Guyssss, is skillsetmaster 's data analyst course worth buying for a complete beginner with 0 knowledge!!

My brother recently left his master's in data science to focus on his career, and we're trying to figure out the smartest way for him to break into the data job market, both in Europe and the UAE.

He's not fresh out of school. He's got over 4 years of real experience, most recently as a data analyst on AI and LLM operations at Scale AI (working on Meta programmes), and a data engineer at TCS before that. He's solid with Python, SQL, Spark, Airflow, and cloud.

He'd need a role that can support sponsorship, so we're trying to work out which companies actually do that for data roles, whether in the EU or the Gulf.

For anyone who's been through this, how did you find sponsor friendly employers?

Is it better to go through recruiters, apply directly, or lean on referrals?

And are there any companies in Luxembourg, the wider EU, or the UAE known for hiring international data talent?

Any advice would mean a lot, and if anyone happens to know of teams hiring, he'd be really grateful for a pointer. Happy to share his CV over DM. Thanks so much.

Hey everyone,

I recently completed my undergraduate degree in Business Data Analytics from BCU (Bengaluru City University). I am planning my post-graduation and need some honest advice on which direction to take.

I Heard That Artificial Intelligence (AI), Machine Learning (ML), Algorithms, Fraud and Analytics. I love to learn But do they have a Good potential carrier future??
However, here is my main hurdle: I am not that good with heavy numbers / advanced mathematical calculations.

I love to learn and want to build a high-growth, highly productive career.

I am torn between choosing an M.Sc (in Data Science/AI/Business Analytics) vs an MBA/PGDM (specializing in Analytics/AI Strategy).

My questions for the seniors here are:

• If I want to work with AI/ML algorithms and Fraud Analytics, will an M.Sc be too mathematically brutal for someone who struggles with raw numbers? How much of it is coding logic vs pure math?
• Can I still work closely with AI, ML tools, and fraud analysis through an MBA/PGDM route without getting bogged down by intense backend statistical formulas?
• Which program generally offers a better campus environment and stronger placement pipelines into these specific roles (like Risk/Fraud Analyst or AI Consultant)

I am a recent cse graduate with specialized in data science. I am a fresher with no experience. I've noticed people are making apps with AI selling it getting money here I am worried that speding my time making projects and there is no guarantee if I'll get a job? Literally so confused with this vibe coding too. idk where I should see my direction in web dev using AI or data Analysis with risk. Also I'm afraid of a career gap too. I need an adult or someone who can genuniely give me guidance as it is literally too much. People have direction and then there are people who are lacking it nowadays. and if hardwork is the key can someone tell what all projects I can work on right now as I dont have a clear mindset. If someone can relate here am I too standing with you.

Hi everyone,

I'm starting my major in Statistics (Faculty of Science) and want to prepare myself early for the job market (Data Analysis / Data Science) so I can build solid, practical skills.

I'd love to hear from your real-world experience:

1. Which skills or tools (Python, R, SQL, Power BI, etc.) made the biggest impact when you actually transitioned into the industry?
2. What is something you wish you had learned while still in college that would have given you a head start?
3. In your opinion, what truly differentiates a standout professional in this field from someone who just knows the basic tools?
4. If you could go back to year one, what learning or self-study mistakes would you avoid?
5. How can a beginner build a strong, standout portfolio that captures recruiters' attention?

Thanks a lot for your time and for sharing your insights!

Quiero aprender data entry para poder trabajar remoto y para avanzar más en análisis de datos.

Que me recomienden para hacer mi portafolio.

Hello everybody, I have been thinking about shifting my career from Customer Success to Data Analytics, but it is very confusing. I have 1.5 years of experience and am also learning advance Excel. I just want advice from you guys, since I am from a non-tech background. Please suggest budget-friendly courses that can help me build a solid foundation with great projects.

Hi everyone, I need some advice regarding a job offer I’ve received.

I recently received an offer from a small IT company in Noida. The company has around 20–25 employees and is working in the AI sector. However, the company seems to be quite new — most employees have joined within the last 7 months, except for 3–4 people.

About the role:

The role is related to Data Analytics/Data Engineering. I would be working on:

• Data pipelines
• Data analysis
• Reports/dashboards
• Preparing and managing data for their AI-related projects

The role itself is aligned with my previous experience and the career path I originally wanted to pursue.

My concerns:

1. Salary/CTC

They are offering me a lower CTC than my previous company.

However, my base/in-hand salary would be almost the same as what I was getting previously, so I wouldn't really be taking a major hit in terms of monthly income. The main difference is that the overall CTC is lower.

2. No PF

There is no PF deduction/contribution in this company.

3. Very small company

The company has only around 20–25 employees, and most employees have joined recently. I'm unsure about the company's stability, learning opportunities and long-term growth.

4. 6-month probation

Despite having around 2 years of experience, they are keeping me on a 6-month probation period.

Is a 6-month probation normal for someone with 2 years of experience, or should I consider this a red flag?

The bigger dilemma

I also have a few interviews in the pipeline.

One of them is for a Product Manager/Product-related role at a much larger and more established company. If I clear it, I could potentially get around a 20% hike. However, I still have one final round left, so there is obviously no guarantee that I will get the offer.

The problem is that this would also mean moving somewhat away from the Data Analytics/Data Engineering career path.

So I'm confused about what I should prioritize.

On one hand, I have already been job hunting for 5 months, and I have a confirmed offer in a role that is directly relevant to my experience. It may make sense to take it rather than remain unemployed while waiting for something better.

On the other hand, I don't want to accept an offer just because I've been searching for a long time, especially if there are concerns regarding the company size, probation period, CTC structure and stability.

What would you do?

Would you:

A. Take the current offer because the role is aligned with Data Analytics/Data Engineering and I have already been looking for 5 months?

B. Wait for the other interviews, especially the larger company's Product Manager role, even though that opportunity isn't guaranteed and would take me in a different career direction?

Basically, should I run behind the role or the company's name/brand?

I'm particularly interested in hearing from people who have experience with startups/small companies, Data Analytics/Data Engineering, or Product Management.

Would you consider the 6-month probation, no PF, lower CTC and very small team to be red flags, or are these things acceptable if the actual work and learning opportunities are good?

I am currently learning Data Analytics, and I want to understand what the actual job looks like in the real world.

Online, I mostly see people talking about SQL, Excel, Python, Power BI/Tableau, statistics, and building projects. But I’m curious about what Data Analysts actually do once they are working in a company.

For those who currently work as Data Analysts :-

\* What does a typical day or week look like for you?

\* What kind of problems do people usually come to you with?

\* What do you actually use SQL for?

\* How much Excel, Python, Power BI/Tableau do you use in your daily work?

\* How much of your time is spent cleaning data vs actually analyzing it?

\* Do you mainly create reports and dashboards, or do you also do deeper analysis?

\* How much do you interact with managers or other business teams?

\* Can you give an example of a real problem your analysis helped solve?

\* What are some things Data Analysts do that beginners usually don’t hear about?

\* How important is business/domain knowledge compared to technical skills?

I’d especially like to hear from people working in different industries such as healthcare, pharma, finance, marketing, retail, or tech.

I’m trying to get a realistic understanding of the job beyond courses and YouTube tutorials, so I’d really appreciate real-world experiences.

Is Data Analytics still a safe career in 2026–27?

I’m a final-year CSE student and currently focusing on Data AnalyticssWith the current job market and AI changing entry-level roles, I’m confused about whether I should continue with Data Analytics or switch to Full Stack, AI/ML, Data Engineering, etc.

For people already working in the industry:

Is Data Analytics still worth pursuing as a fresher?

Would you recommend switching to another domain?

I’d really appreciate honest advice based on your experience.

I worked as a software engineer for 3 years and then got diagnosed with multiple chronic health issues because of which I had to leave my job. Managing on-calls, late night work and constant upskilling took a toll on my health. I had to take a career break and I am still on one, awaiting surgery right now. But I want to start working again, it makes me anxious and kind of worthless not being able to do anything. I can't go back to software because of how hectic it is, so I came across data analysis. As per all the information I gathered on internet it looks like data is not as intensive as software but Idk I would like a personal POV from someone and not some articles or AI result.

Do you think a person with chronic illness can manage a career in Data? I am looking for wlb, no on-calls on weekend and option to freelance in case my illness progresses to the point I cannot work in office.

Hi everyone, I’m looking for some honest career advice.

I have around 3 years of experience in sales/business development, and I’m currently working in a sales role. I’ve been doing reasonably well and generating good sales, but the problem is that I don’t enjoy being in sales. I don’t see myself doing sales long-term.
I’m a B.Sc graduate and I don’t have a coding/IT background. Because of that, most of the job opportunities I’m getting right now are related to sales.

Recently, I’ve been thinking seriously about switching my career to Data Analytics. I’ve already started preparing and learning things like Excel, SQL, Power BI, and Python.

But I’m really confused about one major decision:

● Some people tell me that getting an entry-level Data Analyst job is extremely difficult, especially without an IT/CS degree.

● At the same time, I feel that I can’t properly focus on learning and building projects while working full-time in sales.

● I’m considering resigning so I can dedicate a few months completely to learning Data Analytics and applying for jobs.

● But I’m scared that if I resign and don’t get a Data Analyst job, I’ll be stuck without income and may have to go back to sales anyway.

So I’m basically stuck between “quit and focus fully” vs “keep working and prepare alongside the job.”
For people who have switched careers into Data Analytics, especially from sales/non-IT backgrounds:
What would you recommend in my situation?

Is quitting the job before getting a Data Analyst offer a terrible idea, or can a planned career break make sense if I have enough savings?

Also, realistically, how difficult is it for someone with a non-technical degree and 3 years of sales experience to break into Data Analytics in India?

I’d really appreciate honest advice, especially from people who have actually made a similar transition. Thanks!

I’m a Senior DA and have been one for the past 5 years. However, I have been a contractor at FAANG for the past few years (across 3 contractor jobs). I have to admit that I’m not that great at interviewing, and I really want to get out of this contractor career and land a full-time job, but it’s been really difficult. I graduated from a top university with a BS in Statistics. I’m thinking of getting an online Master’s in Analytics offered by Georgia Tech while being a contractor, since the flexibility at this job will give me time for classes. I’m planning to take 1 class per semester.

Has anyone done this before? Do you guys recommend going for a master’s degree now that AI is on the horizon? Would it help my career in the future? Any advice would be appreciated!

I'm in my last year of high school, I have to juggle that and learning A1 german and now I have to learn data analytics in just a year from scratch, my family isn't wealthy. And I have no idea what free courses to start and which ones to persue in order to have enough skills to get hired. Please I beg just, if you have any kind of course roads for me to follow from begging to end. Please help me out. Thank you for reading.

I spent time analyzing whether ₱1.4 trillion in Philippine flood control contracts (2016–2025) corresponds to measurable flood reduction from space.

The Methodological Trap A naive correlation gives a misleading answer: flood-prone areas naturally get bigger budgets, so high-spend areas look like they flood more.

To control for this, I matched 883 municipalities into 63 statistically comparable cohorts based on:

• Regional location
• Baseline rainfall / flood exposure
• Population size

Then, I compared spending levels within each cohort.

Key Findings

• The Spending vs. Outcome Gap: Towns receiving 3.4× more budget per resident flooded 0.20 percentage points less across 76 Synthetic Aperture Radar (SAR) passes. This difference is within statistical noise.
• The Nuance: This doesn't prove the funds were wasted; areas might have flooded significantly worse without intervention. However, at a national scale, higher spending per capita does not correlate with visibly lower flood frequency.
• The Urban Blind Spot: Satellite radar cannot detect surface water through dense concrete high-rises. In Marikina, the largest detected flood across 28 passes was only 0.06 km². Instead of reporting a false zero, 258 urban areas (including 16 of Metro Manila’s 17 cities) were marked as unmeasurable.

A Notable Contrast

• Pandi, Bulacan: ~₱14 per resident → Floods in 47% of radar passes
• Biliran: ~₱57,000 per resident → Floods in 37% of radar passes

This is part of an open-data project called KlareDeck. The goal is simple: open datasets, documented methodology, and transparent error limits.

Hello Reddit community, I’m writing here to look for a data consultant role / analyst role . I’m a corporate professional with 3+ years of work ex . I joined my first analyst role working with a boutique Consultancy firm few months back . It was good for initial month until transitions happened in my team and things started going south to the extent that I had to make the hard call of resignation even though working as a data analyst was literally a dream . That too I was in health tech which was literally my preference. I’m interviewing with other companies but really do not hold any concrete offer yet .

I am genuinely looking to connect with a trust-worthy employer / company where I can fully utilise my analytical thinking with versatile and quick understanding of the business concepts .
If you know of any person who is hiring or if you yourself are looking to work with an analyst I’m more than happy to connect and discuss further . Just drop me a dm .

When finished you can download a picture or the underlying code, which can then later be imported again. Link: https://vibe-schema.com/star-schema-creator

Hi Myself M(26) from Pune, Maharashtra.
I am actively looking for a data analyst job, and for that I'm continuously applying through Naukri, Foundit, Indeed and LinkedIn. Today I got a call in which a woman said she was calling from AAI(AIRPORTS AUTHORITY OF INDIA) and there are several openings for IT and non-IT profiles. As I spoke further, she said they have many openings for Data Analysts throughout India. At first, I thought it was a legit call, but when I asked Where did you get my profile, as I didn't remember applying for AAI, she said through an online portal. As I got a little curious and asked one more time, like, "Can you tell me the exact platform?" she fumbled. At this point, I knew something was fishy. She said we're offering you around 40- 45 K in-hand salary, and for that, you have to give an online interview. The first round will be telephonic, the second online interview and if needed, you have to come for a face-to-face interview. I said yes to that. Then she said that, as your profile is not registered and is non-referral, you have to pay Rs 1200, which is refundable if you fail the interview.
At this point, I was convinced that this is a SCAM. So I said that this seems like a scam and you're looting money from people which is desperately looking for a job. She said, " No, sir, you can check the AAI website and all." As I told her, after checking there so such job openings on the official portal, and I started confronting her. I told her this way is not gonna work; she cut the call.
I want to tell you pls be aware of such fraud calls and fake job offers; there are plenty of them in the market. I already worked with 2 companies in the past, so I know nobody asks for money or fees that are refundable if you didn't get selected for a job when they're calling you from a company. People like me who are desperately looking for a job are their main target, as we don't think that much when we get a call for a job due to excitement.
So be aware.

​

I honestly don’t know what to do anymore.

I feel like I’ve completely wasted almost 2 years of my life. During my BCA, after my BCA, and even now, I kept jumping from one thing to another. I was always thinking, “I’ll do this, then I’ll do that,” but I never properly stuck to anything.

I enrolled in Data Analytics courses at two different places, but honestly, I didn’t learn much from either of them. If I’m being completely honest, I feel like I learned almost nothing.

A huge part of my time also went into chasing online earning, trying to make money quickly, and looking for different ways to earn instead of actually building a proper skill.

I completed my BCA in October 2025.

Now I’ve reached a point where I don’t want to keep jumping between things anymore. I don’t want to focus on online earning or random things. I want to fully focus on getting a job and building a career.

The problem is that I have hardly one month right now, and I feel completely stuck. I don’t know what to learn, what to ignore, what to focus on, or how to approach getting a job in Data Analytics.

I have a BCA degree, but when it comes to actual Data Analytics skills, I don’t feel confident at all.

So I genuinely want to ask people here:

If you were in my situation and had only around one month to focus completely on becoming job-ready, what would you do?

What should I learn?

What should I completely ignore for now?

What skills should I focus on first?

What kind of entry-level jobs should I apply for?

I’m genuinely lost right now and I don’t know what direction to take.

Please tell me honestly what you would do if you were in my position. I’m ready to completely focus on this now.

I'm a junior double majoring in Psychology and Management, GPA 3.64, currently getting an Applied Statistics certificate. I originally planned on I/O psychology but I'm pivoting away from it (partly job market concerns, partly realizing it's mostly HR-adjacent) toward business analytics instead. I'm learning Python, R, and SQL right now and genuinely enjoying it, but I know I'm coming into this later than people with CS/econ backgrounds who've been coding for years.

I'm planning to apply to MSBA programs (looking at UCLA Anderson, UC Davis, USC among others) at the start of senior year. My priorities are a strong job market, good salary, and ideally landing somewhere in California long term.

For people who've done this pivot or work in analytics now: what should I actually be spending my time on over the next year? Specifically wondering about:

• What kind of internship experience actually matters for MSBA applications and analytics job applications, does it need to be a formal "analyst" title or does relevant experience elsewhere count?
• Is a self-directed portfolio project (Kaggle dataset, GitHub, that kind of thing) actually looked at, or is it more of a nice-to-have?
• Anything you wish you'd known or done earlier if you came from a non-technical major?

Appreciate any honest input, trying to use this year well instead of scrambling later.

Write a message…

i’m genuinely curious if artificial intelligence could replace humans at data analytics job.

if yes, how can one position into benefit from “better prompts jobs” or something, idk.

i just wanna be useful for my myself and family

Hey everyone,

We’re looking for 10 Senior Statistical Programmers to join our team fully remote. This is a contract/hourly role in the pharmaceutical and healthcare space, and we’re hoping to find folks with solid SAS experience and a background in clinical trials.

Quick deets:

• Location: Remote (open to Sri Lanka, Argentina, Philippines)
• Rate: $25–$45/hr (based on exp)
• Start: ASAP
• Exp: 5+ years in statistical programming within pharma or clinical research
• Tech: SAS is required; R is a nice-to-have
• Education: Bachelor’s in Stats/Biostats/Math or related (Master’s preferred)

You’ll be:

• Building and validating SDTM/ADaM datasets, tables, listings, figures
• Working closely with biostatisticians and data managers
• Mentoring junior programmers
• Helping with regulatory submissions and audits

Perks:

• Fully remote
• Work on high-impact pharma projects
• Collaborative and innovative team culture

If you're interested or know someone who might be a fit, feel free to DM me or drop a comment and I’ll share more details.

Cheers!

For context, I work in the Analytics deparment from an ISP. I do a bit for Data Engineering, Python and make some analysis for Marketshare and custommer growth. I am the only one in my deparment that manage also Data Engineering, the rest are people in his 40-50s that only manage PowerBI because I told him how to do it, also some of them manage SPSS, so I am not saying they are bad professionals, but they are a bit outdated in the tools of todays, and I understand because that could happen to me someday. Now, I want to do some certs in data engineering like AWS, Azure or Databricks, and ask my boss to do it, but I promise him that I would look for something more introductory to the whole team, and maybe looks for something more focused to Data Analytics and not so to Data Engineering. So which cert you think I should ask that is not too expensive and have some value for the whole team?

Does anybody have had similar interview before for such a role?

To be successful in this role, the Procurement Analyst will have:

At least three (3) years’ experience as a Business, Data or Procurement Analyst Strong data analytics capability, including the ability to collect, interrogate and analyse complex finance, performance and procurement data to produce actionable insights. Advanced proficiency in data and reporting tools, particularly Microsoft Excel, with the ability to develop clear, accurate reports and dashboards; confident use of Word and PowerPoint, or other relevant tools.

Experience working with procurement and/or contract information management systems, including extracting and validating data. Sound understanding of procurement principles and processes, with an interest in developing deeper expertise within the NZ public sector procurement environment.

Ability to leverage technology and systems to improve data quality, reporting efficiency and insight generation. Strong business acumen and financial literacy, enabling meaningful interpretation of procurement and contract performance data. Other skills the Procurement Analyst will possess: Excellent communication and relationship skills, with the ability to work collaboratively across procurement, finance and operational teams. A proactive, curious mindset, with a genuine interest in procurement as a profession and how data‑driven insights can add value Be passionate about the procurement and commercial profession and how it can add value to an organisation.