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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 582Education2 274

📈 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 70 805 subscribers, ranking 2 274 in the Education category and 4 582 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 70 805 subscribers.

According to the latest data from 25 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -309 over the last 30 days and by -33 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 12.05%. Within the first 24 hours after publication, content typically collects 2.78% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 8 533 views. Within the first day, a publication typically gains 1 972 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|.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Learn 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 26 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.

70 805
Subscribers
-3324 hours
-1127 days
-30930 days
Posts Archive
Data Science
Data Science
70 805
🔅 Advanced Python: Top Tools for Data Science and Engineering 📝 This comprehensive course is designed to equip you with the
🔅 Advanced Python: Top Tools for Data Science and Engineering 📝 This comprehensive course is designed to equip you with the essential skills for data analysis and application development using Python and popular data tools and libraries. 🌐 Author: Joe Marini 🔰 Level: Intermediate ⏰ Duration: 2h 5m 📋 Topics: Pandas, Data Engineering, Data Science 🔗 Join Data Science for more courses

Data Science
Data Science
70 805
Key Pandas Functions for Data Importing, Cleaning, and Statistics. Boost your data analysis workflow with essential Python co
Key Pandas Functions for Data Importing, Cleaning, and Statistics. Boost your data analysis workflow with essential Python commands

Data Science
Data Science
70 805
🔢 Data Cleaning Tips Every Analyst Should Know If your analysis feels off, it’s probably your data. These 5 tips will help y
🔢 Data Cleaning Tips Every Analyst Should Know If your analysis feels off, it’s probably your data. These 5 tips will help you clean your dataset like a pro: ✔️ Handle missing values ✔️ Remove duplicates ✔️ Fix data types ✔️ Standardize formats ✔️ Detect and remove outliers Clean data = better insights = better decisions.

Data Science
Data Science
70 805
📖 Data Structures, you need to know for Coding interview
📖 Data Structures, you need to know for Coding interview

Data Science
Data Science
70 805
📱Data Science 📱Data Science Reporting with Quarto for Python

Data Science
Data Science
70 805
🔅 Data Science Reporting with Quarto for Python 📝 Leverage the power of Quarto to build publication-quality reports, engagi
🔅 Data Science Reporting with Quarto for Python 📝 Leverage the power of Quarto to build publication-quality reports, engaging presentation decks, and rich interactive webpages from Jupyter Notebook for Python. 🌐 Author: Charlie Joey Hadley 🔰 Level: Intermediate ⏰ Duration: 2h 26m 📋 Topics: Data Reporting, Data Science, Data Analytics 🔗 Join Data Science for more courses

Data Science
Data Science
70 805
🔄 Life Cycle of a Data Analytical Project
🔄 Life Cycle of a Data Analytical Project

Data Science
Data Science
70 805
🖥Type of Databases
🖥Type of Databases

Data Science
Data Science
70 805
@LearnPython3 - Python Data Science Handbook 2nd ed.pdf19.70 MB

Data Science
Data Science
70 805
🔰 📙 Python Data Science Handbook 2nd Edition
🔰 📙 Python Data Science Handbook 2nd Edition

Data Science
Data Science
70 805
📱Data Science 📱Decision Intelligence: Data Stories

Data Science
Data Science
70 805
🔅 Decision Intelligence: Data Stories 📝 Learn how to use key lessons from famous data stories around the world to improve d
🔅 Decision Intelligence: Data Stories 📝 Learn how to use key lessons from famous data stories around the world to improve decision-making, interpret data effectively, and communicate insights responsibly. 🌐 Author: Franz Buscha 🔰 Level: Beginner ⏰ Duration: 45m 📋 Topics: Data Science, Decision Sciences, Data-driven Decision Making 🔗 Join Data Science for more courses

Data Science
Data Science
70 805
🖥 8 Common database types explained
🖥 8 Common database types explained

Data Science
Data Science
70 805
📖 Learn Database Databases power everything from websites and apps to enterprise systems. Here’s a learning map that can hel
📖 Learn Database Databases power everything from websites and apps to enterprise systems. Here’s a learning map that can help you master databases: 1 - Database Fundamentals This includes topics like “What is a database”, RDBMS, SQL vs NoSQL, ACID vs BASE, OLTP vs OLAP, Transactions, and Isolation Levels. 2 - Data Models and Types Consists of topics like Relational Databases, Non-Relational Databases, and Data Types (Integer, String, Boolean, Date, JSON, etc). 3 - Querying and Language This includes topics like SQL Basics (SELECT, INSERT, etc), Advanced SQL (Views, Indexes, CTEs, etc), and NoSQL Querying (Aggregation and Key-Value Lookups). 4 - Indexing and Optimization Consists of topics like Indexing (B-Tree, Hash, and Bitmaps), Query Execution Plans, Denormalization vs Normalization, Sharding, Connecting Pooling, and Query Batching. 5 - Security, Backups, and Scaling This includes topics like User Roles, Permissions, Encryption, SQL Injection, High Availability (Replication and Failover), Horizontal vs Vertical Scaling. 6 - Tools and Ecosystem Consists of topics like Popular SQL Databases, NoSQL Database, GUI Tools, ORMs, Cloud DB services (RDS, DynamoDB, Google Cloud SQL, etc.)

Data Science
Data Science
70 805
Do you know the real difference between Data Engineering vs. Data Scientists vs. Data Analysts?
Do you know the real difference between Data Engineering vs. Data Scientists vs. Data Analysts?

Data Science
Data Science
70 805
📱Data Science 📱The 80/20 Rule of Data Science

Data Science
Data Science
70 805
🔅 The 80/20 Rule of Data Science 📝 Explore the core concepts of the 80/20 rule for data science and how to get most of the
🔅 The 80/20 Rule of Data Science 📝 Explore the core concepts of the 80/20 rule for data science and how to get most of the value with minimal effort. 🌐 Author: Howard Friedman 🔰 Level: Intermediate ⏰ Duration: 1h 26m 📋 Topics: Data Science, Project Engineering, Team Management 🔗 Join Data Science for more courses

Data Science
Data Science
70 805
📖 What are DDL Commands in SQL? They don’t touch your data — they shape where your data lives. Use CREATE, ALTER, and DROP t
📖 What are DDL Commands in SQL? They don’t touch your data — they shape where your data lives. Use CREATE, ALTER, and DROP to define and change your database structure. 💡 Powerful, essential — and should be used with care!

Data Science
Data Science
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🖥 Tableau vs. Power BI
🖥 Tableau vs. Power BI

Data Science
Data Science
70 805
🖥 4 main database types
🖥 4 main database types