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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 735Education2 282

📈 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 71 061 subscribers, ranking 2 282 in the Education category and 4 735 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 71 061 subscribers.

According to the latest data from 07 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -16 over the last 30 days and by 26 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 11.90%. Within the first 24 hours after publication, content typically collects 3.01% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 8 458 views. Within the first day, a publication typically gains 2 142 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 08 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.

71 061
Subscribers
+2624 hours
+477 days
-1630 days
Posts Archive
Data Science
Data Science
71 059
🔅 Top Five Things to Know in Advanced SQL 📝 Learn advanced SQL concepts and practice them with hands-on exercises. 🌐 Autho
🔅 Top Five Things to Know in Advanced SQL 📝 Learn advanced SQL concepts and practice them with hands-on exercises. 🌐 Author: Kendall Ruber 🔰 Level: Advanced ⏰ Duration: 1h 35m 📋 Topics: SQL 🔗 Join Data Analysis for more courses

Data Science
Data Science
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📖 SQL data types
+1
📖 SQL data types

Data Science
Data Science
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📖 Top 10 Database Scaling Techniques You Should Know: 1. 𝐈𝐧𝐝𝐞𝐱𝐢𝐧𝐠: Create indexes on frequently queried columns to s
📖 Top 10 Database Scaling Techniques You Should Know: 1. 𝐈𝐧𝐝𝐞𝐱𝐢𝐧𝐠: Create indexes on frequently queried columns to speed up data retrieval. 2. 𝐕𝐞𝐫𝐭𝐢𝐜𝐚𝐥 𝐒𝐜𝐚𝐥𝐢𝐧𝐠: Upgrade your database server by adding more CPU, RAM, or storage to handle increased load. 3. 𝐂𝐚𝐜𝐡𝐢𝐧𝐠: Store frequently accessed data in-memory (e.g., Redis, Memcached) to reduce database load and improve response time. 4. 𝐒𝐡𝐚𝐫𝐝𝐢𝐧𝐠: Distribute data across multiple servers by splitting the database into smaller, independent shards, allowing for horizontal scaling and improved performance. 5. 𝐑𝐞𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Create multiple copies (replicas) of the database across different servers, enabling read queries to be distributed across replicas and improving availability. 6. 𝐐𝐮𝐞𝐫𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Fine-tune SQL queries, eliminate expensive operations, and leverage indexes effectively to improve execution speed and reduce database load. 7. 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐨𝐧 𝐏𝐨𝐨𝐥𝐢𝐧𝐠: Reduce the overhead of opening/closing database connections by reusing existing ones, improving performance under heavy traffic. 8. 𝐕𝐞𝐫𝐭𝐢𝐜𝐚𝐥 𝐏𝐚𝐫𝐭𝐢𝐭𝐢𝐨𝐧𝐢𝐧𝐠: Split large tables into smaller, more manageable parts (partitions), each containing a subset of the columns/features from the original table. 9. 𝐃𝐞𝐧𝐨𝐫𝐦𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Store data in a redundant but structured format to minimize complex joins and speed up read-heavy workloads. 10. 𝐌𝐚𝐭𝐞𝐫𝐢𝐚𝐥𝐢𝐳𝐞𝐝 𝐕𝐢𝐞𝐰𝐬: Pre-compute and store results of complex queries as separate tables to avoid expensive recalculation, reducing database load and improving response times.

Data Science
Data Science
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📁 The in demand skills of a data analytics
📁 The in demand skills of a data analytics

Data Science
Data Science
71 059
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Data Science
Data Science
71 059
📱Data Analysis 📱Python Data Structures: Dictionaries

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Data Science
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🔅 Python Data Structures: Dictionaries 📝 Learn how to use dictionaries to store and retrieve unordered data in Python. 🌐 A
🔅 Python Data Structures: Dictionaries 📝 Learn how to use dictionaries to store and retrieve unordered data in Python. 🌐 Author: Deepa Muralidhar 🔰 Level: Beginner ⏰ Duration: 57m 📋 Topics: Data Structures, Python 🔗 Join Data Analysis for more courses

Data Science
Data Science
71 059
🔰 The 4 Types of SQL Joins SQL joins combine rows from two or more tables based on a related column. Here are the different
🔰 The 4 Types of SQL Joins SQL joins combine rows from two or more tables based on a related column. Here are the different types of joins you can use: 1⃣ Inner Join Returns only the matching rows between both tables. It keeps common data only. 🔢 Left Join Returns all rows from the left table and matching rows from the right table. If a row in the left table doesn’t have a match in the right table, the right table’s columns will contain NULL values in that row. 🔢 Right Join Returns all rows from the right table and matching rows from the left table. If no matching record exists in the left table for a record in the right table, the columns from the left table in the result will contain NULL values. 🔢 FULL OUTER JOIN Returns all rows from both tables, filling in NULL for missing matches.

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📖 SQL cheat sheet - Every JOIN explained
📖 SQL cheat sheet - Every JOIN explained

Data Science
Data Science
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Data Science
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Python Developer (Twitter) Data Science Sandwich ! #python #datascience #machinelearning #deeplearning #ai #artificialintelli

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📦 Exercise Files

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📱Data Analysis 📱Advanced NoSQL for Data Science

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Data Science
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🔅 Advanced NoSQL for Data Science 📝 Explore the fundamentals of NoSQL. Learn the differences between NoSQL and traditional
🔅 Advanced NoSQL for Data Science 📝 Explore the fundamentals of NoSQL. Learn the differences between NoSQL and traditional relational databases, discover how to perform common data science tasks with NoSQL, and more. 🌐 Author: Dan Sullivan 🔰 Level: Advanced ⏰ Duration: 1h 54m 📋 Topics: Data Science, NoSQL 🔗 Join Data Analysis for more courses

Data Science
Data Science
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📖 Types of Keys in SQL
📖 Types of Keys in SQL

Data Science
Data Science
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📱Data Analysis 📱Python in Excel: Getting Started with Data Analysis

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Data Science
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🔅 Python in Excel: Getting Started with Data Analysis 📝 Explore the core concepts and fundamental skills of working with da
🔅 Python in Excel: Getting Started with Data Analysis 📝 Explore the core concepts and fundamental skills of working with data using Python in Microsoft Excel. 🌐 Author: Joe Marini 🔰 Level: Intermediate ⏰ Duration: 1h 40m 📋 Topics: Data Analysis, Microsoft Excel, Python 🔗 Join Data Analysis for more courses

Data Science
Data Science
71 059
📊 Your Data Analyst journey doesn’t start with tools — it starts with a roadmap. From mastering Excel & SQL ➝ understanding
📊 Your Data Analyst journey doesn’t start with tools — it starts with a roadmap. From mastering Excel & SQL ➝ understanding statistics ➝ working with Python & visualization tools ➝ building real-world projects — 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
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📖🔰 Pandas vs SQL: Most Common Operations Comparison
📖🔰 Pandas vs SQL: Most Common Operations Comparison

Data Science
Data Science
71 059
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