Data Analytics & AI | SQL Interviews | Power BI Resources
🔓Explore the fascinating world of Data Analytics & Artificial Intelligence 💻 Best AI tools, free resources, and expert advice to land your dream tech job. Admin: @coderfun Buy ads: https://telega.io/c/Data_Visual
Mostrar más📈 Análisis del canal de Telegram Data Analytics & AI | SQL Interviews | Power BI Resources
El canal Data Analytics & AI | SQL Interviews | Power BI Resources (@data_visual) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 27 283 suscriptores, ocupando la posición 7 207 en la categoría Educación y el puesto 15 291 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 27 283 suscriptores.
Según los últimos datos del 21 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 75, y en las últimas 24 horas de 18, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.22%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.54% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 605 visualizaciones. En el primer día suele acumular 146 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 2.
- Intereses temáticos: El contenido se centra en temas clave como |--, sql, learning, analytic, visualization.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“🔓Explore the fascinating world of Data Analytics & Artificial Intelligence
💻 Best AI tools, free resources, and expert advice to land your dream tech job.
Admin: @coderfun
Buy ads: https://telega.io/c/Data_Visual”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 22 julio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.
Carga de datos en curso...
| Fecha | Crecimiento de Suscriptores | Menciones | Canales | |
| 22 julio | +3 | |||
| 21 julio | +18 | |||
| 20 julio | +11 | |||
| 19 julio | +13 | |||
| 18 julio | +7 | |||
| 17 julio | +8 | |||
| 16 julio | +9 | |||
| 15 julio | +12 | |||
| 14 julio | +2 | |||
| 13 julio | +1 | |||
| 12 julio | +3 | |||
| 11 julio | 0 | |||
| 10 julio | 0 | |||
| 09 julio | +8 | |||
| 08 julio | +9 | |||
| 07 julio | 0 | |||
| 06 julio | +12 | |||
| 05 julio | +4 | |||
| 04 julio | +13 | |||
| 03 julio | 0 | |||
| 02 julio | +8 | |||
| 01 julio | +4 |
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| 2 | 5 resources to learn Claude AI for free 👇
1/ Anthropic's Official Guide:
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5/ FreeAcademy's Guide:
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| 3 | Quick Excel Cheatsheet! 📊
Basic Formulas
1. Add: =A1+B1
2. Subtract: =A1-B1
3. Multiply: =A1*B1
4. Divide: =A1/B1
5. Average: =AVERAGE(A1:A10)
6. Sum: =SUM(A1:A10)
Logical Functions
1. IF: =IF(A1>10, "Yes", "No")
2. AND: =AND(A1>5, B1<10)
3. OR: =OR(A1=1, B1=2)
4. EXACT (case-sensitive match): =EXACT(A1, B1)
Lookup Functions
1. VLOOKUP: =VLOOKUP(A1, Table, 2, FALSE)
2. HLOOKUP: =HLOOKUP(A1, Table, 2, FALSE)
3. XLOOKUP: =XLOOKUP(A1, Range1, Range2)
Counting Data Types
1. Count numbers: =COUNT(A1:A10)
2. Count non-empty: =COUNTA(A1:A10)
3. Count blanks: =COUNTBLANK(A1:A10)
4. Is number: =ISNUMBER(A1)
5. Is text: =ISTEXT(A1)
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| 4 | ✅ Data Analytics Roadmap for Freshers 🚀📊
1️⃣ Understand What a Data Analyst Does
🔍 Analyze data, find insights, create dashboards, support business decisions.
2️⃣ Start with Excel
📈 Learn:
– Basic formulas
– Charts & Pivot Tables
– Data cleaning
💡 Excel is still the #1 tool in many companies.
3️⃣ Learn SQL
🧩 SQL helps you pull and analyze data from databases.
Start with:
– SELECT, WHERE, JOIN, GROUP BY
🛠️ Practice on platforms like W3Schools or Mode Analytics.
4️⃣ Pick a Programming Language
🐍 Start with Python (easier) or R
– Learn pandas, matplotlib, numpy
– Do small projects (e.g. analyze sales data)
5️⃣ Data Visualization Tools
📊 Learn:
– Power BI or Tableau
– Build simple dashboards
💡 Start with free versions or YouTube tutorials.
6️⃣ Practice with Real Data
🔍 Use sites like Kaggle or Data.gov
– Clean, analyze, visualize
– Try small case studies (sales report, customer trends)
7️⃣ Create a Portfolio
💻 Share projects on:
– GitHub
– Notion or a simple website
📌 Add visuals + brief explanations of your insights.
8️⃣ Improve Soft Skills
🗣️ Focus on:
– Presenting data in simple words
– Asking good questions
– Thinking critically about patterns
9️⃣ Certifications to Stand Out
🎓 Try:
– Google Data Analytics (Coursera)
– IBM Data Analyst
– LinkedIn Learning basics
🔟 Apply for Internships & Entry Jobs
🎯 Titles to look for:
– Data Analyst (Intern)
– Junior Analyst
– Business Analyst
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| 5 | 🤖 𝗛𝗢𝗪 𝗧𝗢 𝗙𝗜𝗫 𝗣𝗥𝗢𝗠𝗣𝗧 𝗪𝗜𝗧𝗛 𝗠𝗘𝗧𝗔 𝗣𝗥𝗢𝗠𝗣𝗧𝗜𝗡𝗚:
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| 6 | If you’re just starting out in Data Analytics, it’s super important to build the right habits early.
Here’s a simple plan for beginners to grow both technical and problem-solving skills together:
If You Just Started Learning Data Analytics, Focus on These 5 Baby Steps:
1. Don’t Just Watch Tutorials — Build Small Projects
After learning a new tool (like SQL or Excel), create mini-projects:
- Analyze your expenses
- Explore a free dataset (like Netflix movies, COVID data)
2. Ask Business-Like Questions Early
Whenever you see a dataset, practice asking:
- What problem could this data solve?
- Who would care about this insight?
3. Start a ‘Data Journal’
Every day, note down:
- What you learned
- One business question you could answer with data (Helps you build real-world thinking!)
4. Practice the Basics 100x
Get very comfortable with:
- SELECT, WHERE, GROUP BY (SQL)
- Pivot tables and charts (Excel)
- Basic cleaning (Power Query / Python pandas)
_Mastering basics > learning 50 fancy functions._
5. Learn to Communicate Early
Explain your mini-projects like this:
- What was the business goal?
- What did you find?
- What should someone do based on it?
React with ❤️ if you need a beginner-friendly roadmap to start your data analytics career
Data Analytics Free Resources: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02
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