guys I have a confession 😅
I've been confused about rows and columns forever. not like I didn't know them, it just gets mixed up for me sometimes
today's class finally fixed it. So
rows go sideways ➡ 1,2,3
columns go down ⬇ A,B,C
6/30 #30DaysOfTech@TechSphereAcad
So, there's a whole phase called Iteration and Feedback. you analyze, share with stakeholders, they push back, you go back in and refine. over and over.
so if you've redone something for the fifth time…
how are you guys even coping 😭
day 5 of #30DaysOfTech
who actually makes decisions in a data driven company?
I thought it was just the executives.
Turns out data analysts are in that room too giving recommendations that shape real business decisions.
A little something I learnt in class yesterday 😊
@TechSphereAcad@ezekiel_aleke
day 3 of #30DaysOfTech with @TechSphereAcad
My classes start today at 6pm
no big feelings about it.
just showing up
new job, NYSC, now classes, the next few months are about to be a lot but one step at a time 🫡
let's see how this unfolds
Omo, AI just humbled me 😭
Tried to hand off a task, it couldn't do it the way I needed. Had to do it myself.
but thinking about it, you always know when something is AI.
Human touch still hits different and I don't think that's changing anytime soon
2/30 #30DaysOfTech
Day 1 of 30 🗓️
@TechSphereAcad 30 days learning challenge starts today and I'm in. Will I keep up? 🤷🏻♀️ Honestly no idea. But we'll see.
So this is just an opportunity to make my first post on here... hi guys 👋😂
Let's see how we do.
#30DaysOfTech#LearningWithTS
Act as a senior data analyst and dataset engineer.
Generate a realistic, clean, analysis-ready dataset for [sector]
Dataset requirements:
- Number of rows: [e.g. 500, 1,000, 10,000]
- Columns needed: [list all columns]
- Data type for each column: [text, number, date, category, etc.]
- Realistic distributions and patterns (no random assumptions)
- Include real-world inconsistencies where necessary (missing values, duplicates, typos, outliers) if relevant.
- Make it suitable for: [Excel practice / SQL analysis / Power BI dashboard / Portfolio project / ML, etc.]
Output format:
- Present as a clean table
- Make column names clear and professional
- Ensure the data is realistic and logically consistent
Extra:
- Briefly explain the business context behind the data
- Suggest 5–10 analysis questions that can be answered from the dataset
@asherrkiinee A Laptop🙏🏼
I was awarded the Asherkine scholarship to study Data Analytics at TS Academy 2 days ago. A Laptop will be so helpful to further my learning and after.