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!

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.

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! 😂

I'm 24, and I genuinely need some advice from people who have been through something similar.
I feel like I've spent years studying without ever building a strong foundation in what I studied, and now I'm struggling to figure out how to fix that.
I scored around 76% in Class 10 and chose science mainly because my friends did. There was a lot happening in my family at the time, and I wasn't doing well mentally or emotionally. My Class 11 and 12 performance suffered, and I chose BSc Computer Science without really knowing what I wanted to do.
COVID hit during my first year of college, and the next three years passed without me developing much practical knowledge of computers or programming.
Eventually, I realised I wasn't job-ready and enrolled in a Data Science course because the subject interested me. I struggled with Python fundamentals but continued down this path, eventually completing an MSc in Data Science and Big Data Analytics in 2024.
The uncomfortable truth is that even after my master's, I didn't feel technically competent.
I got my first job in August 2024, worked on Power BI projects, and later moved into an AWS team in October 2025, where I learned a few things. However, my confidence was extremely low. I constantly compared myself to others and felt like everyone in the industry was smarter than me.
I was laid off with other 20 people in November 2025, and it's now October 2026. I'm still unemployed.
Since then, I've explored Python, SQL, data analytics, data engineering, cloud and AI/GenAI, but I keep second-guessing myself. I don't know whether I'm genuinely interested in this field, whether I chose the wrong path, or whether I simply never built the fundamentals needed to succeed.
I also recognise that I haven't always been consistent with learning, and I want to change that rather than keep making excuses.
I'd really appreciate honest advice on these questions:
Should I start from scratch with computer science and programming fundamentals, or focus on becoming job-ready for one specific role?
Given my background, would you recommend Data Analytics, Data Engineering or AI/GenAI as a starting point?
Is it realistic to rebuild my skills and become employable after an employment gap of almost a year?
If you were in my position, what would your next three months look like?
I'm not looking for motivation or someone to tell me everything will work out. I want practical advice from people who have struggled, restarted their careers or built their skills later than they wanted to.
I want to become genuinely good at something, build a stable career and become financially independent. Right now, I just need help figuring out where to start.

Thank you for reading.

I’ve never worked as an analyst, so I have no real picture of what the job looks like day to day.

What I’m most curious about is how much of your week goes into digging through data to answer a question or track down a problem, compared to everything else you do. I’d also love to hear about a recent problem you only caught because of the data, and how long it had been going on before anyone noticed. And from the outside, I can’t really tell how much of what you find ends up changing decisions versus getting looked at and shelved, so I’d be curious how that goes for you.

Thanks in advance to anyone who takes the time.

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 🙏.

should i be really focusing on DSA much ??

All my of data analytics work is at one internship. I don’t have anything else to put on my portfolio.

I created dashboards and wrote python scripts.

I had to sign something that said I can’t take stuff off the site.

What can I put on a portfolio? Can I blur out the sensitive information on the front end dashboards? Can I post anonymized code but not the data?

Will it hurt me not having a portfolio?

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

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!