📊 Ask About Analytics! Every Wednesday, I answer your questions about analytics! From career growth to tools and mindset. Think of it as your weekly boost to think, analyze, and communicate like a pro 👨🏻‍💻 🎯 Today’s question: “How to make the best CV as a junior data analyst?” The secret? Show, don’t tell. Recruiters remember outcomes, not buzzwords 💼 💬 Drop your question for next week’s episode below! 👀 Follow @loresowhat for more weekly analytics insights. #AskAboutAnalytics #DataAnaly
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📊 Ask About Analytics! Every Wednesday, I answer your questions about analytics! From career growth to tools and mindset. Think of it as your weekly boost to think, analyze, and communicate like a pro 👨🏻‍💻 🎯 Today’s question: “How to make the best CV as a junior data analyst?” The secret? Show, don’t tell. Recruiters remember outcomes, not buzzwords 💼 💬 Drop your question for next week’s episode below! 👀 Follow @loresowhat for more weekly analytics insights. #AskAboutAnalytics #DataAnaly
699 views4 months ago
TikTokloresowhat
🧹 Tired of messy customer data ruining your analysis? Here’s how to build a complete data cleaning pipeline in SQL that transforms chaos into crystal-clear insights! 💡 Example: You have customer records with mixed case names, inconsistent phone formats, duplicate emails, and missing values. Instead of manual cleanup, use SQL to automate the entire process and get analysis-ready data in minutes. Stop wasting hours on manual data cleanup. Build this pipeline once and transform any messy dataset
1:42
🧹 Tired of messy customer data ruining your analysis? Here’s how to build a complete data cleaning pipeline in SQL that transforms chaos into crystal-clear insights! 💡 Example: You have customer records with mixed case names, inconsistent phone formats, duplicate emails, and missing values. Instead of manual cleanup, use SQL to automate the entire process and get analysis-ready data in minutes. Stop wasting hours on manual data cleanup. Build this pipeline once and transform any messy dataset
5.3K views2 months ago
TikTokloresowhat
Master Data Grouping in SQL, Tableau, and Python
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Master Data Grouping in SQL, Tableau, and Python
4.1K views3 months ago
TikTokloresowhat
Sistema de Organización para Buscar Empleo Eficaz
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Sistema de Organización para Buscar Empleo Eficaz
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TikTokloresowhat
I built a custom data analyst in under 5 minutes and it replaced hours of dashboard work 📊 No SQL. No Tableau. No technical experience needed. Here's what Thesys Agent Builder actually does: Upload a CSV or connect your database. It auto detects your schema. Ask plain language questions and get real interactive charts. Compare periods, dig deeper, all in one chat. Turn the entire conversation into presentation ready slides in one click. Share the live agent directly with your team. Most AI tool
1:16
I built a custom data analyst in under 5 minutes and it replaced hours of dashboard work 📊 No SQL. No Tableau. No technical experience needed. Here's what Thesys Agent Builder actually does: Upload a CSV or connect your database. It auto detects your schema. Ask plain language questions and get real interactive charts. Compare periods, dig deeper, all in one chat. Turn the entire conversation into presentation ready slides in one click. Share the live agent directly with your team. Most AI tool
710 views3 weeks ago
TikTokloresowhat
The way you're cleaning messy text data in Python is probably wrong 📊 Most analysts chain replace methods to clean phone numbers. It works until a new format appears and everything breaks. Here's the one line fix that handles infinite variations: Junior approach: chain multiple replace methods (fragile, breaks constantly). Senior approach: regex with \\D (non digit pattern). One line of logic that says
0:48
The way you're cleaning messy text data in Python is probably wrong 📊 Most analysts chain replace methods to clean phone numbers. It works until a new format appears and everything breaks. Here's the one line fix that handles infinite variations: Junior approach: chain multiple replace methods (fragile, breaks constantly). Senior approach: regex with \\D (non digit pattern). One line of logic that says
934 views2 weeks ago
TikTokloresowhat
Combine Multiple Datasets in SQL, Tableau & Python
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Combine Multiple Datasets in SQL, Tableau & Python
4.5K views6 months ago
TikTokloresowhat
I challenge you to commit to Data Analytics for 30 days in 2026
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I challenge you to commit to Data Analytics for 30 days in 2026
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2027 in Data Analytics | Here Are 4 Trends to Watch For
20:56
2027 in Data Analytics | Here Are 4 Trends to Watch For
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YouTubeLore So What
3 Levels of SQL AND How To Achieve Them (2026 Edition)
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3 Levels of SQL AND How To Achieve Them (2026 Edition)
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The REALITY of Data Jobs in 2026
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The REALITY of Data Jobs in 2026
4.1K views1 month ago
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Watch me Cleaning Data in minutes with SQL
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Watch me Cleaning Data in minutes with SQL
6.5K views2 weeks ago
YouTubeLore So What
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "🚀 Want to compare date differences fast? One powerful concept every data analyst should know - DATEDIFF! ⏳ 💡 Example: You have a start and end date. Instead of manually counting days, use DATEDIFF to instantly calculate the time between them - whether in SQL, Tableau, or Python. ✅ Perfect for tracking project timelines, customer churn, delivery delays, and more - across any tool you use! Think in date differences, not just dates - an
1:11
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "🚀 Want to compare date differences fast? One powerful concept every data analyst should know - DATEDIFF! ⏳ 💡 Example: You have a start and end date. Instead of manually counting days, use DATEDIFF to instantly calculate the time between them - whether in SQL, Tableau, or Python. ✅ Perfect for tracking project timelines, customer churn, delivery delays, and more - across any tool you use! Think in date differences, not just dates - an
7.2K views5 months ago
Instagramloresowhat
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "This SQL project is what actually gets you past the resume screen 💼 Stop doing toy tutorials. Here’s the end to end dashboard recruiters want to see: Revenue metrics (total, AOV, orders). Growth analysis (MoM, YoY for revenue and customers). Regional performance breakdown. Sales rep rankings by conversion and deal size. Product category analysis with profit margins. Executive summary with variance analysis. This proves y
1:28
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "This SQL project is what actually gets you past the resume screen 💼 Stop doing toy tutorials. Here’s the end to end dashboard recruiters want to see: Revenue metrics (total, AOV, orders). Growth analysis (MoM, YoY for revenue and customers). Regional performance breakdown. Sales rep rankings by conversion and deal size. Product category analysis with profit margins. Executive summary with variance analysis. This proves y
3.4K views1 month ago
Instagramloresowhat
Lorenzo Rosa 🤌 Data Analytics & Data Science | 📊 Ask About Analytics! Every Wednesday, I answer your questions about analytics! From career growth to tools and mindset. Think of it as... | Instagram
1:44
Lorenzo Rosa 🤌 Data Analytics & Data Science | 📊 Ask About Analytics! Every Wednesday, I answer your questions about analytics! From career growth to tools and mindset. Think of it as... | Instagram
1.9K views4 months ago
Instagramloresowhat
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "📊 Want to uncover hidden patterns in your data? One of the most revealing techniques is calculating averages by group - it shows you what’s really happening beneath the surface! 💡 Example: You have employee salary data across departments. Instead of looking at one overall average, group by department to see which teams are paid above or below average - instant insights for HR decisions. ✅ This technique works in
1:05
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "📊 Want to uncover hidden patterns in your data? One of the most revealing techniques is calculating averages by group - it shows you what’s really happening beneath the surface! 💡 Example: You have employee salary data across departments. Instead of looking at one overall average, group by department to see which teams are paid above or below average - instant insights for HR decisions. ✅ This technique works in
3.9K views4 months ago
Instagramloresowhat
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "💬 Comment STATS and I’ll DM you the link to my new video! In this video, I’ll show you exactly how I use statistics as a Data Analyst! from understanding central tendency and variability to applying them in Excel for real business insights. We’ll go through concepts like mean, median, mode, variance, and standard deviation, without the confusion, just the parts that actually matter for your data career. Save this if you’re ready to ma
0:54
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "💬 Comment STATS and I’ll DM you the link to my new video! In this video, I’ll show you exactly how I use statistics as a Data Analyst! from understanding central tendency and variability to applying them in Excel for real business insights. We’ll go through concepts like mean, median, mode, variance, and standard deviation, without the confusion, just the parts that actually matter for your data career. Save this if you’re ready to ma
5.1K views4 months ago
Instagramloresowhat
Lorlo on Instagram: "Last night was a movie of sorts..."
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Lorlo on Instagram: "Last night was a movie of sorts..."
118.7K views3 months ago
Instagramitslorlo
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "🚨 Most people mess up this interview question… Don’t be one of them! But first, send this to yourself so you can revisit it later ✅ Here’s what NOT to say (these answers instantly raise red flags): ❌ “I’ll just tell my manager.” → Too dependent. Shows you can’t handle conflict on your own. ❌ “I’ll ignore it and do my job.” → Makes you sound detached from teamwork. ❌ “I’ll convince them to cooperate.” → Sounds nice, but too vague, no c
0:09
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "🚨 Most people mess up this interview question… Don’t be one of them! But first, send this to yourself so you can revisit it later ✅ Here’s what NOT to say (these answers instantly raise red flags): ❌ “I’ll just tell my manager.” → Too dependent. Shows you can’t handle conflict on your own. ❌ “I’ll ignore it and do my job.” → Makes you sound detached from teamwork. ❌ “I’ll convince them to cooperate.” → Sounds nice, but too vague, no c
6.9K views5 months ago
Instagramloresowhat
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "Dating world explained by data science and machine learning 👀"
2:58
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "Dating world explained by data science and machine learning 👀"
4.9K views4 months ago
Instagramloresowhat
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "How to calculate Year-over-Year Growth % in SQL, Tableau & Python If you’re trying to break into data — this is one of those fundamental skills you NEED to know. Why? Because businesses run on growth metrics. If you can measure YoY growth, you can tell a story about whether a company is winning or losing. ✅ In SQL → Use LAG() to compare current vs previous year ✅ In Tableau → Quick Table Calculation does the heavy lifting ✅ In Python →
2:02
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "How to calculate Year-over-Year Growth % in SQL, Tableau & Python If you’re trying to break into data — this is one of those fundamental skills you NEED to know. Why? Because businesses run on growth metrics. If you can measure YoY growth, you can tell a story about whether a company is winning or losing. ✅ In SQL → Use LAG() to compare current vs previous year ✅ In Tableau → Quick Table Calculation does the heavy lifting ✅ In Python →
109.5K views6 months ago
Instagramloresowhat
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "Stop learning Python syntax and start solving actual business problems 📊 Most people can write code but freeze when asked to analyze a real sales funnel. Here’s the framework that changed everything for me: Define funnel stages. Count unique users from page view to checkout. Calculate conversion rates between stages. Find where the biggest drop offs happen. Analyze by traffic source. Which channels bring quality traffic that actually
1:25
Lorenzo Rosa 🤌 Data Analytics & Data Science on Instagram: "Stop learning Python syntax and start solving actual business problems 📊 Most people can write code but freeze when asked to analyze a real sales funnel. Here’s the framework that changed everything for me: Define funnel stages. Count unique users from page view to checkout. Calculate conversion rates between stages. Find where the biggest drop offs happen. Analyze by traffic source. Which channels bring quality traffic that actually
8.7K views1 month ago
Instagramloresowhat
Check my bio for course links 💡 Discover more on my YouTube channel, @loresowhat, and watch a full video about these courses 🎥 ⠀ ⠀ #datascience #careerchange #data #datascientist #dataanalytics #dataanalysis #dataanalyst #newcareer #datasciencetraining #datascientists #datasciencejobs #datasciencelearning #datavisualisation #sqltips
Check my bio for course links 💡 Discover more on my YouTube channel, @loresowhat, and watch a full video about these courses 🎥 ⠀ ⠀ #datascience #careerchange #data #datascientist #dataanalytics #dataanalysis #dataanalyst #newcareer #datasciencetraining #datascientists #datasciencejobs #datasciencelearning #datavisualisation #sqltips
24.6K viewsFeb 1, 2023
TikTokloresowhat
Transforma tus datos con dbt: una guía para 2025
Transforma tus datos con dbt: una guía para 2025
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TikTokloresowhat
Build THE PERFECT Data Analyst CV
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Build THE PERFECT Data Analyst CV
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The Data Analytics Portfolio that ACTUALLY Works
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The Data Analytics Portfolio that ACTUALLY Works
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PRACTICAL Data Analytics with SQL
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PRACTICAL Data Analytics with SQL
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Python Interactive Dashboard STEP BY STEP
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Python Interactive Dashboard STEP BY STEP
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Data Cleaning fundamentals pt. 1
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Data Cleaning fundamentals pt. 1
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Data Cleaning fundamentals pt. 4
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Data Cleaning fundamentals pt. 4
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