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

Сітка:Data Analytics Індія2 339 Технології та додатки1 126...

📈 Аналітичний огляд Telegram-каналу Data Analytics

Канал Data Analytics (@sqlspecialist) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 109 661 підписників, посідаючи 1 126 місце в категорії Технології та додатки та 2 339 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 109 661 підписників.

За останніми даними від 23 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 529, а за останні 24 години на 20, загальне охоплення залишається високим.

Статус верифікації: Не верифікований
Рівень залученості (ER): Середній показник залученості аудиторії становить 2.83%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.72% реакцій від загальної кількості підписників.
Охоплення публікацій: В середньому кожен допис отримує 3 097 переглядів. Протягом першої доби публікація в середньому набирає 784 переглядів.
Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 8.
Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як row, sql, analytic, analyst, visualization.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Perfect channel to learn Data Analytics Learn SQL, Python, Alteryx, Tableau, Power BI and many more For Promotions: @coderfun @love_data”

Завдяки високій частоті оновлень (останні дані отримано 24 червня, 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 Технології та додатки.

109 661

Підписники

+2024 години

-647 днів

+52930 день

3 097

Перегляди допису

~ 78424 години

~ 1 03248 годин

2.83%

Коефіцієнт залучення

~ 2

Дописів на день

Ads index

beta

Архів дописів

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Glad to see the amazing response Let me go through each topic one by one 🔰 Introduction to Databases & SQL What is a Database? A database is an organized collection of data that allows for easy access, management, and updating. Think of it like a digital filing system. Types of Databases: 1. Relational Databases – Store data in tables (like Excel). Examples: MySQL, PostgreSQL, SQL Server. 2. Non-Relational (NoSQL) – Store data as documents, key-value pairs, etc. Examples: MongoDB, Redis. What is SQL? Structured Query Language (SQL) is the standard language used to communicate with relational databases. It allows you to create, read, update, and delete data — often remembered by the acronym CRUD. Why Learn SQL? SQL is foundational for data analysis, data science, backend development, and database administration. It’s used across industries to manage and analyze large volumes of data. Real-World Example: Imagine you're a data analyst at a retail company. SQL helps you answer questions like: "How many orders were placed in the last 30 days?" "What’s the average purchase value by city?" React with ❤️ if you’re ready for the next one: 📄 SQL vs NoSQL! Share with credits: https://t.me/sqlspecialist Hope it helps :)

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𝐅𝐑𝐄𝐄 𝐌𝐚𝐬𝐭𝐞𝐫𝐜𝐥𝐚𝐬𝐬 𝐎𝐧 𝐋𝐚𝐭𝐞𝐬𝐭 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬😍 - AI/ML - Data Analytics - Business Analytics - Data Science - Fullstack - UI/UX - DevOps 🚀 3 Steps to Build Future-Proof Your IT Career! 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐍𝐨𝐰 👇:- https://pdlink.in/4j9x7Os (Limited Slots ..HurryUp🏃‍♂️ ) 𝐃𝐚𝐭𝐞 & 𝐓𝐢𝐦𝐞:-11th April 2025, at 7 PM Don't Miss This Opportunity 🤗

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🔰 SQL Roadmap for Beginners 2025 ├── 🗃 Introduction to Databases & SQL ├── 📄 SQL vs NoSQL (Just Basics) ├── 🧱 Database Concepts (Tables, Rows, Columns, Keys) ├── 🔍 Basic SQL Queries (SELECT, WHERE) ├── ✏️ Filtering & Sorting Data (ORDER BY, LIMIT) ├── 🔢 SQL Operators (IN, BETWEEN, LIKE, AND, OR) ├── 📊 Aggregate Functions (COUNT, SUM, AVG, MIN, MAX) ├── 👥 GROUP BY & HAVING Clauses ├── 🔗 SQL JOINS (INNER, LEFT, RIGHT, FULL, SELF) ├── 📦 Subqueries & Nested Queries ├── 🏷 Aliases & Case Statements ├── 🧾 Views & Indexes (Basics) ├── 🧠 Common Table Expressions (CTEs) ├── 🔄 Window Functions (ROW_NUMBER, RANK, PARTITION BY) ├── ⚙️ Data Manipulation (INSERT, UPDATE, DELETE) ├── 🧱 Data Definition (CREATE, ALTER, DROP) ├── 🔐 Constraints & Relationships (PK, FK, UNIQUE, CHECK) ├── 🧪 Real-world SQL Scenarios & Challenges Like for detailed explanation ❤️ #sql

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What does the following SQL query return? SELECT COUNT(DISTINCT department) FROM employees;

Anonymous voting

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10 Data Analyst Interview Questions You Should Be Ready For (2025) ✅ Explain the difference between INNER JOIN and LEFT JOIN. ✅ What are window functions in SQL? Give an example. ✅ How do you handle missing or duplicate data in a dataset? ✅ Describe a situation where you derived insights that influenced a business decision. ✅ What’s the difference between correlation and causation? ✅ How would you optimize a slow SQL query? ✅ Explain the use of GROUP BY and HAVING in SQL. ✅ How do you choose the right chart for a dataset? ✅ What’s the difference between a dashboard and a report? ✅ Which libraries in Python do you use for data cleaning and analysis? Like for the detailed answers for above questions ❤️ Share with credits: https://t.me/sqlspecialist Hope it helps :)

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𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗣𝗿𝗲𝗺𝗶𝘂𝗺 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 Skills you will gain:- - Introduction to GenAI - Chatgpt - Prompt design - AI for business solutions - Prompt Engineering - Python 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/41VIuSA Enroll Now & Get a course completion certificate🎓

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Which of the following is not an aggregate function in SQL?

Anonymous voting

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7 Must-Have Tools for Data Analysts in 2025: ✅ SQL – Still the #1 skill for querying and managing structured data ✅ Excel / Google Sheets – Quick analysis, pivot tables, and essential calculations ✅ Python (Pandas, NumPy) – For deep data manipulation and automation ✅ Power BI – Transform data into interactive dashboards ✅ Tableau – Visualize data patterns and trends with ease ✅ Jupyter Notebook – Document, code, and visualize all in one place ✅ Looker Studio – A free and sleek way to create shareable reports with live data. Perfect blend of code, visuals, and storytelling. React with ❤️ for free tutorials on each tool Share with credits: https://t.me/sqlspecialist Hope it helps :)

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𝗟𝗲𝗮𝗿𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 & 𝗘𝗹𝗲𝘃𝗮𝘁𝗲 𝗬𝗼𝘂𝗿 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗚𝗮𝗺𝗲!😍 Want to turn raw data into stunning visual stories?📊 Here are 6 FREE Power BI courses that’ll take you from beginner to pro—without spending a single rupee💰 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4cwsGL2 Enjoy Learning ✅️

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9 tips to learn Python for Data Analysis: 🐍 Start with the basics: variables, loops, functions 🧹 Master Pandas for data manipulation 🔢 Use NumPy for numerical operations 📊 Visualize data with Matplotlib and Seaborn 📂 Work with real datasets (CSV, Excel, APIs) 🧼 Clean and preprocess messy data 📈 Understand basic statistics and correlations ⚙️ Automate repetitive analysis tasks with scripts 💡 Build mini-projects to apply your skills Free Python Resources: https://t.me/pythonanalyst Like for more daily tips 👍 ♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)

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Python CheatSheet 📚 ✅ 1. Basic Syntax - Print Statement: print("Hello, World!") - Comments: # This is a comment 2. Data Types - Integer: x = 10 - Float: y = 10.5 - String: name = "Alice" - List: fruits = ["apple", "banana", "cherry"] - Tuple: coordinates = (10, 20) - Dictionary: person = {"name": "Alice", "age": 25} 3. Control Structures - If Statement:

     if x > 10:
         print("x is greater than 10")

- For Loop:

     for fruit in fruits:
         print(fruit)

- While Loop:

     while x < 5:
         x += 1

4. Functions - Define Function:

     def greet(name):
         return f"Hello, {name}!"

- Lambda Function: add = lambda a, b: a + b 5. Exception Handling - Try-Except Block:

     try:
         result = 10 / 0
     except ZeroDivisionError:
         print("Cannot divide by zero.")

6. File I/O - Read File:

     with open('file.txt', 'r') as file:
         content = file.read()

- Write File:

     with open('file.txt', 'w') as file:
         file.write("Hello, World!")

7. List Comprehensions - Basic Example: squared = [x**2 for x in range(10)] - Conditional Comprehension: even_squares = [x**2 for x in range(10) if x % 2 == 0] 8. Modules and Packages - Import Module: import math - Import Specific Function: from math import sqrt 9. Common Libraries - NumPy: import numpy as np - Pandas: import pandas as pd - Matplotlib: import matplotlib.pyplot as plt 10. Object-Oriented Programming - Define Class:

      class Dog:
          def __init__(self, name):
              self.name = name
          def bark(self):
              return "Woof!"

11. Virtual Environments - Create Environment: python -m venv myenv - Activate Environment: - Windows: myenv\Scripts\activate - macOS/Linux: source myenv/bin/activate 12. Common Commands - Run Script: python script.py - Install Package: pip install package_name - List Installed Packages: pip list This Python checklist serves as a quick reference for essential syntax, functions, and best practices to enhance your coding efficiency! Checklist for Data Analyst: https://dataanalytics.beehiiv.com/p/data Here you can find essential Python Interview Resources👇 https://t.me/DataSimplifier Like for more resources like this 👍 ♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)

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𝟰 𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 These free, Microsoft-backed courses are a game-changer! With these resources, you’ll gain the skills and confidence needed to shine in the data analytics world—all without spending a penny. 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/4jpmI0I Enroll For FREE & Get Certified🎓

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Must-Know Power BI Charts & When to Use Them 1. Bar/Column Chart Use for: Comparing values across categories Example: Sales by region, revenue by product 2. Line Chart Use for: Trends over time Example: Monthly website visits, stock price over years 3. Pie/Donut Chart Use for: Showing proportions of a whole Example: Market share by brand, budget distribution 4. Table/Matrix Use for: Detailed data display with multiple dimensions Example: Sales by product and month, performance by employee and region 5. Card/KPI Use for: Displaying single important metrics Example: Total Revenue, Current Month’s Profit 6. Area Chart Use for: Showing cumulative trends Example: Cumulative sales over time 7. Stacked Bar/Column Chart Use for: Comparing total and subcategories Example: Sales by region and product category 8. Clustered Bar/Column Chart Use for: Comparing multiple series side-by-side Example: Revenue and Profit by product 9. Waterfall Chart Use for: Visualizing increment/decrement over a value Example: Profit breakdown – revenue, costs, taxes 10. Scatter Chart Use for: Relationship between two numerical values Example: Marketing spend vs revenue, age vs income 11. Funnel Chart Use for: Showing steps in a process Example: Sales pipeline, user conversion funnel 12. Treemap Use for: Hierarchical data in a nested format Example: Sales by category and sub-category 13. Gauge Chart Use for: Progress toward a goal Example: % of sales target achieved Hope it helps :) #powerbi

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10 SQL Concepts Every Data Analyst Should Master 👇 ✅ SELECT, WHERE, ORDER BY – Core of querying your data ✅ JOINs (INNER, LEFT, RIGHT, FULL) – Combine data from multiple tables ✅ GROUP BY & HAVING – Aggregate and filter grouped data ✅ Subqueries – Nest queries inside queries for complex logic ✅ CTEs (Common Table Expressions) – Write cleaner, reusable SQL logic ✅ Window Functions – Perform advanced analytics like rankings & running totals ✅ Indexes – Boost your query performance ✅ Normalization – Structure your database efficiently ✅ UNION vs UNION ALL – Combine result sets with or without duplicates ✅ Stored Procedures & Functions – Reusable logic inside your DB React with ❤️ if you want me to cover each topic in detail

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𝗚𝗼𝗼𝗴𝗹𝗲 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 Learn AI for FREE with these incredible courses by Google! Whether you’re a beginner or looking to sharpen your skills, these resources will help you stay ahead in the tech game. 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/3FYbfGR Enroll For FREE & Get Certified🎓

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Which of the following is not a recommend practice while writing SQL code?

Anonymous voting