r/dataanalytics

I want to know whether basic Knowledge in maths is required or not in python and data analytics as a whole. As im very weak at maths and didn't touch it from almost 7 years after my 10th.

Hi everyone,

I'd really appreciate advice from people who are working as Data Analysts or recently got hired. Any roadmap, study plan, or resources would be incredibly helpful.

I'm a BBA graduate(2023) trying to break into data analytics by SELF TAUGHT after a long gap.

Now it's 2026, AI is everywhere, and I'm honestly confused about what skills employers actually expect from entry-level Data Analysts.

My questions are:

1)Is it possible to become a Data Analyst through self-study when I have 3.5 yrs of a career gap?

2. What skills are essential for a Data Analyst in 2026?

3. Which tools should I prioritize more(Excel, SQL, Python, Power BI, Tableau, AI tools, etc.)?

4. How much Python is actually needed?

5. What AI skills are becoming important for Data Analysts?

6. What kind of portfolio projects should I build to get interviews?

7. Are certifications like the Google Data Analytics Certificate still worth it?

Heyyoo. I have a free trial for Parallel Desktop because I’m SO done with Windows laptops, but still need Windows for work and school since I’m in accounting/data analytics.

I want to make sure that the excel I have actually has all the features, because I know that there are some important things that don’t work on MacOS.

What should I test to make sure that I have the proper excel version?

By successfully, I mean that it's used almost daily with reasonable accuracy.

I am also not interested in toy projects, but in enterprise-grade analytics.

Hi.

I'm a cook by trade. For the last four or five years I've been thinking about moving into IT, and data analytics is where I landed — I genuinely like building things, making tables, putting documents in order, digging through data, setting up systems.

But I ran into the problem that has followed me my whole life: I cannot learn something that doesn't interest me and that I don't need right now. It just goes dull and my head starts refusing new information. What I can do is play games — strategy and simulators mostly. So I figured I'd learn SQL through a game.

The trouble was that none of the games I found show what the job actually looks like. So I built one, using Claude and a lot of YouTube videos of working analysts talking about their day.

Here's my problem: I'm not an analyst and I have never worked as one. I can't judge whether any of this resembles the real job, or whether it actually teaches anything useful. The whole thing might be plausible-looking nonsense and I'd have no way of knowing.

So if you do this for a living, I'd be really grateful if you took a look and told me what you think.

What it is: you're hired as a junior analyst at a fictional company. Colleagues message you on chat and email with requests, and you answer them — sometimes by writing SQL, sometimes by asking the right clarifying question first, sometimes by reading finished numbers and saying what does and doesn't follow from them. Roughly half the tasks need no SQL at all, because from the videos it looked like that's the half people actually get wrong.

Free, no signup, runs in the browser. No telemetry — one HTML file that works offline. English and Russian.

What I'd really like to know:

1. Do the requests read like something a colleague would actually send you?
2. Where does the difficulty break — too easy, or a jump that makes no sense?
3. Which part of your real job has no equivalent here at all?
4. Some tasks are built so exactly one answer is defensible (A/B tests, "what follows from this data"). If you disagree with any of them, that's the most useful thing you could tell me — it would mean I taught myself something wrong.

Link: https://solad-in.github.io/nexos-analyst-sim/
Source: https://github.com/Solad-in/nexos-analyst-sim

Thanks.

I’m a beginner in data analysis and I want to develop strong analytical skills, not just learn tools like Excel, SQL, Python, or Power BI.

As AI and technology evolve, I believe Data Analysts need strong problem-solving skills, critical thinking, creativity, and sound judgment to interpret data and make good decisions.

I’d appreciate advice on five things:

1. What skills should a beginner develop early?

2. How can I improve real-world problem-solving with data?

3. How can I develop genuine analytical judgment?

4. What projects or exercises build creativity and reasoning?

5. How can I find a good mentor to work with long-term?

I’m looking beyond courses and tutorials. I want to become an analyst who can think critically, question data, and solve meaningful problems.

Any advice from experienced analysts or data professionals would be greatly appreciated.

I see alot of these projects where people make a dashboard out of some fictional csv about pizza sales or similar, and everything is crammed on to a single page "top selling product" etc.

I know you've got to start somewhere, but tbh I really don't think these are going to help anybody get hired. If you had a Real project, where the data is all over the place, kept in different systems and formats, and actually took time to get it together into something useful, and THEN you make dashboards. The analytics should be showing not only the data but stuff that would help real decisions be made, then that's of more value - because honestly anybody can use these tools to just draw a graph showing pizza sales per month or whatever. Not to discourage anybody, keep on going (I have no idea what entry level looks like but I would assume they look for a quantative degree at least?

After a bad injury that includes my spine, I could no longer be in law enforcement. To put it plainly I need to wear sunglasses pretty much daily to reduce the stress on my eyes outside and inside. So I know a remote only role is needed in my life as I really do not want to have to answer questions on why I’m wearing sunglasses inside. I also have some other disabilities that I don’t want to get into as it’s still a sore subject for me. I plan on taking two IBM courses on coursera in order to learn the basics and make some projects. I know the TikTok trend is blowing up the field. But I really miss investigating and figuring out “problems” finding the reason it is happening then making a solution. My life was really turned around by this injury. I really would like any advice that yall could give on things I could also do or things you wish you would have known when you started. Thanks for reading this. (:

Question 1:

You have a dataset with 50 million rows, and it doesn't fit into memory. How would you analyze it efficiently?

My answer:

I wouldn't load everything into Pandas. I'd first filter only the required columns/rows, push aggregations to SQL where possible, process the data in chunks, and use tools like PySpark if distributed processing is actually needed.

Question 2:

Your dashboard suddenly shows a 40% drop in active users overnight. What would you check first?

My answer:

I wouldn't immediately assume user activity actually dropped. I'd first validate the data — pipeline status, data refresh, tracking events, source tables, filters, and any recent changes to the product or tracking logic. Once the data is confirmed, I'd investigate the actual cause.

If you were in my place, how would you answer these two questions?

Would love to hear how experienced Data Analysts would approach them.

Hey guyss!!

I am a recent graduate in EEE very much interested in data analytics roles. I want to learn from YouTube and udemy cources and from some other youtubers courses. Will this work out in 2026.

My goal is to get placed by the end of December 2026.

If anybody wants to prepare genuinely from scratch please dm me.

And please share your thoughts.

Thank you.

Hi, after months of searching for something I finally got a job as a crm data coordinator, the role seem pretty simple initially. Right now Im mainly doing some data entry into the CRM, but a lot of the data that Im having to enter from the excel files are incredibly messy and unfinished, for example in the excel theyll have one name, but on the CRM one the project will have a slightly different name or a completely different name, or maybe itll just be the acronym. Say Im searching for Riverdale Elementary School in the excel file, Ill enter that into the CRM and get back something like RIverdale ES, RES, Riverdale ES BLDG 1, Riverdale School, MUSD Riverdale, etc. And I have to basically figure out where the data goes. Not very technically hard, but not as easy as it sounds. And can be frustrating. Anyways how good of role is this? Am I essentially wasting my time?

Im looking for data analyst role, but after 6 months of searching, I was able to get only Strategy manager contract role in a small CDP data consulting company. (My previous job title was crm project coordinator in an international fashion company, basically managing salesforce and checking customer data are coming in and out correctly)

My company gave me this title, but Im not sure if they really think Im good fit or just gave it to me to bill clients where Ill be dispatched to work for them.

I work with my client and help them writing sns/online community marketing performance report, digging a bit why the number has dropped or up

My goal is to become a fulltime data analyst and I wonder if the title and JD will not help me when I apply for those roles later. What do you think?

Yo anyone who is interested in pursuing business analytics ,

Hey everyone,

I’ve been working in the Business Intelligence space for about 12 years. Throughout my career, I’ve built a solid foundation around:

Data Viz & Reporting: Advanced Tableau dashboarding, storytelling, and UI design for enterprise stakeholders.

Database & Querying: Mid-level SQL and relational database design/concepts.

Leadership: Team management, leading small-to-mid reporting teams, and bridging the gap between business stakeholders and technical teams.

With the current AI wave — generative AI, automated insights, NLQ (Natural Language Querying), LLM integrations, and modern semantic layers (dbt, Cube, Databricks Genie, etc.) — standard dashboard development feels like it's shifting fast.

While I know stakeholder management, business context, and governance aren't going away, I want to make sure my hard skills stay future-proof for the next 5–10 years.

My questions for you:

For those in senior BI / Analytics roles (10+ YoE), what skills or tools have given you the highest ROI recently?

Are you moving upstream into Data Engineering, leaning into AI/LLM tooling, or leaning further into leadership/management?

If you were in my shoes today, where would you invest 5–10 hours a week for the next 6 months?

Appreciate any perspective, brutal honesty, or personal career shift stories!

TL;DR: 12 YoE BI lead (Tableau heavy, mid-SQL, team manager) looking to reskill in the AI era.

Should I go deeper into Data Engineering (dbt/Python), AI/LLM analytics integration, Data Governance,

or double down on Data Leadership/Product Management? Looking for advice on where to focus.