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
显示更多📈 Telegram 频道 Data Analytics & AI | SQL Interviews | Power BI Resources 的分析概览
频道 Data Analytics & AI | SQL Interviews | Power BI Resources (@data_visual) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 27 283 名订阅者,在 教育 类别中位列第 7 207,并在 印度 地区排名第 15 291 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 27 283 名订阅者。
根据 21 七月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 75,过去 24 小时变化为 18,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 2.22%。内容发布后 24 小时内通常能获得 0.54% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 605 次浏览,首日通常累积 146 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 2。
- 主题关注点: 内容集中在 |--, sql, learning, analytic, visualization 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“🔓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”
凭借高频更新(最新数据采集于 22 七月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 教育 类别中的关键影响点。
数据加载中...
| 日期 | 订阅者增长 | 提及 | 频道 | |
| 22 七月 | +3 | |||
| 21 七月 | +18 | |||
| 20 七月 | +11 | |||
| 19 七月 | +13 | |||
| 18 七月 | +7 | |||
| 17 七月 | +8 | |||
| 16 七月 | +9 | |||
| 15 七月 | +12 | |||
| 14 七月 | +2 | |||
| 13 七月 | +1 | |||
| 12 七月 | +3 | |||
| 11 七月 | 0 | |||
| 10 七月 | 0 | |||
| 09 七月 | +8 | |||
| 08 七月 | +9 | |||
| 07 七月 | 0 | |||
| 06 七月 | +12 | |||
| 05 七月 | +4 | |||
| 04 七月 | +13 | |||
| 03 七月 | 0 | |||
| 02 七月 | +8 | |||
| 01 七月 | +4 |
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1/ Anthropic's Official Guide:
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2/ Great Learning's Free Course:
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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)
React ❤️ for more | 1 213 |
| 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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| 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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