Elvis | Analytics📊

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Elvis | Analytics📊

Elvis | Analytics📊

@TheeAnalyst_ke

SQL | Python | Excel | Power Bi | Tech Enthusiast. | lessons & Insights Daily

Beigetreten Mayıs 2026
21 Folgt42 Follower
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Elvis | Analytics📊
Elvis | Analytics📊@TheeAnalyst_ke·
Maths + Computer Science student who fell in love with data 📊 Now turning that into a career in Data Analytics Here I share: 📊 Data tips & tricks 🛠️ Tools — SQL, Python, Power BI 🚀 My journey from student to analyst If you're into data or just starting out -let's connect 👇
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Thelma Etuk
Thelma Etuk@officialladi_T·
Every data analyst's journey started from here. right? 😅
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Elvis | Analytics📊
Elvis | Analytics📊@TheeAnalyst_ke·
SQL Tip 🐘🐬 Learning SQL? CASE WHEN is one of those features you'll use again and again. How to use it: ✅ Inside the SELECT statement ✅ Give the result an alias using AS ✅ Add one or more WHEN conditions ✅ Finish with END Small features make better queries.
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Dorcas🦋|UI/UX Designer
Dorcas🦋|UI/UX Designer@DorcasOyesun·
Guys 🥹 You people will type congratulations o 😭, I'm coming first
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Shravani
Shravani@Shra_va_ni·
met someone today who built a full app in a weekend and couldn't tell me what a API does
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Dark Coder
Dark Coder@dark_coderz·
I haven't seen a C++ vibecoder yet. I wonder why?
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Annie🦋
Annie🦋@DabereNnamani·
Which measure is least affected by extreme values? A. Mean B. Median C. Range D. Sum
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Kinghamzy🪙
Kinghamzy🪙@kinghamzy·
Day 3 of my Data Analytics journey No new topics today. Instead, I practiced everything I learned using a retail sales dataset. While using TRANSPOSE(), I kept getting an error and thought my formula was wrong. Turns out... my formula was correct.
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vivian
vivian@vheeorji22·
Can someone tell me how the fuck people are making so much money from Pinterest?
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Tech P
Tech P@Tech_p001·
What is the best advice you can give to someone learning Data engineering??
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Dera | Power BI Developer 💛✨
One underrated career habit Reply to people. Congratulate them. Ask thoughtful questions. Share opportunities. Networking isn’t collecting followers. It’s building relationships.
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Elvis | Analytics📊
Elvis | Analytics📊@TheeAnalyst_ke·
Day 4🚀 A single bug almost made me skip today,😅 Today's progress ✅ Improved the overall layout ✅ Made key fraud trends, the main focus ✅ Cleaned up the UI for better readability ✅ Fixed bugs and refined the experience ⛏️Python, streamlit Next up: Interactive Filters
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Timilehin | Excel Automation Specialist
📌 PART 1 : How Data Analysts Collect Company Data (Beginner-Friendly Guide) Lately I’ve been talking to a lot of new analysts who feel confused about what to actually do when a company says: “Help us analyze our data.” I’ve been there, unsure of where to start, what questions to ask, or how real analysts collect business data. So today, I want to break it down in the simplest way possible. If you’re a beginner, read this carefully and save it. 1️⃣ Start With a Requirements Discovery Call Before touching Excel, SQL, or Power BI, your first job is to understand the business, not the dataset. Ask the company questions around: Business Goals • What problem are we solving? • What decisions will this analysis improve? • What does success look like? Data Needs • What data sources exist? • Where is the data stored (Excel, SQL, CRM, POS)? • What time period should be analyzed? Output Expectations • Dashboard, report, or cleaned dataset? • Which KPIs matter the most? • Should the report update weekly or monthly? Access & Security • Will you need login access? • Any sensitive columns to anonymize? This is how professionals avoid confusion and build trust early. 2️⃣ Ask for the Right Data Files Depending on the industry, request the correct tables: Retail / E-commerce Orders, Customers, Products, Inventory, Returns. Finance Transactions, Ledger, Forecasts, Budgets. Healthcare Appointments, Billing, Encounters, Lab results. HR Employees, Payroll, Hiring funnel, Performance. Always request the files in Excel or CSV, with proper column names. And ask for a data dictionary, it explains what each column means. 👉 If this helped you, watch out for Part 2 where I’ll break down cleaning, analyzing, and delivering insights like a pro.
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Elvis | Analytics📊
Elvis | Analytics📊@TheeAnalyst_ke·
Take this scenario: A telecom company has seen a sharp increase in customers switching to competitors. You're the data analyst. Before touching SQL or Excel, what questions would you ask?
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Elvis | Analytics📊
Elvis | Analytics📊@TheeAnalyst_ke·
You can write perfect SQL queries and build beautiful dashboards. But if you're solving the wrong problem, none of it matters. Business understanding comes first.
Timilehin | Excel Automation Specialist@Timsedx

📌 PART 1 : How Data Analysts Collect Company Data (Beginner-Friendly Guide) Lately I’ve been talking to a lot of new analysts who feel confused about what to actually do when a company says: “Help us analyze our data.” I’ve been there, unsure of where to start, what questions to ask, or how real analysts collect business data. So today, I want to break it down in the simplest way possible. If you’re a beginner, read this carefully and save it. 1️⃣ Start With a Requirements Discovery Call Before touching Excel, SQL, or Power BI, your first job is to understand the business, not the dataset. Ask the company questions around: Business Goals • What problem are we solving? • What decisions will this analysis improve? • What does success look like? Data Needs • What data sources exist? • Where is the data stored (Excel, SQL, CRM, POS)? • What time period should be analyzed? Output Expectations • Dashboard, report, or cleaned dataset? • Which KPIs matter the most? • Should the report update weekly or monthly? Access & Security • Will you need login access? • Any sensitive columns to anonymize? This is how professionals avoid confusion and build trust early. 2️⃣ Ask for the Right Data Files Depending on the industry, request the correct tables: Retail / E-commerce Orders, Customers, Products, Inventory, Returns. Finance Transactions, Ledger, Forecasts, Budgets. Healthcare Appointments, Billing, Encounters, Lab results. HR Employees, Payroll, Hiring funnel, Performance. Always request the files in Excel or CSV, with proper column names. And ask for a data dictionary, it explains what each column means. 👉 If this helped you, watch out for Part 2 where I’ll break down cleaning, analyzing, and delivering insights like a pro.

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Elvis | Analytics📊
Elvis | Analytics📊@TheeAnalyst_ke·
New month. New goals. Same mindset: consistency over perfection. 🎯 June was about Python and SQL projects. This month, I'm focused on Excel and Power BI—mastering data modeling, advanced DAX, and dashboard storytelling. Half of 2026 is here. What are you learning this month?
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