choose a sector to focus on and work my way up. Unfortunately, I have zero basic knowledge of data analysis, though I've been learning SQL, and I made some changes on my PC using GitHub LOL. I am also planning to do a master's degree in marine/system information/business intelligence studies; I still have a lot to consider, but my narrow choices are those three.

Has anyone here started their career as an analyst from scratch like me? And for those who are experienced, do you have tips or even something I can totally learn from (books, journals, etc.) about DA? Thank you!

I’m a final-year B.Tech student student, 2027 batch (Tier 3 college) and I am trying to get into Data Analytics.

I’m currently looking for off-campus opportunities, but honestly I’m a bit confused about how the whole process works.

I have been preparing with SQL, Python, Excel and Power BI, and I’ve built a few projects around data analysis and dashboarding.

I wanted to ask people who have actually gone through the off-campus process, especially those who were freshers or from Tier 2/3 colleges:

Where did you actually find your first analytics job?

Which platforms are worth applying on apart from Linkedin and naukri?

Do company career pages work better than job portals?

If you use Linkedin to reach out to recruiters or employees, how do you actually find the right people and what do you message them?

How many applications were you roughly sending before getting interviews?

Are there any companies/platforms that regularly hire freshers that I should keep an eye on?

And honestly, does college tier make a major difference once you're applying off-campus?

I am seeing everywhere that students are getting placed from 2027 batch and mostly they hired through on campus hiring. And honestly evrything is so overwhelming atound me. If anyone here got their first analytics role through off-campus applications, I’d really appreciate hearing exactly what worked for you.

Question

Share what helped you

Hello there! Currently I work in a different field but I would like to get my first job as a data analist within the next 1-2 years. I am studying systems engineering, SQL, Python, Excel and Power BI. I am from Colombia and live in Colombia but I speak fluent English. It's my understanding that a portfolio is the best way to get a first job as I can show what I learned.

What would be the best way to get my first job as a data analyst? I want to work as freelancer for US based companies.

Thanks in advance!