r/dataanalyst

I am preparing for a data analyst job role. I have 1 year of experience as a web developer. Let's study together.

Recent grad here, currently learning data analysis (SQL, Python, the whole path) while job hunting. Honestly the hardest part hasn't been the skills — it's doing this completely alone. No one to bounce questions off, no one to just vent to when a rejection email hits, no one who actually gets what this stage feels like.

So I started a small Discord called Call Out — for anyone in a similar spot. Job hunting, upskilling, figuring out the next move. Not a course, not a paid program, no gurus. Just people showing up, sharing what they're learning, asking dumb questions without feeling judged, and keeping each other going.

If that sounds like something you need right now, come hang out: [htt://discord.gg/w2Dp9rXNb]

No pressure, no sales pitch — just looking for people who get it.

hoping people will reach out .....thank you .add tps in the link

Since AI is replacing jobs, I don't think data analytics is gonna be worth it. Most of the entry level jobs are getting replaced or are gonna be replaced in the near future and to get a job you require experience. So where are you gonna get that from. And now everybody would try to take the role of the person that uses AI to do the analysis instead of 10 people who got replaced. So basically 10 gets replaced and 1 gets a new job. Everyone would start learning AI to apply it in their fields and then it would leave the jobs of not much value cus of the competition. I don't know which field i wanna choose at this point.

My_Qualifications: B.Tech Mechanical Engineering (May 2026)

I knew before graduating that I wanted out of mech. It wasn't just the low pay, I genuinely had no interest in manufacturing/core jobs anymore. I also put my master's on hold cause I wanted work ex first. I don't wanna spend another year just learning something and end up with a huge gap on my resume.

At first I thought about support/sys admin/QA kind of IT roles since I'm not into hardcore coding or SDE stuff. Later I switched to analytics cause it looked like it'd have more options. I've learned Excel, learning SQL rn and planning to do Power BI next, but no portfolio or analytics internship yet.

The more I research, the more confused I get. First people say learn tools, then Python, then AI, then AI agents, then domain knowledge. As a fresher, idk how I'm supposed to get domain knowledge without getting my first job.

I'm applying on and off campus but barely getting any calls. So should I keep going with analytics or switch to something else? Should I target IT support/testing roles instead? Or just prepare for CAT/GRE and move on?

I'm not looking for "the market is bad" replies. Ik that already. I just wanna hear from people who were in this phase and actually made it out. What would u focus on if u were starting from scratch today?

I'm a fresher preparing for a data analyst role, and I'd love to understand how SQL is used in day-to-day work.

For those with experience as data analysts, what does your daily SQL work look like? What types of queries do you write most often? Do you spend more time writing new queries, optimizing existing ones, creating views or stored procedures, or something else?

I'd really appreciate hearing about your real-world experience.

I'm a data analyst fresher and I'm curious about the role of machine learning in a data analyst career.

Is machine learning actually required for data analysts, especially for someone with 2–5 years of experience? If yes, how much should we learn? Is a basic understanding enough, or are algorithms, model building, and deployment expected in day-to-day work?

I'd love to hear from working data analysts about what you actually use on the job.

Right now I'm learning python hit me up if you are in same boat

I'm preparing for a data analyst role and have been learning SQL, Power BI, and Python. One area I'm struggling with is domain knowledge and business thinking.

How did you learn about different business domains (e-commerce, banking, healthcare, etc.)? What resources or approach helped you the most?

Also, when you're given a business problem, how do you approach it? How do you break it down, decide which metrics to analyze, and identify the root cause?

I'd really appreciate any advice or resources that helped you when you were starting out.

In two weeks, I'm starting a new job as a data analyst at a Silicon Valley startup.

I spent my previous careers in product and program management focused on data infrastructure. I went back for a master's to switch careers as a data analyst (or scientist), and finally landed the role I wanted.

It's going to be an interesting journey, switching careers in my 40s into a profession that's quickly being taken over by AI. I'm confident in this career switch, but only if I can consistently provide value beyond what AI can. That's also what makes it exciting.

My question to the group: would you be interested if I documented this journey/survival in a blog?

It wouldn't be another "how to become a data analyst" guide. It would be more like: "Here's what I'm trying," "Here's why I made this decision," or "Here's what failed and what I learned." It will not be anonymous.

If that sounds interesting, give me a thumbs up. And if you have time, I'd love to hear what kind of content you'd actually want to read.

Thank you!

what is required tech stack for data analyst beginner roles , and how can i level up my skills , what sort of projects i should focus on and what is its scope , is it still in demand ?

I am currently working as a Business Analyst for one year and am considering earning this certification to upgrade my skills and advance my career. However, I am unsure how much value this certificate will add to my professional profile. Since it costs $82, do you think this certificate will enhance my professional profile?

I'm starting a journey of learning so I can become a data analyst. I went on SQLZoo to get myself started but I came across a couple of challenges that left me frustrated and ready to give up, I had to go up and down looking for resources to help me.

My solution right now is learning SQL, Excel, PowerBI and other tools on a platform with proper structure like I'm used to doing from the time I was in school. I wanted to do the Google Analytics Course on Coursera but I read a lot of reviews saying it's "fluff", I've also been checking Data Camp and others, FreeCodeCamp has this really long video and I got instantly overwhelmed.

What's the best place to get started on my journey, that has a clear syllabus and can give me tasks so I know how I'm doing while maybe giving me projects as well that could get me a step ahead to land my first job. An added bonus is if I can get it for free or not too expensive.

Any tips and advice will be highly appreciated.

Started Data Analytics in 2025. Learned SQL, Excel, Power BI & Tableau. Now learning Python. What projects should I build to get a job?

Hi everyone,

I started learning Data Analytics in early 2025 without any prior experience. Over the past year, I've been consistently studying and practicing.

So far, I've learned:

- SQL (Joins, CTEs, Window Functions, Queries)

- Excel (Pivot Tables, XLOOKUP, Dashboards)

- Power BI (Data Modeling, DAX, Interactive Dashboards)

- Tableau (Visualizations & Storytelling)

Recently, I started learning Python, mainly focusing on Pandas, NumPy, and data analysis.

Now I'm at a stage where I feel stuck.

I know learning tools isn't enough to get hired. Most job descriptions ask for projects and practical experience.

My question is:

- What type of projects actually help in getting a Data Analyst job?

- Should I build end-to-end business projects?

- Is it better to focus on SQL + Power BI projects or Python projects?

- How many strong portfolio projects are enough?

- What datasets would you recommend for someone targeting an entry-level Data Analyst role?

I'd really appreciate advice from people who have recently landed a Data Analyst job or who interview candidates.

Thanks in advance!

Just started in an entry-level new role for a health care company. However, most of the job is just refreshing Crystal Reports and setting new parameters for Crystal. I do a little tedious stuff here and there using Excel, but nothing a high schooler can't do. Don't use much SQL or Tableau/Power BI? Is this normal?

I've recently completed my MBA and am looking to build a career in Data Analytics.

I'm currently learning SQL and was planning to move on to Python (Jupyter Notebook, Pandas, Spyder, etc.) afterward. However, I'm trying to understand what companies actually expect from entry-level Data Analysts.

• How important is SQL compared to Python?
• How much Python is typically required?
• What skills are most commonly asked for in interviews?
• If you were starting today, what would you focus on first?

And they’ll be like “Must have 10+ years experience in our ultra niche HR software called GABA-GOOK”

Or “Must know python, R, C++, tableau and MEDICAL CODING skills of a NURSE PRACTITIONER”

Bruh…

I want to transition into Data Analytics, but I'm worried I missed the boat. With AI handling so much of the technical workload today and companies heavily adopting AI automation, is the field still relevant for newcomers in 2026?

A bit about me: I have a degree in microbiology, and I'm returning from a career break.

1. What core skills are required to stand out to employers right now?
2. How can I build practical, real-world portfolio projects that prove business value?
3. Can I leverage my microbiology background as an advantage in specific sectors (like biotech or healthcare data)?
4. What is the most effective way to cold-message recruiters given my career gap?

Thanks in advance for the reality check!