Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources
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Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun
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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。
53 299
订阅者
-824 小时
-127 天
+1130 天
帖子存档
SQL The Ultimate Intermediate Guide.pdf2.54 MB
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
Computer Vision
Pancham Shukla, 2023
Udemy - SQL & Database Design A-Z™ Learn MS SQL Server + PostgreSQL (Goldmine Drive 🗃️)
Save your $2000 💸💸
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https://www.linkedin.com/posts/sql-analysts_udemy-sql-database-design-a-z-learn-activity-7139133531926040577-Lyna
📚 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 course that comes with assured job opportunities!
Click the link below to register now and start your career in data science -
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5 Mini Projects for Power BI
👇👇
https://t.me/PowerBI_analyst/52
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❤️
The AI Project Handbook
Minh Trinh, 2021
Hopefully everyone got this free book 😄👍
