PRIME

The best way to end the year 🥹😍 Didn’t deserve it I earned it

@dekhane_mukul Poco loco

Don't force children to take science if they interested in Arts Issued in public interest!! 😂😄🤣 #Wisdom

Bi Developers, on avg, how long will this take in Power BI or Tableau? I know Excel can’t do it so excel people please shit. Note: this is a UI design by @Agunbiadesina1 not an actual analysis.

This DAX Measure let’s you send Emails Directly from Power BI Full video on YouTube ✌🏻 #powerbi #report #dax

@ObohX @iam_daniiell 😂😂😂 Yakubu you can always manage No fear

@Prime_Analysis @iam_daniiell This year I say make I dey mind my business, as I see am I pass 😂😂 Make una no put me for talk

😂😂😂 Omo na joke ooo, excel can actually do it My bet on @ObohX and @iam_daniiell

@_VictorUgwu @Agunbiadesina1 Na me talk am Oya do your worst 😂

@Prime_Analysis @Agunbiadesina1 Who said Excel people can't recreate it

@dhisaniya @Agunbiadesina1 Hmmm 3-5 days It’s a 6 page analysis ooo

@Prime_Analysis @Agunbiadesina1 It takes 3 to 5 coz thinking of what data to show takes alot of time for me.

@Agunbiadesina1 Beautiful work How long does it take you?

I challenged myself to design a modern, clean, and data-driven eCommerce dashboard UI

@pengs_love Idolo stop scrolling

Stop scrolling Get to learning

You think that you need to learn all tools for you to become a data analyst or job ready? Guess what, you can be a data analyst and job ready by first learning data analytics concepts, context and Excel. Many have limit data analytics to Tools and dashboard.

I don’t get why this sounds funny. In the right context, you become job ready as a data analyst within 3 months.

Data Analytics mistakes beginners should avoid: 1. Jumping Straight to Visuals - Skipping Data Cleaning (EDA) - Leads to incorrect charts - Clean and explore data first - Understand the "shape" of your data 2. Relying Solely on Excel - Limited with large datasets - Hard to automate complex tasks - Learn SQL for data extraction - Try to use Python/R for advanced analysis 3. Overcomplicating Visualizations - Too many colors and chart types - Confuses the end-user - Keep it simple and clean - Use the right chart for the right data 4. Ignoring the "Why" (Business Context) - Reporting numbers without meaning - Analysis doesn't solve a problem - Understand business goals first - Focus on actionable insights 5. Poor SQL Habits - Using SELECT * on huge tables - Writing unreadable, messy queries - Use aliases and formatting - Filter data early with WHERE 6. Missing Outliers and Distributions - Only looking at the "Average" (Mean) - Outliers can skew your results - Check median and standard deviation - Visualize distributions with histograms 7. No Documentation or Comments - Hard to reproduce your work - You’ll forget your logic in a month - Document your data sources - Comment your code and SQL scripts 8. Correlation vs. Causation - Assuming $A$ caused $B$ just because they moved together - Leads to false business advice - Look for underlying factors - Use A/B testing where possible 9. Not Validating Results - Trusting the output blindly - Logic errors in formulas/queries - Cross-check totals with raw data - Peer-review your findings 10. Poor Communication Skills - Great analysis, but poor presentation - Getting too technical with stakeholders - Tell a story with your data - Focus on the "So What?" for the audience

New in the Power BI March 2026 Update ✌🏻 Set the default page size directly in themes Have you tried it already? Follow for more Power BI news ✅ #powerbi #update #new #setpage #analytics

New! Customize total calculations in Power BI 🙌🏻 March 2026 Update Follow for more Power BI news ✅ #powerbi #report #canvas

This is where things got exciting. Raw data is useful, but visuals? That's where you see the real story. What I Added: Breakdown Table A dynamic summary table that automatically calculates: Total Income (MTD) Total Expenses (by category: Needs, Wants, Savings) Remaining Budget per category Percentage spent Visual Overview Progress bars using bar charts, they fill up as spending increases For Wants & Need .. Donut chart for Savings (work in progress) 3. Smart Alerts When spending hits 80% of a category budget → cell turns yellow When spending hits 100% →cell turns red with a warning message The Formula Behind It: excel =SUMIFS(Expense_Amount, Expense_Category, "Needs", Expense_Date, ">="&EOMONTH(TODAY(),-1)+1) This sums only this month's "Needs" expenses — clean and dynamic. What's Working Well Speed: Data entry takes seconds now Clarity – I can see at a glance if I'm overspending on Wants (spoiler: I am) Motivation – Watching the Savings bar grow is actually addictive No surprises – The alerts mean I adjust before I break the budget I'm planning to add: Monthly comparison reports (January vs. February) Goal trackers This project started as a simple tracker. But with each test, the mini calendar, the breakdown table, the visuals, it's becoming something I actually want to use. And when you enjoy using your budget tool? You stick with it. And when you stick with it? Your money starts behaving. Always building. Always improving. Tool: @msexcel #Excel #BudgetTracker #PersonalFinance #VBA #DataVisualization #Productivity

Are you in Lagos,Ibadan,Ekiti, Ilorin? Join us this Saturday as we celebrate #worldwaterday to clean up a water body #Volunteers #sdg6 #cleanwaterandsanitation @ossap_sdgs

You exit abi them beat you comot for Champions league? @ChelseaFC

Senegal is our African champion 🇸🇳