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Data Analytics

Data Analytics

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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

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๐Ÿ“ˆ Analytical overview of Telegram channel Data Analytics

Channel Data Analytics (@sqlspecialist) in the English language segment is an active participant. Currently, the community unites 109 661 subscribers, ranking 1 126 in the Technologies & Applications category and 2 339 in the India region.

๐Ÿ“Š Audience metrics and dynamics

Since its creation on ะฝะตะฒั–ะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 109 661 subscribers.

According to the latest data from 23 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 529 over the last 30 days and by 20 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.83%. Within the first 24 hours after publication, content typically collects 0.72% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 3 097 views. Within the first day, a publication typically gains 784 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 8.
  • Thematic interests: Content is focused on key topics such as row, sql, analytic, analyst, visualization.

๐Ÿ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
โ€œPerfect channel to learn Data Analytics Learn SQL, Python, Alteryx, Tableau, Power BI and many more For Promotions: @coderfun @love_dataโ€

Thanks to the high frequency of updates (latest data received on 24 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 Technologies & Applications category.

109 661
Subscribers
+2024 hours
-647 days
+52930 days
Posts Archive
7 High-Impact Portfolio Project Ideas for Aspiring Data Analysts โœ… Sales Dashboard โ€“ Use Power BI or Tableau to visualize KPIs like revenue, profit, and region-wise performance โœ… Customer Churn Analysis โ€“ Predict which customers are likely to leave using Python (Logistic Regression, EDA) โœ… Netflix Dataset Exploration โ€“ Analyze trends in content types, genres, and release years with Pandas & Matplotlib โœ… HR Analytics Dashboard โ€“ Visualize attrition, department strength, and performance reviews โœ… Survey Data Analysis โ€“ Clean, visualize, and derive insights from user feedback or product surveys โœ… E-commerce Product Analysis โ€“ Analyze top-selling products, revenue by category, and return rates โœ… Airbnb Price Predictor โ€“ 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;
Anonymous voting

๐Ÿ“Š 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 โค๏ธ if you're excited for the next topic: ๐Ÿ‘ฅ GROUP BY & HAVING Clauses.

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What will this query return? SELECT * FROM customers WHERE city = 'Delhi' AND name LIKE 'A%';
Anonymous voting

Letโ€™s go to the next topic in our SQL Roadmap! ๐Ÿ”ข 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 โ€” 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 โค๏ธ if you're ready for the next one: ๐Ÿ“Š Aggregate Functions (COUNT, SUM, AVG, MIN, MAX). Share with credits: https://t.me/sqlspecialist Hope it helps :)

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What will this query return? SELECT name FROM employees ORDER BY salary DESC LIMIT 1;
Anonymous voting

Letโ€™s move on to the next topic in our SQL Roadmap! โœ๏ธ 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 โ€” 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 โค๏ธ if you're excited for the next one: ๐Ÿ”ข SQL Operators (IN, BETWEEN, LIKE, AND, OR).

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What does the following SQL query do? SELECT * FROM products WHERE price > 1000;
Anonymous voting

Moving on to next topic! ๐Ÿ” Basic SQL Queries (SELECT, WHERE) 1. SELECT Statement: The SELECT command is used to retrieve data from a table. Itโ€™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 โค๏ธ if you're ready for the next one: โœ๏ธ 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 :)

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In a relational database, what is the main purpose of a foreign key?
Anonymous voting

Awesome! Letโ€™s dive into the next one: ๐Ÿงฑ 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 โ€” 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 customerโ€™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. Itโ€™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 โค๏ธ to keep the momentum going! Next up: ๐Ÿ” Basic SQL Queries (SELECT, WHERE). Share with credits: https://t.me/sqlspecialist Hope it helps :)

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Which type of database is best suited for complex JOIN operations?
Anonymous voting

Let's go to our next topic now ๐Ÿ“„ 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 donโ€™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 โค๏ธ to keep going! Up next: ๐Ÿงฑ Database Concepts (Tables, Rows, Columns, Keys). Share with credits: https://t.me/sqlspecialist Hope it helps :)