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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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📈 Аналітичний огляд Telegram-каналу Data Science

Канал Data Science (@sql_databases) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 70 805 підписників, посідаючи 2 274 місце в категорії Освіта та 4 582 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 70 805 підписників.

За останніми даними від 25 серпня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на -309, а за останні 24 години на -33, загальне охоплення залишається високим.

  • Статус верифікації: Не верифікований
  • Рівень залученості (ER): Середній показник залученості аудиторії становить 12.05%. Протягом перших 24 годин після публікації контент зазвичай збирає 2.78% реакцій від загальної кількості підписників.
  • Охоплення публікацій: В середньому кожен допис отримує 8 533 переглядів. Протягом першої доби публікація в середньому набирає 1 972 переглядів.
  • Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 0.
  • Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як database, learning, linkedin, udemy, 029k|.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
Learn how to analyze data effectively and manage databases with ease. Buy ads: https://telega.io/c/sql_databases

Завдяки високій частоті оновлень (останні дані отримано 26 серпня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.

70 805
Підписники
-3324 години
-1127 днів
-30930 день
Архів дописів
📱Data Science 📱How To Be a Lead Data Scientist

🔅 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

😉 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?

🖥 Data Analyst Roadmap
🖥 Data Analyst Roadmap

📖 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.

📱Data Science 📱Ethical Hacking: SQL Injection

🔅 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

SQL
+5
SQL

SQL is way easier when you actually know what matters. These are the core basics every beginner needs to build projects, answ
+5
SQL is way easier when you actually know what matters. These are the core basics every beginner needs to build projects, answer real business questions, and stop feeling overwhelmed 📊 Master these first and everything else becomes 10x easier. Save this to review later ✅

📖 SQL Learning Roadmap — 8 Key Steps: 1. Basic: Start by understanding what SQL is, why it’s used, and the different types o
📖 SQL Learning Roadmap — 8 Key Steps: 1. Basic: Start by understanding what SQL is, why it’s used, and the different types of SQL commands (DDL, DML, DCL, TCL). This builds your foundation. 2. Queries: Learn how to fetch data using commands like SELECT, FROM, WHERE, ORDER BY, and LIMIT. Practice filtering data with operators such as =, !=, LIKE, IN, and BETWEEN. 3. Joins: To work with multiple tables, you must understand INNER, LEFT, RIGHT, and FULL OUTER JOIN. Know how primary and foreign keys relate tables. 4. Functions: Use built-in functions like COUNT, SUM, AVG, MIN, and MAX for data analysis. Learn how to group data using GROUP BY and filter groups with HAVING. 5. Subqueries: Write queries within queries! Learn scalar, correlated, and multi-row subqueries. They’re powerful for solving complex data problems. 6. Data Manipulation: Master how to change data using INSERT, UPDATE, and DELETE. Also, understand transactions using BEGIN, COMMIT, and ROLLBACK to maintain data integrity. 7. Advanced: Take it further with window functions (ROW_NUMBER, RANK, LEAD, LAG), CTEs (WITH), views, and indexing to write efficient and optimized queries. 8. Practice: The final step is consistent practice. Work with real-world datasets, focus on query optimization, and solve challenges on platforms like LeetCode, Mode, or HackerRank.

📖 4 Main in Database Types
📖 4 Main in Database Types

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

🔅 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 Visualisation CheatSheet
📖 Data Visualisation CheatSheet

📖 Data Analyst
📖 Data Analyst

📖 MOST COMMON SQL INTERVIEW QUESTION Do you knew this? 👉 “What is the order of execution in an SQL query?” Don’t let the SE
📖 MOST COMMON SQL INTERVIEW QUESTION Do you knew this? 👉 “What is the order of execution in an SQL query?” Don’t let the SELECT fool you – it’s NOT the first step! 😮 Here’s the correct order that SQL follows behind the scenes: 🔢 SQL Order of Execution: 1️⃣ FROM 2️⃣ JOIN 3️⃣ WHERE 4️⃣ GROUP BY 5️⃣ HAVING 6️⃣ SELECT 7️⃣ DISTINCT 8️⃣ ORDER BY 9️⃣ LIMIT / OFFSET 🔥 Pro tip: Interviewers LOVE this question to test your SQL fundamentals! Memorize it, understand it – and impress in your next interview. 💼

📦 Exercise Files

📱Data Science 📱PostgreSQL Essential Training

🔅 PostgreSQL Essential Training 📝 Learn how to set up and work with one of the worlds most popular open-source database pla
🔅 PostgreSQL Essential Training 📝 Learn how to set up and work with one of the worlds most popular open-source database platforms, PostgreSQL. 🌐 Author: Adam Wilbert 🔰 Level: Intermediate ⏰ Duration: 3h 18m 📋 Topics: PostgreSQL 🔗 Join Data Science for more courses