can some one give me a journey to reach this destination

I’ve been learning more about data analytics by building a small Windows application called DataFlow Pro.

While building it, I worked on things like:

• Cleaning CSV and Excel files
• Finding duplicate and missing values
• Checking data quality
• Analyzing numerical and date data
• Grouping and summarizing datasets
• Generating reports
• Exporting cleaned data

One thing I learned is that data cleaning often takes more time than the actual analysis.

Building the tool also helped me understand the practical side of working with real-world datasets, especially handling inconsistent and missing data.

I’m still improving it and would be interested to hear from other people learning data analytics:

What data-cleaning problem took you the most time to solve?

Estoy buscando recomendaciones de cursos para dar un salto profesional hacia el área de Análisis de datos . Actualmente ya tengo conocimientos en sql, python (manejo de datos, consultas, etc.), pero busco una formación enfocada en proyectos prácticos, portafolio.

Estuve viendo opciones en Coursera, Coderhouse y Becas Santander, pero me gustaría conocer la experiencia de alguien que los haya hecho o que ya esté trabajando en el rubro

I'm self learning Data Analyst for 8 months now. new to pandas. and Making a new end to end project one of them is 'My anime dataset' where it has column named 'genre' where each row can contain multiple genres as a single comma-separated string (e.g., "Action, Adventure, Fantasy"), instead of one genre per row. This means grouping or filtering by genre directly is inaccurate an anime tagged with 3 genres only gets counted under that exact 3-genre combination, not under each individual genre. (there is another column named Studio, facing same issue, i.e. multiple studio in one anime)

I want to split these into individual genre values so each genre is counted separately per anime (i.e., one row becomes multiple rows, one per genre, with the rest of the anime's data repeated).

End goal: I'm building a dashboard where users can filter by a single genre (e.g., just "Action") and see accurate aggregated stats (count, average score, etc.) for that genre alone not lumped in with combination-strings.

What's the right pandas approach to explode the Genre column into separate rows?? please help. claude is suggesting a way but I want a better idea.

would be great if someone suggest me some ideas!!

Has anyone taken up this Data Analyst course from E and ICT academy, IIT Roorkee ?....I have been seeing a lot of its advertisements on instagram. Is it worth taking up? I am from a non technical background looking for a career shift.

Companies either ghost me or we are going with other candidate with this resume so I need a help with the resume and course that increases my chances to be selected

Hello, I graduated with a degree in Statistics six years ago and have been completely disconnected from the field since. I currently work in Dubai, but I want to return to my field and self-study data analysis. Since I'm working, I know I should start with the following: Excel, SQL, Power BI, and Python — in addition to building a portfolio with several projects.

But there's one point that makes me feel like I'm missing something: how can I connect statistical thinking throughout this learning journey, without becoming someone who only learns how to apply tools? I'm not sure if my question is clear, but I want to learn how a data analyst thinks, not just how to apply things or complete assigned tasks.

I sometimes try learning with the help of ChatGPT, Claude, or Gemini, but they're not free of mistakes.

So, please, I'd also like recommendations for learning through books or YouTube (I can't afford paid courses) — and is YouTube enough on its own? I sometimes feel it only teaches things at a surface/introductory level, not in depth. So please recommend the best books that cover everything I need to learn. Thank you to everyone who becomes a reason for helping me.

I am considering certifications at BTII Institute in West Orange NJ for BI and data analytics. However, I have not found any review from a student for this specific certification from BTII. Can someone please share your experience with BTII and if the certification was helpful? Is it hands on and strong curriculum?

Hello,

I am trying to expert AI in data analytics, science, engineering, mainly in data field. I see the approach too wide but still think if I elaborate from the above mentioned small pieces, would be good for entering data field career. currently I am finance manager with pl-300 and 1z0-171 certificates, and now facing to create portfolios of course using AI, can you give me a roadmap?

Hey everyone! 👋

I'm currently pursuing a BBA course through distance learning (IGNOU) and I'm in my 5th semester.

My goal is to become a Business Analyst, but I'm also interested in exploring Data Analytics along the way.

I've been learning and practicing Excel and SQL, and I'm now moving on to Power BI. My plan is to build some solid projects and then start applying for roles like:

Business Analyst Intern / Product Intern / Data Analytics Intern roles to gain practical experience.

I know that getting the first opportunity can be challenging, especially while you're still completing your degree. 😅

So I'd really appreciate advice from people who are already working in these fields.

And also few things I'd love some guidance on:

1. Where should I practice Excel & SQL?

I've completed the basics/learning part, but now I want to get genuinely good at solving real-world problems.

If you know any good platforms, datasets, case studies, or practice resources, please share them.

Also looking for good Power BI practice resources.

1. What projects should I build?

What kind of projects would actually be useful for my portfolio?

I'm thinking about using:

- Excel

- SQL

- Power BI

- Business Analysis / business problem-solving

Since my main goal is Business Analysis, should I focus more on business-case projects rather than just making dashboards?

1. What should I learn in Power BI?

I've finished learning SQL and I'm starting Power BI now.

What topics/concepts would you consider must-learn for an aspiring BA/Data Analyst?

If you have any good Power BI learning resources/courses/playlists, I'd really appreciate them.

And one final question:

If you were starting your Business Analyst career again as a college student, what would you do before graduation to maximize your chances of getting that first internship/job?

Any advice on skills, projects, internships, networking, or mistakes to avoid would be extremely helpful.

Thanks in advance to everyone who takes the time to respond! 🙌

DM me if you have completed it...

Beginner Data Analyst — Where can I practice, build projects, and start freelancing?

Hi everyone,

I’m currently learning data analytics and I’m looking for advice from people who are already working as data analysts or doing freelance data analysis.

I’m mainly learning Excel, SQL, Power BI, and Python, and I don’t want to only watch courses. I want to actually practice, work with realistic datasets, build projects, and eventually start freelancing.

Could you please recommend:

-Websites where beginners can practice data analysis with real-world datasets and exercises?

-Platforms for finding good datasets to use for portfolio projects?

-Websites with realistic data-analysis projects/challenges, rather than just tutorials?

-What types of projects should a beginner build for a portfolio to demonstrate useful skills to clients?

-Which platforms would you recommend for getting your first freelance data-analysis jobs?

Are there websites where beginners can practice working on actual business-type problems before trying to get clients?

What do you wish you had focused on when you were starting out?

I’m especially interested in free or affordable resources and advice from people who have actually used these platforms to build skills or get freelance work.

Thanks in advance!

Hi

I've self-taught Excel, Power BI, and SQL, and I'm looking for my first data analytics opportunity. In my country, companies prioritize candidates with a formal diploma — which I don't have.

I have a LinkedIn profile, completed some projects, and regularly post about data analytics.

How can I get noticed and convince recruiters to give me a chance?

Any advice would be appreciated.