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Perfect channel to learn Data Analytics Learn SQL, Python, Alteryx, Tableau, Power BI and many more For Promotions: @coderfun @love_data
Больше📈 Аналитический обзор Telegram-канала Data Analytics
Канал Data Analytics (@sqlspecialist) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 109 661 подписчиков, занимая 1 126 место в категории Технологии и приложения и 2 339 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 109 661 подписчиков.
Согласно последним данным от 23 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 529, а за последние 24 часа — 20, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.83%. В первые 24 часа после публикации контент обычно набирает 0.72% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 3 097 просмотров. В течение первых суток публикация набирает 784 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 8.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как row, sql, analytic, analyst, visualization.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Perfect channel to learn Data Analytics
Learn SQL, Python, Alteryx, Tableau, Power BI and many more
For Promotions: @coderfun @love_data”
Благодаря высокой частоте обновлений (последние данные получены 24 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 Технологии и приложения.
109 661
Подписчики
+2024 часа
-647 дней
+52930 день
Архив постов
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7 High-Impact Portfolio Project Ideas for Aspiring Data Analysts
✅ Sales Dashboard – Use Power BI or Tableau to visualize KPIs like revenue, profit, and region-wise performance
✅ Customer Churn Analysis – Predict which customers are likely to leave using Python (Logistic Regression, EDA)
✅ Netflix Dataset Exploration – Analyze trends in content types, genres, and release years with Pandas & Matplotlib
✅ HR Analytics Dashboard – Visualize attrition, department strength, and performance reviews
✅ Survey Data Analysis – Clean, visualize, and derive insights from user feedback or product surveys
✅ E-commerce Product Analysis – Analyze top-selling products, revenue by category, and return rates
✅ Airbnb Price Predictor – Use machine learning to predict listing prices based on location, amenities, and ratings
These projects showcase real-world skills and storytelling with data.
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What does the following SQL query return?
SELECT COUNT(email) FROM customers;
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📊 Aggregate Functions (COUNT, SUM, AVG, MIN, MAX)
Aggregate functions are used to perform calculations on multiple rows of a table and return a single value. They're mostly used with GROUP BY, but also work standalone.
1. COUNT()
Returns the number of rows.
Example:
SELECT COUNT(*) FROM employees;
Counts all employees in the table.
You can also count only non-null values in a column:
SELECT COUNT(email) FROM customers;
2. SUM()
Adds up all the values in a numeric column.
Example:
SELECT SUM(salary) FROM employees;
Gives you the total salary payout.
3. AVG()
Calculates the average value of a numeric column.
Example:
SELECT AVG(price) FROM products;
Finds the average product price.
4. MIN()
Returns the lowest value.
Example:
SELECT MIN(salary) FROM employees;
Finds the smallest salary.
5. MAX()
Returns the highest value.
Example:
SELECT MAX(salary) FROM employees;
Finds the highest salary in the table.
Bonus Example:
SELECT
COUNT(*) AS total_orders,
SUM(amount) AS total_revenue,
AVG(amount) AS avg_order_value
FROM orders;
This gives you a quick business summary: number of orders, total revenue, and average order value.
React with ❤️ if you're excited for the next topic: 👥 GROUP BY & HAVING Clauses.
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109 659
What will this query return?
SELECT * FROM customers WHERE city = 'Delhi' AND name LIKE 'A%';
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Let’s go to the next topic in our SQL Roadmap!
🔢 SQL Operators (IN, BETWEEN, LIKE, AND, OR)
These operators help you build flexible and powerful conditions inside your WHERE clause.
1. IN Operator
Used to match multiple values in a column.
Example:
SELECT * FROM customers WHERE city IN ('Delhi', 'Mumbai', 'Bangalore');
This fetches customers who live in any of the three cities.
2. BETWEEN Operator
Used to filter values within a range (inclusive).
Example:
SELECT * FROM orders WHERE order_date BETWEEN '2024-01-01' AND '2024-12-31';
Returns all orders placed in 2024.
3. LIKE Operator
Used for pattern matching. Especially useful with wildcards (%).
Example:
SELECT * FROM customers WHERE name LIKE 'A%';
Finds customers whose names start with "A".
Another example:
SELECT * FROM emails WHERE address LIKE '%@gmail.com';
Finds all Gmail users.
4. AND Operator
Combines multiple conditions — all must be true.
Example:
SELECT * FROM employees WHERE department = 'HR' AND salary > 50000;
Finds HR employees earning more than 50,000.
5. OR Operator
Returns results if any one condition is true.
Example:
SELECT * FROM products WHERE category = 'Electronics' OR category = 'Books';
Fetches products that belong to either of the two categories.
Pro Tip:
Combine these operators for complex logic!
SELECT * FROM orders
WHERE status = 'Delivered'
AND delivery_date BETWEEN '2025-01-01' AND '2025-03-31';
React with ❤️ if you're ready for the next one: 📊 Aggregate Functions (COUNT, SUM, AVG, MIN, MAX).
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
109 659
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109 659
What will this query return?
SELECT name FROM employees ORDER BY salary DESC LIMIT 1;
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Let’s move on to the next topic in our SQL Roadmap!
✏️ Filtering & Sorting Data (ORDER BY, LIMIT)
1. ORDER BY Clause:
ORDER BY is used to sort the result set based on one or more columns — either in ascending or descending order.
Syntax:
SELECT column1, column2 FROM table_name ORDER BY column1 ASC|DESC;
Example:
SELECT name, salary FROM employees ORDER BY salary DESC;
This lists employees with the highest salaries at the top.
By default, it sorts in ascending (ASC) order if no direction is specified.
2. LIMIT Clause:
LIMIT is used to restrict the number of rows returned by a query. Super useful when you want just a sample or the top results.
Syntax:
SELECT * FROM table_name LIMIT number;
Example:
SELECT * FROM products LIMIT 5;
This fetches only the first 5 products.
You can also combine ORDER BY and LIMIT:
SELECT * FROM products ORDER BY price DESC LIMIT 3;
This gets the top 3 most expensive products.
Quick Recap:
Use ORDER BY to sort your data
Use LIMIT to control how many results you get
React with ❤️ if you're excited for the next one: 🔢 SQL Operators (IN, BETWEEN, LIKE, AND, OR).
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109 659
What does the following SQL query do?
SELECT * FROM products WHERE price > 1000;
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Moving on to next topic!
🔍 Basic SQL Queries (SELECT, WHERE)
1. SELECT Statement:
The SELECT command is used to retrieve data from a table. It’s the most fundamental query in SQL.
Syntax:
SELECT column1, column2 FROM table_name;
Example:
SELECT name, email FROM customers;
This fetches the name and email of all customers from the customers table.
You can also use * to select all columns:
SELECT * FROM customers;
2. WHERE Clause:
The WHERE clause is used to filter records that meet a specific condition.
Syntax:
SELECT column1, column2 FROM table_name WHERE condition;
Example:
SELECT name FROM customers WHERE city = 'Delhi';
This returns names of all customers who are from Delhi.
Another example using numbers:
SELECT * FROM products WHERE price > 1000;
This gets all products priced above 1000.
Key Point:
SELECT fetches data
WHERE filters it based on conditions
React with ❤️ if you're ready for the next one: ✏️ Filtering & Sorting Data (ORDER BY, LIMIT).
I keep quizzes after the explanation to understand you're really understanding each concept
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
109 659
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109 659
In a relational database, what is the main purpose of a foreign key?
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Awesome! Let’s dive into the next one:
🧱 Database Concepts (Tables, Rows, Columns, Keys)
1. Table:
A table is the basic structure where data is stored in a relational database. Think of it like a spreadsheet. Each table represents one type of entity — for example, a Customers table or a Products table.
2. Rows (Records):
Each row in a table represents a single record or entry.
Example: A row in the Customers table could represent one customer’s details like their name, email, and phone number.
3. Columns (Fields):
Columns represent the attributes or properties of the data.
Example: In a Products table, columns might be product_id, product_name, price, and category.
4. Keys:
Keys are special columns that help in uniquely identifying rows and establishing relationships between tables.
Primary Key (PK): Uniquely identifies each record in a table. It must be unique and not null.
Example: customer_id in a Customers table.
Foreign Key (FK): A field in one table that refers to the primary key in another table. It’s used to link tables together.
Example: customer_id in an Orders table links to the Customers table.
Real-World Analogy:
Imagine a school:
The "Student" table holds data about each student.
Each row is one student.
Each column is an attribute like name, roll number, or class.
The primary key might be roll_number.
A foreign key might be class_id that links to a Classes table.
React with ❤️ to keep the momentum going!
Next up: 🔍 Basic SQL Queries (SELECT, WHERE).
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
109 659
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109 659
Which type of database is best suited for complex JOIN operations?
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Let's go to our next topic now
📄 SQL vs NoSQL
1. What is SQL (Relational) Database?
SQL databases are structured and use tables (rows and columns) to store data. They follow a strict schema, meaning the data format is predefined.
Examples: MySQL, PostgreSQL, SQLite, SQL Server
Used For: Applications where data integrity and relationships are important, like banking systems or e-commerce platforms.
2. What is NoSQL (Non-Relational) Database?
NoSQL databases are more flexible and can store unstructured or semi-structured data like JSON or key-value pairs. They don’t require a fixed schema.
Examples: MongoDB, Redis, Firebase, Cassandra
Used For: Real-time applications, large-scale data, or when rapid development and scalability are more important than structure.
Key Differences:
Data Format: SQL uses tables; NoSQL uses documents or key-value pairs.
Schema: SQL is strict; NoSQL is flexible.
Scalability: SQL scales vertically (strong server); NoSQL scales horizontally (more servers).
Use Case: SQL is great for complex queries and transactions; NoSQL excels in high-volume, real-time scenarios.
React with ❤️ to keep going! Up next: 🧱 Database Concepts (Tables, Rows, Columns, Keys).
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
