现已上线！2025 年 Telegram 研究 — 年度关键洞察 
Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources
前往频道在 Telegram
Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun
显示更多📈 Telegram 频道 Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources 的分析概览
频道 Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources (@learndataanalysis) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 51 872 名订阅者，在 教育 类别中位列第 3 348，并在 印度 地区排名第 7 164 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 51 872 名订阅者。
根据 18 六月, 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 499，过去 24 小时变化为 6，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 5.83%。内容发布后 24 小时内通常能获得 1.17% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 3 025 次浏览，首日通常累积 609 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 6。
- 主题关注点： 内容集中在 analyst, |--, excel, visualization, analytic 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：
“Data Analysis Useful Resources
#dataanalysis
#dataanalysisbooks
#sqlbooks
#pythonbooks
#tableau
#powerbi
#datavisualization
For promotions: @coderfun”
凭借高频更新（最新数据采集于 19 六月, 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。
51 872
订阅者
+624 小时
+1097 天
+49930 天
帖子存档
applied_statistics.pdf4.53 MB
sql-performance-explained_compress.pdf1.17 MB
Where are you from?
oracle_database_problem_solving_and_troubleshooting_handbook.azw331.81 MB
Interview questions asked by top product-based companies.
https://t.me/Curiousprogrammer/130
Demystifying the way to learn Data Visualization.pdf20.30 MB
Business Intelligence Career Master Plan (2023).pdf16.38 MB
Leveling Up with SQL.pdf41.73 MB
Pandas in 8 Pages.pdf8.28 KB
Hands-On Data Science and Python Machine Learning
Frank Kane, 2017
Top 15 advanced Power BI interview question
👇👇
https://t.me/sqlspecialist/422
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ML_cheatsheets.pdf6.49 MB
Introduction to SQL.pdf6.36 KB
Fundamentals of Data Observability (2023).pdf7.97 MB
Learning Professional Python - Volume 1.pdf3.88 MB
Data science cheatsheet
Data Analysis with Excel
👇👇
https://t.me/excel_analyst/2
Power BI DAX Functions
👇👇
https://t.me/PowerBI_analyst/2
All about SQL
👇👇
https://t.me/sqlanalyst/29
Python for data analysis
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https://t.me/pythonanalyst/26
Statistics Book and other useful resources
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https://t.me/DataAnalystInterview/34
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