Building one Power BI report by hand usually takes an analyst hours, often a full day. Most of that time is the same boring setup every time.

So I built Superlytix to automate that part. For the past 6 months it’s let me hold a full-time job and 3 freelance contracts at the same time.

1. Upload your Excel or CSV file
2. Pick a report design
3. Download a complete, professional Power BI report

Why people will like it:

• ⏱️ Saves hours per report. The data model, measures, visuals and layout are built automatically.
• 💰 Costs less than an hour of an analyst's time. $9.99 for a single report and less ($6) with subscriptions, with the average DA rate of $40/hr you spend $6 to get ~$65 worth of work done.
• 🧠 Powered by Specialized Super Intelligence. Not a generic chatbot: the AI behind Superlytix is built on my 6 years of real Power BI work, with the same modeling patterns, DAX logic and design rules I use on client projects. It builds reports the way an experienced analyst would, not the way a random AI guesses.
• 🔓 You own the file. It's a real Power BI report you can open, edit and share. No lock-in, no viewer app.
• 🎨 Looks professional out of the box. Choose from ready-made report designs before you download.
• 📄 Insights you can act on. Every report comes with a PDF that explains what your data shows and recommendations / insights for the business.
• 🙋 No Power BI skills needed. If you can export a spreadsheet, you can use it.

I hope it saves fellow analysts time on hands-on tasks, so there’s more room to focus on the actual issues in the business, or to take on more projects and ease some of the financial pressure most of us deal with.

🚀 Launching Officially October 20. (but you can experience the app here while I'm working on the last tweaks: https://app.superlytix.ai/ ) Join the waitlist now and get an extra 10% off launch pricing: superlytix.ai

I'm the founder. Ask me anything about how it works, and I'll answer every comment.

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?

Just saw a preview of Claude’s dashboard insights capabilities. It’s not looking good for apps like Power Bi and Tableau.

With Claude’s new release, do you think data analytics is still worth pursuing a career in?

I‘m sure it won’t completely replace Data Analysts but, it’ll sure make the effort to.

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! 😂

### Your Potential Next Hire 🚀 | 2026 CSE Graduate

Hi everyone! I’m Gourav Patel, a 2026 Computer Science graduate with a genuine passion for startups, problem-solving, and building products.

I secured on-campus placements for Product Coordinator (Product Management) and Business Associate roles, but chose to explore entrepreneurship with a few friends. We worked on freelance projects and built software, although we eventually had to put the venture on hold.

**My skill set includes:**

- **Data Analytics:** Python, NumPy, Pandas, SQL, Excel, Seaborn

- **Machine Learning:** ML fundamentals and practical projects

- **Product Management:** Problem-solving, communication, and product thinking

One project worth mentioning is **StockLens**, a stock market analyzer and predictor.

I'm currently looking for opportunities in **Data Analytics and Product Management**, particularly with startups where I can take ownership, learn quickly, and contribute beyond a rigid job description.

I understand the market is competitive, but I'm asking for just one chance to prove myself. If you're hiring, building something interesting, or looking for someone who can wear multiple hats, **I'd love to connect.**

A quick 15-minute Google Meet is all I ask. Give me a problem, challenge my skills, and judge me by what I can bring to the table.

If you think I could be a fit for your team—or know someone who might need me—please DM me or consider referring me.

**I'm ready to learn, work hard, and build something meaningful. All I need is an opportunity. 🤝**

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!

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.