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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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📈 Аналитический обзор Telegram-канала Data Science

Канал Data Science (@sql_databases) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 71 033 подписчиков, занимая 2 273 место в категории Образование и 4 764 место в регионе Индия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 71 033 подписчиков.

Согласно последним данным от 05 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -54, а за последние 24 часа — 6, при этом общий охват остаётся высоким.

  • Статус верификации: Не верифицирован
  • Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 12.21%. В первые 24 часа после публикации контент обычно набирает 2.97% реакций от общего числа подписчиков.
  • Охват публикаций: В среднем каждый пост получает 8 672 просмотров. В течение первых суток публикация набирает 2 110 просмотров.
  • Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 0.
  • Тематические интересы: Контент сосредоточен на ключевых темах, таких как database, learning, linkedin, udemy, 029k|.

📝 Описание и контентная политика

Автор описывает ресурс как площадку для выражения субъективного мнения:
“Learn how to analyze data effectively and manage databases with ease. Buy ads: https://telega.io/c/sql_databases”

Благодаря высокой частоте обновлений (последние данные получены 06 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.

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Архив постов
Data Science
Data Science
71 036
🖥Type of Databases
🖥Type of Databases

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

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

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Data Science
71 036
📱Data Science 📱Decision Intelligence: Data Stories

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🔅 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
71 036
🖥 8 Common database types explained
🖥 8 Common database types explained

Data Science
Data Science
71 036
📖 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
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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?

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

Data Science
Data Science
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🔅 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
71 036
📖 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
71 036
🖥 Tableau vs. Power BI
🖥 Tableau vs. Power BI

Data Science
Data Science
71 036
🖥 4 main database types
🖥 4 main database types

Data Science
Data Science
71 036
📱Data Science 📱How To Be a Lead Data Scientist

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Data Science
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🔅 How To Be a Lead Data Scientist 📝 Build a foundation and develop skills for seasoned data scientists to level up from mod
🔅 How To Be a Lead Data Scientist 📝 Build a foundation and develop skills for seasoned data scientists to level up from model builders to AI leaders. 🌐 Author: Matthew Blasa 🔰 Level: Advanced ⏰ Duration: 1h 6m 📋 Topics: Data Science, Team Management 🔗 Join Data Science for more courses

Data Science
Data Science
71 036
😉 A list of the best YouTube videos ✅ To learn data science 1️⃣ SQL language ⬅️ Learning 💰 4-hour SQL course from zero to one hundred 💰 Window functions tutorial ⬅️ Projects 📎 Starting your first SQL project 💰 Data cleansing project 💰 Restaurant order analysis ⬅️ Interview 💰 How to crack the SQL interview? ➖➖➖ 2️⃣ Python ⬅️ Learning 💰 12-hour Python for Data Science course ⬅️ Projects 💰 Python project for beginners 💰 Analyzing Corona Data with Python ⬅️ Interview 💰 Python interview golden tricks 💰 Python Interview Questions ➖➖➖ 3️⃣ Statistics and machine learning ⬅️ Learning 💰 7-hour course in applied statistics 💰 Machine Learning Training Playlist ⬅️ Projects 💰 Practical ML Project ⬅️ Interview 💰 ML Interview Questions and Answers 💰 How to pass a statistics interview? ➖➖➖ 4️⃣ Product and business case studies ⬅️ Learning 💰 Building strong product understanding 💰 Product Metric Definition ⬅️ Interview 💰 Case Study Analysis Framework 💰 How to shine in a business interview?

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🖥 Data Analyst Roadmap
🖥 Data Analyst Roadmap

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📖 Merging and Joining Data Working with multiple datasets? Combine them just like SQL: # Inner join (default) merged = pd.me
📖 Merging and Joining Data Working with multiple datasets? Combine them just like SQL: 
# Inner join (default)
merged = pd.merge(df_sales, df_customers, on='customer_id')

# Left join
pd.merge(df_sales, df_customers, on='customer_id', how='left')

# Concatenate vertically
all_data = pd.concat([df_2023, df_2024], ignore_index=True)

# Join on index
df1.join(df2, on='date')
This wraps up our Data Manipulation Using Pandas Series.

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📱Data Science 📱Ethical Hacking: SQL Injection

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🔅 Ethical Hacking: SQL Injection 📝 Learn about the SQL command language and SQL injections. Examine SQL injections in MySQL
🔅 Ethical Hacking: SQL Injection 📝 Learn about the SQL command language and SQL injections. Examine SQL injections in MySQL, SQL Server, and Oracle XE, and discover how attackers defeat web application firewalls. 🌐 Author: Malcolm Shore 🔰 Level: Intermediate ⏰ Duration: 1h 45m 📋 Topics: Ethical Hacking, SQL Injection 🔗 Join Data Science for more courses