Transforming Numbers into Narratives | Passionate About Data & Visualization

Joined May 2011
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๐Ÿš€ Return to Space - my submission for the #mavenreturntospacechallenge ๐ŸŒŒ Visualizing 65 years of human exploration (1957โ€“2022) Link: public.tableau.com/app/profiโ€ฆ #DataViz #Tableau #DataStorytelling
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๐Ÿšจ My submission to the #dataDNA September Challenge ๐Ÿšจ Credit Risk Analysis at Nova Bank ๐Ÿ’ณ Built with Tableau ๐Ÿ“Š 3 dashboard pages: * Risk Profile * Loan Performance * Borrower Drilldown ๐Ÿ”— Explore here: public.tableau.com/app/profiโ€ฆ
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Obi Chinyere Mayree ๐Ÿ“Š | retweeted
I created my LinkedIn 40 weeks ago. Easiest algorithm to crack by a country mile. I have since added $70,000 to my agency pipeline, generated five figures this month for SEO Stuff, built 7,400 connections, logged 1,720,745 impressions, and reached 535,761 members. Use my system before they close the loopholes. And if you want my full cheat sheet including updated engagement group templates, carousel strategy, and DM workflows: Follow me Repost this Comment โ€œX LinkedIn growth guideโ€ You must do all 3 to get the DM. What is working now for audience growth: LinkedIn rewards original insights, depth, and conversation. The fastest-growing accounts right now are doing these things consistently: Proof Perspective, since people want numbers and your take. Basically dashboard screenshots, Stripe receipts, client results followed by โ€œhereโ€™s what I learned.โ€ Story-first content, which are basically posts that tell a quick story. Even a small win or failure outperform generic how-tos. Also, don't sleep on comment-first growth. The easiest way to grow your audience fast is to be seen in other peopleโ€™s comments daily. Thoughtful comments can outperform posts for reach when done consistently. Also, try to prompt conversation. Posts that create back-and-forth replies inside the comments get shown for 2โ€“3 extra days. Ask real questions and reply to every comment to keep the discussion alive. Network overlap is key to. If your content keeps getting engagement from two or three adjacent niches, LinkedIn starts showing you to those networks more often. Consistency is key, by the way. Three posts a day, every day, is better than six posts one day and silence the next. My posting routine: I post 3 times per day, 7 days a week, unless I'm traveling. (And when I travel my stats plummet). Morning: Text post with POV, story, or market insight Afternoon: Carousel, proof post, or annotated screenshot Evening: Mini-thread, framework, or quick win Even 2 days off posting cuts impressions and inbound leads by half. (I learn this the hard way every month.) Best-performing formats right now: Carousels Slide 1: bold headline tied to a pain point or result Slides 2โ€“5: numbered steps, bullets, or annotated visuals Final slide: CTA (โ€œDrop guide below if you want the SOPโ€) Carousels with a mix of text and screenshots are outperforming plain text slides by 30โ€“40%. Short videos Under 60 seconds Hook hard in the first 3 seconds Use subtitles with a strong first line (auto-previews drive clicks) Show processes, dashboards, or quick wins over overly polished production Text posts Hook with a question or bold claim 1โ€“2 lines per paragraph for scannability 3โ€“5 bullet takeaways perform better than walls of text End with a question that invites others to share their experience Proof breakdown posts Share a result Explain how it happened in 3โ€“4 short bullets Turn your metrics into a mini-case study Conversation-first posts Ask a real question, share a controversial POV, or open a loop that invites debate Formats that kind of suck right now: Generic AI-written content with no voice Metrics-only posts with no โ€œhowโ€ Text walls with no whitespace Links in the post body Timing sweet spots: 7โ€“8 AM for thought-leadership or text-heavy posts 1โ€“3 PM for maximum reach Sunday evening for outsized visibility with less competition Tuesday and Thursday for CTA or lead-gen posts Engagement strategy for building a strong audience: Comment on 20 posts/day with insight or examples (not just โ€œgreat postโ€) Like 50 posts/day, focusing on people who engage with your content Reply to every comment within the first hour, this drives early velocity Repost your best-performing posts every 5โ€“7 days with a fresh angle DM 5โ€“10 new people daily with context tied to what they just posted LinkedIn is now weighting comment threads and returning commenters more heavily. Encourage dialogue between commenters and follow up with people who engaged last time, repeat engagement makes your reach grow week over week. Hooks converting right now: โ€œI started this account 40 weeks ago. Hereโ€™s the exact revenue it has generated.โ€ โ€œ$10K this month from LinkedIn posts. Hereโ€™s the breakdown.โ€ โ€œThis 7-slide carousel booked 3 calls in 24 hours. Slide 1 below.โ€ โ€œIf I had to rebuild my LinkedIn from scratch in 2025, hereโ€™s what I would do.โ€ โ€œThe 3-post-per-day system I use to consistently generate inbound leads.โ€ Always pair with screenshots, receipts, or analytics for credibility. 30-day checklist for building a strong audience: Post 3x/day Comment on 20 posts/day with substance Like 50 posts/day Reply to every comment in the first hour Repost your top performers weekly DM 5โ€“10 people/day with value-first context Track impressions, replies, inbound leads, and comment thread depth weekly LinkedIn is still the most underpriced attention engine in 2025. Run this playbook for 30 days. Screenshot your Day 31 results. Tag me when the inbound starts. And if you want the full cheat sheet with engagement group templates, carousel strategy, and DM workflows: Follow me Repost this Comment โ€œX LinkedIn growth guideโ€ You must do all 3 for the DM.
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๐Ÿ”Data Insight Monday: When to Keep vs. Delete Missing Data ๐Ÿ’ฐThe $50K Missing Data Decision Ever faced this? โ†’ 30% missing values in your dataset. I did recently while analyzing customer satisfaction. ๐Ÿ‘‰Delete? Impute? The wrong call could have completely skewed my analysis
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๐Ÿ“Š My Outcome? I kept the missing satisfaction data, coded it as โ€œno opinionโ€, and discovered: โžก๏ธ 60% of these customers became our highest spenders. If I had deleted them, Iโ€™d have missed this goldmine insight.
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โœจTakeaway: Missing data isnโ€™t always a problem. Sometimes, itโ€™s the answer youโ€™re looking for. ๐Ÿ‘‰ Over to you: When you hit significant missing data; do you delete or keep & impute? #DataInsightMonday #DataAnalysis #Python #DataScience #Analytics #MotivationMonday
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๐Ÿšจ New Project: I recreated a dashboard design from @HowToPowerBI using simulated data. Marketing Campaign Dashboard | Python Data Viz ๐Ÿ“Š ๐Ÿ”— Explore Dashboard here: public.tableau.com/app/profiโ€ฆ #DataAnalytics #DashboardDesign
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It covers records from 2023โ€“2025 across 3 marketing channels. Highlights: - Tracked KPIs: Impressions, Spend, Conversion Rate, CTR, CPA. - Segmented performance by audience, creative variants, city, and device type. - Compared current vs. prior month trends .
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๐Ÿ” Data Insight Monday: Your First 10 Minutes with Clean Data Hi Datafam, Your data is finally clean. But whatโ€™s the FIRST thing you do before visualizing? Hereโ€™s my 10-min routine for quick insights:
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โœ… Step 4: Ask Business Questions (3 mins) โ€ข What's the trend over time? โ€ข Which segments perform differently? โ€ข Where are the biggest opportunities?
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The Result? In 10 minutes, I know if I'm looking at seasonal patterns, outliers, or data quality issues. Whatโ€™s your go-to step when exploring new data? Drop it below ๐Ÿ‘‡ #DataInsightMonday #DataAnalysis #Python #DataScience #Analytics #MotivationMonday
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๐Ÿ” Data Insight Monday: From messing to Analysis-Ready in Minutes Last week: Why data cleaning takes 80% of my time. This week: HOW I clean data fast using Python Pandasโฌ‡๏ธ
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More toolkit lines: * df.drop(columns=[โ€˜nameโ€™]) โ€” Remove unnecessary columns * df[โ€˜colโ€™].replace({โ€˜oldโ€™: โ€˜newโ€™}) โ€”Fix inconsistent values * df.rename(columns={โ€˜oldโ€™: โ€˜newโ€™}) โ€”Standardize naming
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Wrap-up: These 7 lines can turn hours of manual cleaning into seconds of automation. Whatโ€™s you go to cleaning tools? Python, SQL or Excel Drop your favorite trick below #DataInsightMonday #DataCleaning #DataAnalysis #Analytics
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