ch
Feedback

不要被骗子欺骗!Telemetrio 会找到并标记这些频道 👉 如果想查看标记,请订阅

Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources

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 53 299 名订阅者,在 教育 类别中位列第 3 305,并在 印度 地区排名第 6 431 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 53 299 名订阅者。

根据 04 十一月, 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 11,过去 24 小时变化为 -8,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 7.19%。内容发布后 24 小时内通常能获得 1.16% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 0 次浏览,首日通常累积 616 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 0。
  • 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 05 十一月, 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。

Buy Ad
53 299
订阅者
-824 小时
-127 天
+1130 天
帖子存档
Shared the resources 😄 Thanks for the amazing response

Complete Syllabus for Data Analytics interview: SQL: 1. Basic    - SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING    - Basic JOINS (INNER, LEFT, RIGHT, FULL)    - Creating and using simple databases and tables 2. Intermediate    - Aggregate functions (COUNT, SUM, AVG, MAX, MIN)    - Subqueries and nested queries - Common Table Expressions (WITH clause)    - CASE statements for conditional logic in queries 3. Advanced    - Advanced JOIN techniques (self-join, non-equi join)    - Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag)    - optimization with indexing    - Data manipulation (INSERT, UPDATE, DELETE) Python: 1. Basic    - Syntax, variables, data types (integers, floats, strings, booleans)    - Control structures (if-else, for and while loops)    - Basic data structures (lists, dictionaries, sets, tuples)    - Functions, lambda functions, error handling (try-except)    - Modules and packages 2. Pandas & Numpy    - Creating and manipulating DataFrames and Series    - Indexing, selecting, and filtering data    - Handling missing data (fillna, dropna)    - Data aggregation with groupby, summarizing data    - Merging, joining, and concatenating datasets 3. Basic Visualization    - Basic plotting with Matplotlib (line plots, bar plots, histograms)    - Visualization with Seaborn (scatter plots, box plots, pair plots)    - Customizing plots (sizes, labels, legends, color palettes)    - Introduction to interactive visualizations (e.g., Plotly) Excel: 1. Basic    - Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.)    - Introduction to charts and basic data visualization    - Data sorting and filtering    - Conditional formatting 2. Intermediate    - Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF)    - PivotTables and PivotCharts for summarizing data    - Data validation tools    - What-if analysis tools (Data Tables, Goal Seek) 3. Advanced    - Array formulas and advanced functions    - Data Model & Power Pivot - Advanced Filter - Slicers and Timelines in Pivot Tables    - Dynamic charts and interactive dashboards Power BI: 1. Data Modeling    - Importing data from various sources    - Creating and managing relationships between different datasets    - Data modeling basics (star schema, snowflake schema) 2. Data Transformation    - Using Power Query for data cleaning and transformation    - Advanced data shaping techniques    - Calculated columns and measures using DAX 3. Data Visualization and Reporting   - Creating interactive reports and dashboards    - Visualizations (bar, line, pie charts, maps)    - Publishing and sharing reports, scheduling data refreshes Statistics Fundamentals: Mean, Median, Mode, Standard Deviation, Variance, Probability Distributions, Hypothesis Testing, P-values, Confidence Intervals, Correlation, Simple Linear Regression, Normal Distribution, Binomial Distribution, Poisson Distribution. ENJOY LEARNING 👍👍

Steps to become data analyst when you are fresher 👇👇 1 - First try to focus 3 mandatory skills i.e. Sql, Ms excel and python - - For sql you can refer Ankit Bansal Or Thoufiq Mohammed (techtfq) on @sqlanalyst - For Ms excel refer Leila Gharani or @excel_analyst - For python refer freecodecamp from YouTube or @pythonanalyst 2 - After that try to be clear with basic idea of tableau or powerbi. (Not mandatory for every job). You can refer this channel for free resources https://t.me/PowerBI_analyst 3 - Add your college project in your resume, if it's a data science related project it will help a lot. If you don't have project then you can make some dashboarding projects from YouTube in tableau/powerbi. 4 - And start applying for jobs which is having 0-1 yr experience required, you can also apply for 1 yr experience required job in analytics because sometimes they may consider fresher also. You can refer this channel @jobs_sql for job opportunities

Udemy - SQL & Database Design A-Z™ Learn MS SQL Server + PostgreSQL (Goldmine Drive 🗃️) Save your $2000 💸💸 (Limited Time ⏰
Udemy - SQL & Database Design A-Z™ Learn MS SQL Server + PostgreSQL (Goldmine Drive 🗃️) Save your $2000 💸💸 (Limited Time ⏰ ) Just Free Of Cost!! 👇👇 https://www.linkedin.com/posts/sql-analysts_udemy-sql-database-design-a-z-learn-activity-7139133531926040577-Lyna

+1
📚 Title: Python Image Processing Cookbook (2020)

Learn Data science in your native language and earn upto 21 LPA! Certified by IIT Madras Pravartak, this is a 3-5 month cours
Learn Data science in your native language and earn upto 21 LPA! Certified by IIT Madras Pravartak, this is a 3-5 month course that comes with assured job opportunities! Click the link below to register now and start your career in data science - https://bit.ly/4834qfW

Building Machine Learning Powered Applications (2020) #ml #en

Thanks for the likes and comments on LinkedIn. You guys are the reason because of which I am still sharing free resources❤️