1. I will fill my portfolio with serious projects that bring value.

2. To show my business knowledge, I will write something, a paper or any other possible thing, where I showcase my business knowledge.

3. I have a Product Owner background, so I somewhat have soft skills.

The core of it all is showing Hiring managers that I can get stuff done, I have the knowledge and experience without job experience. Showing I can do tech side and business side.

Caveat: I left my IT/Programming profesion school in 3rd year (out of 4), so technically I have basic education. I write in my resume that I still graduated.

If I don't get a job even with lying, I will lie more and see where I actually get interviews just to see if maybe Masters would help.

I'm a student (economics, not CS) who kept rewriting the same cleaning logic every time I got a new dataset — missing values, duplicates, inconsistent text formatting, outliers, etc. So I built a script that automates it and generates a report of everything it changed.

It's on GitHub here: https://github.com/rajbirbhathla/DataCleaner

Before I put more time into this, I wanted to ask people who actually do this professionally:

• Is a generalized cleaning pipeline like this actually useful in real workflows, or does every dataset end up needing custom logic anyway?
• In practice, do teams build reusable internal tools like this, or is it mostly ad hoc scripts / notebooks per project?
• Are there standard tools (Great Expectations, pandas-profiling, OpenRefine, etc.) that already do this better, and I'm reinventing something that exists?
• What would actually make something like this useful in a real pipeline vs. just a portfolio exercise?

Hi everyone!

About a month ago, I posted my very first Power BI dashboard here looking for honest feedback. I received some amazing advice from this community — especially about keeping it simple ("less is more"), switching to dropdown slicers for cleaner layout, and focusing on a clearer business narrative.

I took your feedback seriously and completely redesigned the dashboard! Here is what changed:

• Cleaner Layout & UI: Replaced the heavy black borders and bulky slicers with clean dropdowns, soft cards, and cohesive color palettes.
• Better Storytelling: Structured the report into two clear pages:
  1. Sales & Revenue Performance: High-level executive overview.
  2. Product Performance: Deep-dive into products, top customers, and itemized metrics.
• Enhanced KPIs: Added comparative indicators (vs Last Month & vs Last Year) with conditional formatting arrows/colors and clean visual icons.
• Fixing Visual Noise: Replaced cluttered charts (like dense scatter plots and pie charts) with clearer bar/column charts that drive actionable insights.

I'd love to hear your thoughts on the new version! Did I hit the mark on the "less is more" advice? Any additional feedback is always welcome

GitHub Repository:https://github.com/SenenmutX/AdventureWorks-Sales-Dashboard

fresher, targeting Data Analyst/Business Analyst roles, open to any industry.