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Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun

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📈 Analytical overview of Telegram channel Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 51 872 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.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun”

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.

51 872

Subscribers

-524 hours

+1227 days

+50630 days

3 314

Post views

~ 65424 hours

~ 90248 hours

6.39%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

51 872

Free Data sets for Data Science & Machine Learning Projects 👇👇 https://t.me/DataPortfolio

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Statistics and Data Visualization in Climate Science with R.pdf35.54 MB

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Nice to see amazing participation 😄❤️

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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.

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New Giveaway 500 TB Tutorials + Books + Courses + Trainings + Workshops + Educational Resources 😀 Data science Python Data Analytics AWS Certified BIG DATA BI Machine Learning and more.. 👇👇 https://www.linkedin.com/posts/sql-analysts_python-datascience-aws-activity-7134053938898608128-TCyi?utm_source=share&utm_medium=member_android

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EDA With Pandas.pdf0.94 KB

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Avoid directly copying YouTube projects onto your resume because if everyone looks the same, recruiters might discard resumes. Instead, for eg, let's say you are working on a SQL case study, download a dataset from Kaggle (usually a CSV file), set up a Postgre/MySQL database, connect it with the data, and prompt ChatGPT with questions ranging from basic to advanced SQL. 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. ENJOY LEARNING 👍👍

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Python Data Science Projects For Boosting Your Portfolio

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https://www.linkedin.com/posts/sql-analysts_excel-sql-power-bi-python-and-tableau-activity-7132410397864660992-etK8?utm_source=share&utm_medium=member_android

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Fuzzy Data Matching with SQL Jim Lehmer, 2023

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Mission AI Haroon Sheikh, 2023

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Useful books to learn Python, C++ & other programming languages posted in this channel 👇👇 https://t.me/codingwithsagar

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Do you enjoy reading this channel? Perhaps you have thought about placing ads on it? To do this, follow three simple steps: 1) Sign up: https://telega.io/c/learndataanalysis 2) Top up the balance in a convenient way 3) Create an advertising post If the topic of your post fits our channel, we will publish it with pleasure.

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Applied Geospatial Data Science with Python.pdf21.67 MB

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Beginner-friendly Excel Book

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https://www.linkedin.com/posts/sql-analysts_excel-for-beginners-activity-7131506316677693440-Ip8j?utm_source=share&utm_medium=member_android

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Importance of Data Cleaning https://www.linkedin.com/posts/sql-analysts_datacleaning-dataanalytics-numpy-activity-7131211154634264577-C21z?utm_source=share&utm_medium=member_android

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R Programming for Beginners Nathan Metzler, 2020

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Data Analytics Using R Serma Acharya, 2018

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Repost from MS Excel for Data Analysis

Excel for Data Analysis