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Data Science

Data Science

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Learn how to analyze data effectively and manage databases with ease. Buy ads: https://telega.io/c/sql_databases

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India4 562Education2 261

πŸ“ˆ Analytical overview of Telegram channel Data Science

Channel Data Science (@sql_databases) in the English language segment is an active participant. Currently, the community unites 70 803 subscribers, ranking 2 261 in the Education category and 4 562 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 70 803 subscribers.

According to the latest data from 26 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -310 over the last 30 days and by -15 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 11.21%. Within the first 24 hours after publication, content typically collects 2.74% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 7 934 views. Within the first day, a publication typically gains 1 943 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.
  • Thematic interests: Content is focused on key topics such as database, learning, linkedin, udemy, 029k|.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œLearn how to analyze data effectively and manage databases with ease. Buy ads: https://telega.io/c/sql_databases”

Thanks to the high frequency of updates (latest data received on 27 August, 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.

70 803
Subscribers
-1524 hours
-1277 days
-31030 days
Posts Archive
Data Science
Data Science
70 803
πŸ“– Types of Keys in SQL
πŸ“– Types of Keys in SQL

Data Science
Data Science
70 803
πŸ“±Data Analysis πŸ“±Python in Excel: Getting Started with Data Analysis

Data Science
Data Science
70 803
πŸ”… Python in Excel: Getting Started with Data Analysis πŸ“ Explore the core concepts and fundamental skills of working with da
πŸ”… Python in Excel: Getting Started with Data Analysis πŸ“ Explore the core concepts and fundamental skills of working with data using Python in Microsoft Excel. 🌐 Author: Joe Marini πŸ”° Level: Intermediate ⏰ Duration: 1h 40m πŸ“‹ Topics: Data Analysis, Microsoft Excel, Python πŸ”— Join Data Analysis for more courses

Data Science
Data Science
70 803
πŸ“Š Your Data Analyst journey doesn’t start with tools β€” it starts with a roadmap. From mastering Excel & SQL ➝ understanding
πŸ“Š Your Data Analyst journey doesn’t start with tools β€” it starts with a roadmap. From mastering Excel & SQL ➝ understanding statistics ➝ working with Python & visualization tools ➝ building real-world projects β€” a clear Data Analyst roadmap can save you months of confusion and wrong learning choices. If you’re serious about breaking into analytics in 2026, you don’t need random tutorials. You need structured learning, hands-on practice, and industry-relevant skills.

Data Science
Data Science
70 803
πŸ“–πŸ”° Pandas vs SQL: Most Common Operations Comparison
πŸ“–πŸ”° Pandas vs SQL: Most Common Operations Comparison

Data Science
Data Science
70 803
πŸ”… PREMIUM CHANNELS -β—¦-β—¦--β—¦--β—¦-β—¦--β—¦--β—¦-β—¦--β—¦--β—¦-β—¦--β—¦- πŸ”° Web Development -β—¦-β—¦--β—¦--β—¦-β—¦--β—¦--β—¦-β—¦-- 221k| πŸ”° Linkedin Learning 143k| πŸ”° Udemy Premium 134k| πŸ”° Web Development -β—¦-β—¦--β—¦- 121k| πŸ”° Python 3 099k| πŸ”° JavaScript Training 091k| πŸ”° Machine Learning -β—¦-β—¦--β—¦- 070k| πŸ”° Data Analysis and Databases 069k| πŸ”° Artificial Intelligence 064k| πŸ”° React and NextJs -β—¦-β—¦--β—¦- 064k| πŸ”° Linux and DevOps 050k| πŸ”° 100 Days of Python 049k| πŸ”° OpenAI Mastery -β—¦-β—¦--β—¦- 049k| πŸ”° Business and Finance 044k| πŸ”° Best Telegram Channels 041k| πŸ”° Udemy Learning -β—¦-β—¦--β—¦- 040k| πŸ”° Zero to Mastery 040k| πŸ”° Mobile Apps 036k| πŸ”° Linkedin Learning Courses -β—¦-β—¦--β—¦- 035k| πŸ”° Codedamn Courses 034k| πŸ”° React 101 031k| πŸ”° Crypto Tutorials -β—¦-β—¦--β—¦- 031k| πŸ”° Coding Interview 025k| πŸ”° Telegram's Shorts 023k| πŸ”° The Coding Space -β—¦-β—¦--β—¦- 023k| πŸ”° Linux Training -β—¦-β—¦--β—¦--β—¦-β—¦--β—¦--β—¦-β—¦-- πŸ”° Add Your Channel -β—¦-β—¦--β—¦--β—¦-β—¦--β—¦--β—¦-β—¦--β—¦--β—¦-β—¦--β—¦- πŸ”° 2hrs on top & 8hrs in channel!

Data Science
Data Science
70 803
80% of data problems can be solved with just 16 SQL functions. I’ve been working with data for years and this truth keeps pro
+1
80% of data problems can be solved with just 16 SQL functions. I’ve been working with data for years and this truth keeps proving itself: You don’t need fancy tools. You need to master the fundamentals. For data analysts, data scientists, and data engineers: SQL isn’t optional. Because data lives in databases. And databases speak SQL-ish. Most problems fall into 2 categories: Aggregate functions (summarise data): SUM() - Total revenue COUNT() - Total orders AVG() - Average purchase value MIN() - Smallest sale MAX() - Biggest transaction STRING_AGG() - Combine text values Window functions (compare rows): ROW_NUMBER() - Pagination RANK() - Leaderboards with ties DENSE_RANK() - Performance tiers NTILE() - Split into quartiles LEAD() - Compare current vs next LAG() - Compare current vs previous FIRST_VALUE() - Highest value per group LAST_VALUE() - Lowest value per group SUM() OVER() - Running totals AVG() OVER() - Moving averages Aggregates collapse rows β†’ one summary result Window functions keep all rows β†’ add calculations across them

Data Science
Data Science
70 803
πŸ“¦ Exercise Files

Data Science
Data Science
70 803
πŸ“±Data Analysis πŸ“±MySQL Installation and Configuration

Data Science
Data Science
70 803
πŸ”… MySQL Installation and Configuration πŸ“ Learn how to install and configure MySQL on various platforms, including Mac and W
πŸ”… MySQL Installation and Configuration πŸ“ Learn how to install and configure MySQL on various platforms, including Mac and Windows. 🌐 Author: Bill Weinman πŸ”° Level: Intermediate ⏰ Duration: 1h 20m πŸ“‹ Topics: MySQL, Database Administration πŸ”— Join Data Analysis for more courses

Data Science
Data Science
70 803
πŸ“ Mastering SQL
πŸ“ Mastering SQL

Data Science
Data Science
70 803
πŸ“– SQL Basics
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πŸ“– SQL Basics

Data Science
Data Science
70 803
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Data Science
Data Science
70 803
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Data Science
Data Science
70 803
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Data Science
Data Science
70 803
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Data Science
Data Science
70 803
If you’re thinking of starting a career in data science but not sure where to begin, πŸ€” don’t worryβ€”I’ve got you covered! πŸ™Œ
If you’re thinking of starting a career in data science but not sure where to begin, πŸ€” don’t worryβ€”I’ve got you covered! πŸ™Œ Here’s a list of platforms that can help you learn πŸ“š, practice πŸ’», and ace your interviews. Whether you’re diving into online courses πŸ§‘β€πŸ«, looking for datasets πŸ“Š to build your projects, or sharpening your coding skills πŸ’‘ for interviews, these resources are perfect for you.

Data Science
Data Science
70 803
πŸ“±Data Analysis πŸ“±Hands-On Advanced Python: Data Engineering Basics

Data Science
Data Science
70 803
πŸ”… Hands-On Advanced Python: Data Engineering Basics πŸ“ Practice applying advanced concepts and coding moves in Python in thi
πŸ”… Hands-On Advanced Python: Data Engineering Basics πŸ“ Practice applying advanced concepts and coding moves in Python in this hands-on, interactive course with coding challenges in CoderPad. 🌐 Author: Joe Marini πŸ”° Level: Advanced ⏰ Duration: 1h 56m πŸ“‹ Topics: Python πŸ”— Join Data Analysis for more courses

Data Science
Data Science
70 803
πŸ“– Brain of Data Analyst
πŸ“– Brain of Data Analyst