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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
Show moreπ Analytical overview of Telegram channel Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources
Channel Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources (@learndataanalysis) in the English language segment is an active participant. Currently, the community unites 51 869 subscribers, ranking 3 352 in the Education category and 7 187 in the India region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 51 869 subscribers.
According to the latest data from 17 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 506 over the last 30 days and by -5 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 6.39%. Within the first 24 hours after publication, content typically collects 1.26% reactions from the total number of subscribers.
- Post reach: On average, each post receives 3 314 views. Within the first day, a publication typically gains 654 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 6.
- Thematic interests: Content is focused on key topics such as analyst, |--, excel, visualization, analytic.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βData Analysis Useful Resources
#dataanalysis
#dataanalysisbooks
#sqlbooks
#pythonbooks
#tableau
#powerbi
#datavisualization
For promotions: @coderfunβ
Thanks to the high frequency of updates (latest data received on 18 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.
51 869
Subscribers
-524 hours
+1227 days
+50630 days
Posts Archive
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SQL Basics: https://t.me/sqlanalyst/105
Here are some Excel shortcuts that are commonly used by data analysts:
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ENJOY LEARNING ππππData Analytics skills and projects to add in a resume to get shortlisted
1. Technical Skills:
Proficiency in data analysis tools (e.g., Python, R, SQL).
Data visualization skills using tools like Tableau or Power BI.
Experience with statistical analysis and modeling techniques.
2. Data Cleaning and Preprocessing:
Showcase skills in cleaning and preprocessing raw data for analysis.
Highlight expertise in handling missing data and outliers effectively.
3. Database Management:
Mention experience with databases (e.g., MySQL, PostgreSQL) for data retrieval and manipulation.
4. Machine Learning:
If applicable, include knowledge of machine learning algorithms and their application in data analytics projects.
5. Data Storytelling:
Emphasize your ability to communicate insights effectively through data storytelling.
6. Big Data Technologies:
If relevant, mention experience with big data technologies such as Hadoop or Spark.
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Showcase an understanding of the business context and how your analytics work contributes to organizational goals.
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Highlight instances where you solved business problems through data-driven insights.
9. Collaboration and Communication:
Demonstrate your ability to work in a team and communicate complex findings to non-technical stakeholders.
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πΌTailor your resume to the specific job description, emphasizing the skills and experiences that align with the requirements of the position you're applying for.
Best practices for writing SQL queries:
Join for more: https://t.me/learndataanalysis
1- Write SQL keywords in capital letters.
2- Use table aliases with columns when you are joining multiple tables.
3- Never use select *, always mention list of columns in select clause.
4- Add useful comments wherever you write complex logic. Avoid too many comments.
5- Use joins instead of subqueries when possible for better performance.
6- Create CTEs instead of multiple sub queries , it will make your query easy to read.
7- Join tables using JOIN keywords instead of writing join condition in where clause for better readability.
8- Never use order by in sub queries , It will unnecessary increase runtime.
9- If you know there are no duplicates in 2 tables, use UNION ALL instead of UNION for better performance.
SQL Basics: https://t.me/sqlanalyst/105
Avoid directly copying YouTube projects onto your resume because if everyone looks the same, recruiters might discard resumes.
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Solve the questions step by step. When using PowerBI, connect to the database and create a compelling dashboard. Don't just upload the dataset; employ DAX queries, statistical functions, and avoid relying solely on drag-and-drop features. Use Formatting section to do creative stuff and add your unique element in the project.
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