Excited to share my latest Power BI project — a FIFA World Cup 2026 Tournament Analytics Dashboard.

I designed this dashboard to analyze the tournament from multiple perspectives:

📌 Page 1 — Matches Overview

A complete view of tournament-level match data, including:

• 104 Matches

• 328 Total Goals

• 3.15 Average Goals per Match

• Attendance Analysis

• Goals by Tournament Round

• Home vs Away Performance

• Possession, Saves, Fouls, Crosses & Offsides

• Interactive filters for deeper exploration

🏆 Page 2 — Top 3 Performers

A focused comparison of the top-performing teams across key metrics such as:

• Goals Scored

• Defensive Performance

• Possession

• Shots on Target

• Fouls

• Cards

🥇 Page 3 — Executive Summary

A high-level summary of the tournament, highlighting:

• Champion

• Runner-up

• Third Place

• Best Attack

• Best Defense

• Fair Play Team

• Highest Attendance Match

• Biggest Win

• Highest-Scoring Match

The goal was not just to visualize football statistics, but to structure the dashboard as a complete analytical story — moving from full tournament data → top performers → key tournament outcomes.

🛠️ Tools & Skills:

Power BI | DAX | Power Query | Data Modeling | Data Visualization | Data Analysis

This project helped me further improve my skills in transforming raw data into an interactive dashboard that communicates insights clearly and effectively.

I’d appreciate your feedback:

What would you improve or add to this dashboard?

Hi all, I have recently decided to take a break from my current trajectory in psychological research, and use the skills I have developed to transition into a data analyst role. Since then I have been working on projects using python, SQL, Power BI, and Excel. I would appreciate any feedback on my resume linked to this message. Thank you!

i applied for more than 200+ jobs but didn't here any response , i need some guidance what i did wrong , is anything bad in my resume , did i miss something

I’m about a year away from graduating with my bachelor’s in Biology, and I’m trying to figure out what I want to do with it.

I’ve worked in Medicaid provider enrollment for almost 10 years, and I originally thought I’d go into ecology or conservation, but I’ve realized I actually enjoy the problem solving and computer side of my current job a lot more than I expected.

I recently came across a Reporting Analyst position at my company, and it got me wondering if healthcare data analytics is something I should be looking into instead.

I’m curious if anyone here has made a similar transition from healthcare administration or provider enrollment into data analytics.

Does my biology degree really add anything, or would employers mostly care about my work experience and learning skills like SQL, Power BI, and Excel?

I guess I’m just trying to figure out if this seems like a realistic path with my background or if I’d basically be starting from scratch. If you were in my position, is healthcare data analytics something you’d seriously consider? I’d love to hear from anyone who’s taken a similar path or works in the field.

Thank you :)

What helped so far is using resume.zoevera.com to customize my resume for each application and prepare.zoevera.com to practice interviews with scenarios I'm expecting. It made my prep feel a lot more intentional instead of just hoping I covered the right things. Anyone else found something that keeps everything organized?

Hello,

I had an interview in a bank and I did good except I was told that I have no experience with working with big data,

could someone direct me on how to get those data other than kaggle? how to gain that experience

Hi, i am looking for process mining jobs whether freelance , projects or else. I hve built experience in doing my master thesis in conformance checking which included treatement of event log data and process discovery and ontology engineering, etc.

If you know any opportunities or jobs tell me. And thank youu.

Hey guys, I’m 21 and I recently graduated with a BE in Computer Science and Data Science. I’m currently thinking about pursuing a master’s in Data Science, but I feel a little lost about what I actually know.

During my undergraduate degree, I studied a lot of different subjects, including Data Foundations, DBMS, Computer Communication, Machine Learning, IoT, R Programming, Probability and Statistics, Big Data, Business Intelligence, Cryptography, Applied Machine Learning, and Data Visualization.

The problem is, even though I’ve studied all these subjects, I don’t really know how everything connects together or how these skills are actually used in the real world. Sometimes I feel like I’ve learned a lot of things but, at the same time, know very little about actual data science.

Before jumping into a master’s, I want to build a strong foundation and properly understand what data science actually involves. I also want to understand the differences between careers like Data Scientist, Data Engineer, and Data Analyst- what they actually do in their jobs, what the job market is like, and what skills I should focus on for each role.

Since I’m considering a master’s in Data Science, I’d also like to know what I should learn beforehand to make sure this is the right path for me.

If you guys have any good YouTube videos, courses, roadmaps, or other resources that could help me start from the basics and build a solid understanding of data science, I’d really appreciate your recommendations.

Just a clueless recent graduate trying to figure out what to do next. Any advice would be greatly appreciated!

New in this ..want a friends .. where we will be following a proper roadmap and making pair projects on discord .

Dm me if u are serious

Hi everyone,

I hope you're doing well.

I'm a recent CSE graduate who has been actively searching for my first opportunity as a Data Analyst or Business Analyst. I've been learning SQL, Excel, Power BI, and Python, working on projects, and preparing for interviews, but breaking into the industry as a fresher has been challenging.

If your company is hiring freshers or if you're in a position to provide a referral, I'd be incredibly grateful. I'm eager to learn, work hard, and contribute from day one.

Please let me know if I can share my resume.

Thank you for reading, and I truly appreciate any help.

Hi all, I did my bachelor's in India and recently got a US green card. I have zero professional experience so far and about 6 months to upskill before I start applying for jobs in the US.

I've been going back and forth between two paths:

• Data Analyst (SQL, Excel, Python, Power BI/Tableau)
• Full Stack Developer (Java/Spring Boot + React)

I don't need visa sponsorship, so my main question is which path realistically gets me hired faster as a total fresher given current US hiring trends. Would love to hear from people who've actually gone through this, especially anyone who broke in recently. Thanks!

Greetings!

I'm an international student (not from Europe) hoping to pursue a Bachelor's in Data Science or Data Analytics. At the moment, I'm not ready to relocate abroad, so I've been looking primarily at online bachelor's programs. Besides letting me stay home for now, I'm hoping it will also save on living costs.

The programs I'm most interested in are:

• University of London (LSE)
• Open University (UK)
• University of Essex
• IU International University

I have a few questions:

1. Is pursuing an online Bachelor's worthwhile for breaking into data analytics/science roles? How well are the degrees (especially from the universities mentioned above) respected by employers in Europe? Any success stories or warnings?
2. I'm not super confident in my math skills. I've heard about preparatory courses (e.g., for Open University and LSE Maths Essentials). Would those help bridge the gap? What’s the experience like?
3. If you've studied at any of these universities, I'd love to hear about your experience. Are there other online programs you'd recommend instead?

I'd really appreciate any advice, success stories, or warnings. Thanks!

i've been enrolled in a bootcamp(data engineering) for about a year now and i'm confident in my skills atleast for entry level roles. i'm based in Ethiopia and i can say that there's almost no data engineering jobs here ,there're very few open positions for data analyst or scientists which requires atleast 4years experience and you know that remote jobs are even more competitive and struggling for entry levels. the only tech roles here seems to be backend devs,frontend and fullstack(there're tons of jobs ).what should i do ,i love data but the market is really bad here.
thanks

Much like software development?

Hey, I am at crossroads now. I wish to show two good projects on my resume, my first project a simple e-commerce sales analysis is done. However it’s my second project that I have no clue over. I was thinking funnel analysis in Saas/ tech, but after a few linked in posts it makes me wonder am I over achieving here. Please tell me what should my next project be, where I can showcase my knowledge on Case, Joins, CTEs, windows. Please help.

Hey guys rank how these based on importance of being comfortable using these tools for a data analytics job or internship:

Python
R
SQL
Tableau
Power BI
Excel

Feel free to add any more you think is worth including!

grinded leetcode for like 3 months before my DA interviews and maybe 10% of it actually came up. writing this down bc the gap between what i prepped and what got asked genuinely annoyed me

stuff i wasted time on: hard leetcode sql, algo-style python, weird window function edge cases

what actually came up, roughly most to least common:

live sql but medium difficulty, the catch is doing it in ~20 min while someone watches. nothing exotic, joins/aggregation/a window function. two places gave me deliberately messy schemas to see if i'd ask questions before diving in

metrics cases were the make or break round everywhere. "DAU dropped 8% last tuesday, walk me through it." leetcode does nothing for you here, you need an actual structure. this is where i kept getting cut early on

"explain a past project to me like im a stakeholder" — they dig at whether you got WHY you did the analysis, not the sql

and behavioral, but deeper than i expected. "tell me about a time your analysis was wrong" showed up in 3 different loops lol

what i'd change: less leetcode, more timed practice on realistic stuff. for sql i just used stratascratch and dataford (real interview questions + the timer is the part that actually helps). metrics cases i wrote frameworks on paper and said them out loud until they stopped sounding memorized

also just look up the company's format first. glassdoor, whatever prep sites have company guides. take-home vs live vs case changes your whole last week

can write up the metrics framework in a comment if people want

I started learning a little about data analytics a couple months ago and I really enjoy it and want to pursue further learning and a career in the field. I just want to know beforehand if my background will stop me from being hired. I’m 35 now, my charges are from 2014 but it is a violent charge (I use to be a drug addict and committed robberies to supply my habit). I know that life is completely behind me now, and I just want to build a good life for my daughter who’s 2 years old, but at the same time I understand that consequences follow you for life. I’m not on any type of probation or anything like that and paid off all my fines, if that matters to hiring managers at all. I’m pretty open about everything, I just want to find out if I’m wasting my time or not, so I’ll appreciate any relevant response!

I am 22 years with a bachelors in economics and masters in data science. In the past 9 months I had been working as a data analyst at Siemens DISW, and I genuinely fell in love with the work I was doing and felt I was making an impact. On top of that it was nice just having a full time job in the career I wanted. I was laid off this past June due to “Workforce Restructure” which just sucks cuz I barely got my foot in the door. I don’t have much else experience in data analytics but I excelled and loved my job!!

Would love any advice on what to do because it’s been a struggling in this field lately. And while I was employed I was so grateful. It took me 4 months from graduating with my masters in June 2025 to land the role I had at Siemens. I feel like I’m back in the same spot and struggling to even get interviews!! Feeling really down and would appreciate any help or advice

Just to add on I did a lot of SQL work and dashboarding with PowerBI ! Edit: also wanting to add I have strong knowledge of ETL processes and have quite some experience working with AI and building agents!

Thanks again!

Cuando decidí cambiar de carrera y entrar al mundo de los datos, pensé que todo dependía de aprender herramientas: Python, SQL, Excel, Power BI...Y obviamente son importantes. Sin una buena base técnica es muy difícil avanzar. Pero después de comenzar a trabajar en análisis de datos me di cuenta de algo que no esperaba. Muchas veces el desafío no es obtener la información. Es lograr que otra persona la entienda.

Puedes hacer una consulta SQL impecable, construir un dashboard muy completo o desarrollar un análisis técnicamente correcto. Pero si quien recibe esa información no entiende qué significa o qué decisión puede tomar con ella, gran parte del valor se pierde.

En mi caso, una de las cosas que más me ha ayudado viene de mi trabajo anterior, donde pasé muchos años comunicando ideas y trabajando con personas. Nunca imaginé que esa experiencia terminaría siendo tan útil en tecnología.

Por eso creo que, a veces, nos enfocamos demasiado en aprender nuevas herramientas y muy poco en desarrollar habilidades como la comunicación, hacer buenas preguntas o entender realmente el problema que queremos resolver. No digo que las habilidades técnicas sean menos importantes, pero sí que rara vez son suficientes por sí solas.

¿Qué opinan ustedes?

Si tuvieran que contratar a un analista junior con el mismo nivel técnico, ¿preferirían al que comunica mejor o al que sabe una herramienta más?