Available now! Telegram Research 2025 โ the year's key insights 
Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources
Open in Telegram
Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun
Show more๐ 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 51 838 subscribers, ranking 3 362 in the Education category and 7 262 in the India region.
๐ Audience metrics and dynamics
Since its creation on ะฝะตะฒัะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 51 838 subscribers.
According to the latest data from 14 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 525 over the last 30 days and by 20 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 7.70%. Within the first 24 hours after publication, content typically collects 1.28% reactions from the total number of subscribers.
- Post reach: On average, each post receives 3 991 views. Within the first day, a publication typically gains 665 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 8.
- Thematic interests: Content is focused on key topics such as analyst, |--, excel, visualization, analytic.
๐ Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
โData Analysis Useful Resources
#dataanalysis
#dataanalysisbooks
#sqlbooks
#pythonbooks
#tableau
#powerbi
#datavisualization
For promotions: @coderfunโ
Thanks to the high frequency of updates (latest data received on 15 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.
51 838
Subscribers
+2024 hours
+1377 days
+52530 days
Posts Archive
Choosing the Right Chart Type
Selecting the appropriate chart can make or break your data storytelling. Here's a quick guide to help you choose the perfect visualization:
โณ ๐๐๐ซ ๐๐ก๐๐ซ๐ญ๐ฌ: Perfect for comparing quantities across categories (Think: regional sales comparison)
โณ ๐๐ข๐ง๐ ๐๐ก๐๐ซ๐ญ๐ฌ: Ideal for showing trends and changes over time (Example: monthly website traffic)
โณ ๐๐ข๐ ๐๐ก๐๐ซ๐ญ๐ฌ: Best for showing parts of a whole as percentages (Use case: market share breakdown)
โณ ๐๐ข๐ฌ๐ญ๐จ๐ ๐ซ๐๐ฆ๐ฌ: Great for showing the distribution of continuous data (Like salary ranges across your organization)
โณ ๐๐๐๐ญ๐ญ๐๐ซ ๐๐ฅ๐จ๐ญ๐ฌ: Essential for exploring relationships between variables (Perfect for marketing spend vs. sales analysis)
โณ ๐๐๐๐ญ ๐๐๐ฉ๐ฌ: Excellent for showing data density with color variation (Think: website traffic patterns by hour/day)
โณ ๐๐จ๐ฑ ๐๐ฅ๐จ๐ญ๐ฌ: Invaluable for displaying data variability and outliers (Great for analyzing performance metrics)
โณ ๐๐ซ๐๐ ๐๐ก๐๐ซ๐ญ๐ฌ: Shows cumulative totals over time (Example: sales growth across product lines)
โณ ๐๐ฎ๐๐๐ฅ๐ ๐๐ก๐๐ซ๐ญ๐ฌ: Powerful for displaying three dimensions of data (Combines size, position, and grouping)
๐๐ซ๐จ ๐๐ข๐ฉ: Always consider your audience and the story you want to tell when choosing your visualization type.
I have curated the best interview resources to crack Power BI Interviews ๐๐
https://t.me/PowerBI_analyst
Hope you'll like it
Like this post if you need more resources like this ๐โค๏ธ
Repost from Python Projects & Resources
๐ฃ๐ผ๐๐ฒ๐ฟ๐๐ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ ๐๐ฟ๐ผ๐บ ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐๐
โ
Beginner-friendly
โ
Straight from Microsoft
โ
And yesโฆ a badge for that resume flex
Perfect for beginners, job seekers, & Working Professionals
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/4iq8QlM
Enroll for FREE & Get Certified ๐
Data types are foundational in computing, and it's essential to understand them to work effectively in any programming environment.
Let's take a dive into the top ten commonly used data types:
1. Integer (int):
- Represents whole numbers.
- Examples: -2, -1, 0, 1, 2, 3
2. Floating Point (float/double):
- Represents numbers with decimals.
- Examples: -2.5, 0.0, 3.14
3. Character (char):
- Represents single characters.
- Examples: 'A', 'b', '1', '%'
4. String:
- Represents sequences of characters, basically text.
- Examples: "Hello", "ChatGPT", "1234"
5. Boolean (bool):
- Represents true or false values.
- Examples: True, False
6. Array:
- Represents a collection of elements, often of the same type.
- Examples: [1, 2, 3], ["apple", "banana", "cherry"]
7. Object:
- Used in object-oriented programming, represents a combination of data and methods to manipulate the data.
- Examples: A Car object might have data like color and speed and methods like drive() and park().
8. Date & Time:
- Represents date and time values.
- Examples: 23-10-2023, 12:30:45
9. Byte & Binary:
- Represents raw binary data.
- Examples: 01010101 (Byte), 101000111011 (Binary)
10. Enum:
- Represents a set of named constants.
- Examples: Days of the week (Monday, Tuesday...), Colors (Red, Blue, Green)
Repost from SQL Programming Resources
๐ง๐ผ๐ฝ ๐ฐ ๐๐ผ๐ฟ ๐๐ฅ๐๐ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐ ๐ง๐ผ ๐ ๐ฎ๐๐๐ฒ๐ฟ ๐ฆ๐ค๐ ๐๐ผ๐ฟ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐
These FREE resources are all you need to go from beginner to confident analyst! ๐ป๐
โ
Hands-on projects
โ
Beginner to advanced lessons
โ
Resume-worthy skills
๐๐ถ๐ป๐ธ:-๐
https://pdlink.in/4jkQaW1
Learn today, level up tomorrow. Letโs go!โ
Steps to become data analyst when you are fresher ๐๐
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
Repost from Artificial Intelligence
๐๐ฒ๐ฎ๐ฟ๐ป ๐ก๐ฒ๐ ๐ฆ๐ธ๐ถ๐น๐น๐ ๐ณ๐ผ๐ฟ ๐๐ฅ๐๐ & ๐๐ฎ๐ฟ๐ป ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ฒ๐!๐
Looking to upgrade your skills in Data Science, Programming, AI, Business, and more? ๐๐ก
This platform offers FREE online courses that help you gain job-ready expertise and earn certificates to showcase your achievements! โ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/41Nulbr
Donโt miss out! Start exploring today๐
TOP CONCEPTS FOR INTERVIEW PREPARATION!!
๐TOP 10 SQL Concepts for Job Interview
1. Aggregate Functions (SUM/AVG)
2. Group By and Order By
3. JOINs (Inner/Left/Right)
4. Union and Union All
5. Date and Time processing
6. String processing
7. Window Functions (Partition by)
8. Subquery
9. View and Index
10. Common Table Expression (CTE)
๐TOP 10 Statistics Concepts for Job Interview
1. Sampling
2. Experiments (A/B tests)
3. Descriptive Statistics
4. p-value
5. Probability Distributions
6. t-test
7. ANOVA
8. Correlation
9. Linear Regression
10. Logistics Regression
๐TOP 10 Python Concepts for Job Interview
1. Reading data from file/table
2. Writing data to file/table
3. Data Types
4. Function
5. Data Preprocessing (numpy/pandas)
6. Data Visualisation (Matplotlib/seaborn/bokeh)
7. Machine Learning (sklearn)
8. Deep Learning (Tensorflow/Keras/PyTorch)
9. Distributed Processing (PySpark)
10. Functional and Object Oriented Programming
Like โค๏ธ the post if it was helpful to you!!!
Data Analysis vs Data Science
Data analysis often focuses on interpreting and summarizing existing data, requiring skills like statistical analysis, SQL, and data visualization.
On the other hand, data science involves a broader set of skills, including machine learning, predictive modeling, and advanced programming.
In essence, data analysis is a subset of data science, with data scientists often having a more extensive toolkit for handling complex and unstructured data.
Free Resources to become data analyst -> https://www.linkedin.com/posts/sql-analysts_freecertificates-dataanalysts-python-activity-7113004712412524545-Uw4k
Steps to become data scientist -> https://t.me/learndataanalysis/559
Repost from SQL Programming Resources
๐ช๐ฒ๐ฏ ๐๐ฒ๐๐ฒ๐น๐ผ๐ฝ๐บ๐ฒ๐ป๐ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐
Want to master web development? These free certification courses will help you build real-world full-stack skills:
โ
Web Design ๐จ
โ
JavaScript โก
โ
Front-End Libraries ๐
โ
Back-End & APIs ๐
โ
Databases ๐พ
๐ก Start learning today and build your career for FREE! ๐
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/4bqbQwB
Enroll for FREE & Get Certified ๐
Checklist to become a Data Analyst
๐ฑ ๐๐ฅ๐๐ ๐๐ผ๐ผ๐ด๐น๐ฒ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐
Explore AI, machine learning, and cloud computing โ straight from Google and FREE
1. ๐Google AI for Anyone
2. ๐ปGoogle AI for JavaScript Developers
3. โ๏ธ Cloud Computing Fundamentals (Google Cloud)
4. ๐ Data, ML & AI in Google Cloud
5. ๐ Smart Analytics, ML & AI on Google Cloud
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/3YsujTV
Enroll for FREE & Get Certified ๐
Want to build your first AI agent?
Join a live hands-on session by GeeksforGeeks & Salesforce for working professionals
- Build with Agent Builder
- Assign real actions
- Get a free certificate of participation
Registeration link:๐
https://gfgcdn.com/tu/V4t/
9 secrets about Data Storytelling every analyst should know (number 6 is a must):
1/ Start with the end in mindโwhatโs the key takeaway?
2/ Donโt just present numbersโexplain the 'so what' behind them.
3/ Data should drive decisionsโframe your analysis as a solution to a problem.
#DataAnalytics
4/ Visualise trends over time to tell a story.
5/ Add context to your dataโit makes your insights relevant.
6/ Speak the language of your audienceโsimplify complex terms.
7/ Use metaphors or analogies to explain difficult concepts. Don't use professional jargon.
8/ Include both the big picture and the detailsโit appeals to different stakeholders.
9/ Conclude with a call to actionโwhat should they do next?
๐๐ฅ๐๐ ๐ช๐ฒ๐ฏ๐๐ถ๐๐ฒ๐ ๐ง๐ผ ๐ ๐ฎ๐๐๐ฒ๐ฟ ๐๐ผ๐ฑ๐ถ๐ป๐ด ๐๐ผ๐ฟ ๐๐ฅ๐๐ ๐
Level up your coding skills without spending a dime? ๐ฐ
These free interactive platforms will help you learn, practice, and build real projects in HTML, CSS, JavaScript, React, and Python!
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/4aJHgh5
Enroll For FREE & Get Certified ๐
๐ Starter Kit 2025 - Data Analyst
Want to make a transition to a career in data?
Here is a 7-step plan for each data role
Data Scientist
Statistics and Math: Advanced statistics, linear algebra, calculus.
Machine Learning: Supervised and unsupervised learning algorithms.
xData Wrangling: Cleaning and transforming datasets.
Big Data: Hadoop, Spark, SQL/NoSQL databases.
Data Visualization: Matplotlib, Seaborn, D3.js.
Domain Knowledge: Industry-specific data science applications.
Data Analyst
Data Visualization: Tableau, Power BI, Excel for visualizations.
SQL: Querying and managing databases.
Statistics: Basic statistical analysis and probability.
Excel: Data manipulation and analysis.
Python/R: Programming for data analysis.
Data Cleaning: Techniques for data preprocessing.
Business Acumen: Understanding business context for insights.
Data Engineer
SQL/NoSQL Databases: MySQL, PostgreSQL, MongoDB, Cassandra.
ETL Tools: Apache NiFi, Talend, Informatica.
Big Data: Hadoop, Spark, Kafka.
Programming: Python, Java, Scala.
Data Warehousing: Redshift, BigQuery, Snowflake.
Cloud Platforms: AWS, GCP, Azure.
Data Modeling: Designing and implementing data models.
#data
๐ง๐ผ๐ฝ ๐ ๐ก๐๐ ๐๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐๐ ๐
Mercedes :- https://pdlink.in/3RPLXNM
TechM :- https://pdlink.in/4cws0oN
SE :- https://pdlink.in/42feu5D
Siemens :- https://pdlink.in/4jxhzDR
Dxc :- https://pdlink.in/4ctIeis
EY:- https://pdlink.in/4lwMQZo
Apply before the link expires ๐ซ
Hi Guys,
Here are some of the telegram channels which may help you in data analytics journey ๐๐
SQL: https://t.me/sqlanalyst
Power BI & Tableau: https://t.me/PowerBI_analyst
Excel: https://t.me/excel_analyst
Python: https://t.me/dsabooks
Jobs: https://t.me/jobs_SQL
Data Science: https://t.me/datasciencefree
Artificial intelligence: https://t.me/machinelearning_deeplearning
Data Engineering: https://t.me/sql_engineer
Data Analysts: https://t.me/sqlspecialist
Hope it helps :)
๐๐ฃ ๐ ๐ผ๐ฟ๐ด๐ฎ๐ป ๐๐ฅ๐๐ ๐ฉ๐ถ๐ฟ๐๐๐ฎ๐น ๐๐ป๐๐ฒ๐ฟ๐ป๐๐ต๐ถ๐ฝ ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐๐
JPMorgan offers free virtual internships to help you develop industry-specific tech, finance, and research skills.
- Software Engineering Internship
- Investment Banking Program
- Quantitative Research Internship
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/4gHGofl
Enroll For FREE & Get Certified ๐
