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📈 Analytical overview of Telegram channel Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources

Channel Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources (@sqlproject) in the English language segment is an active participant. Currently, the community unites 39 681 subscribers, ranking 4 600 in the Education category and 9 817 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 39 681 subscribers.

According to the latest data from 27 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 37 over the last 30 days and by -1 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 1.80%. Within the first 24 hours after publication, content typically collects 0.74% reactions from the total number of subscribers.
Post reach: On average, each post receives 716 views. Within the first day, a publication typically gains 292 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 2.
Thematic interests: Content is focused on key topics such as analytic, dataset, visualization, sql, learning.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Covering all technical and popular stuff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. Ads/ Promo: @love_data”

Thanks to the high frequency of updates (latest data received on 28 August, 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 Education category.

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39 681

Subscribers

-124 hours

-407 days

+3730 days

716

Post views

~ 29224 hours

~ 40448 hours

1.80%

Engagement rate

~ 1

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🔥 𝗙𝘂𝗹𝗹𝘀𝘁𝗮𝗰𝗸 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗙𝗥𝗘𝗘 𝗗𝗲𝗺𝗼 𝗖𝗹𝗮𝘀𝘀 𝗶𝗻 𝗣𝘂𝗻𝗲! 😍 Want to crack a job at top tech companies? - Master Fullstack Development from the Top 1% Instructors (IITs & Top MNCs) 💡 Why Join? ✅ 500+ Hiring Partners ✅ 100% Placement Assistance ✅ 60+ Hiring Drives Every Month ✅ Real-time Projects & Mentorship 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗡𝗼𝘄👇 :- https://pdlink.in/3YA32zi 📢 Hurry! Limited seats available.

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𝗨𝗽𝘀𝗸𝗶𝗹𝗹 𝗙𝗮𝘀𝘁: 𝗟𝗲𝗮𝗿𝗻 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 𝘄𝗶𝘁𝗵 𝗣𝗿𝗼𝗷𝗲𝗰𝘁-𝗕𝗮𝘀𝗲𝗱 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗶𝗻 𝗝𝘂𝘀𝘁 𝟯𝟬 𝗗𝗮𝘆𝘀!😍 Level up your tech skills in just 30 days! 💻👨‍🎓 Whether you’re a beginner, student, or planning a career switch, this platform offers project-based courses👨‍💻✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3U2nBl4 Start today and you’ll be 10x more confident by the end of it!✅️

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𝗟𝗲𝗮𝗿𝗻 𝗚𝗲𝗻𝗔𝗜 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘 , 𝗘𝗮𝗿𝗻 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲𝘀 & 𝗠𝗮𝗸𝗲 𝗬𝗼𝘂𝗿 𝗖𝗼𝗹𝗹𝗲𝗴𝗲 𝗜𝗻𝗱𝗶𝗮’𝘀 𝗔𝗜 𝗖𝗵𝗮𝗺𝗽𝗶𝗼𝗻😍 Join the #GreatLearningAIChallenge | 🗓️ 13th–15th July 🎁 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂 𝗚𝗲𝘁:- ✅ Certificates worth ₹40,000 – Absolutely FREE ✅ Internship Opportunity at Great Learning ✅ Top 10 students from winning colleges get Third Wave Coffee vouchers ☕ 🏆 More participants = Higher rank for your college! 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐅𝐨𝐫 𝐅𝐑𝐄𝐄 👇:- https://pdlink.in/4ksaynS Get your classmates to join & win BIG together!🎓

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𝗛𝗮𝗿𝘃𝗮𝗿𝗱 𝗝𝘂𝘀𝘁 𝗥𝗲𝗹𝗲𝗮𝘀𝗲𝗱 𝟱 𝗙𝗥𝗘𝗘 𝗧𝗲𝗰𝗵 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻’𝘁 𝗠𝗶𝘀𝘀 𝗶𝗻 𝟮𝟬𝟮𝟱!😍 🚨 Harvard just dropped 5 FREE online tech courses — no fees, no catches!📌 Whether you’re just starting out or upskilling for a tech career, this is your chance to learn from one of the world’s top universities — for FREE. 🌍 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4eA368I 💡Learn at your own pace, earn certificates, and boost your resume✅️

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SQL isn't easy! It’s the powerful language that helps you manage and manipulate data in databases. To truly master SQL, focus on these key areas: 0. Understanding the Basics: Get comfortable with SQL syntax, data types, and basic queries like SELECT, INSERT, UPDATE, and DELETE. 1. Mastering Data Retrieval: Learn advanced SELECT statements, including JOINs, GROUP BY, HAVING, and subqueries to retrieve complex datasets. 2. Working with Aggregation Functions: Use functions like COUNT(), SUM(), AVG(), MIN(), and MAX() to summarize and analyze data efficiently. 3. Optimizing Queries: Understand how to write efficient queries and use techniques like indexing and query execution plans for performance optimization. 4. Creating and Managing Databases: Master CREATE, ALTER, and DROP commands for building and maintaining database structures. 5. Understanding Constraints and Keys: Learn the importance of primary keys, foreign keys, unique constraints, and indexes for data integrity. 6. Advanced SQL Techniques: Dive into CASE statements, CTEs (Common Table Expressions), window functions, and stored procedures for more powerful querying. 7. Normalizing Data: Understand database normalization principles and how to design databases to avoid redundancy and ensure consistency. 8. Handling Transactions: Learn how to use BEGIN, COMMIT, and ROLLBACK to manage transactions and ensure data integrity. 9. Staying Updated with SQL Trends: The world of databases evolves—stay informed about new SQL functions, database management systems (DBMS), and best practices. ⏳ With practice, hands-on experience, and a thirst for learning, SQL will empower you to unlock the full potential of data! You can read detailed article here I've curated essential SQL Interview Resources👇 https://t.me/DataSimplifier Share with credits: https://t.me/sqlspecialist Hope it helps :)

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𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗪𝗲𝗯𝗶𝗻𝗮𝗿 | 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘😍 A Guide to a Career in Data Science : Tools, Skills, and Career Fundamentals - Learn how How MAANG Companies Use Data Science in Their Daily Business - Get a step-by-step guide on how to start building the expertise companies are hiring for. Eligibility :- Students,Freshers & Woking Professionals 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐅𝐨𝐫 𝐅𝐑𝐄𝐄 👇:- https://pdlink.in/3TwjLjZ (Limited Slots ..HurryUp🏃‍♂️ ) 𝐃𝐚𝐭𝐞 & 𝐓𝐢𝐦𝐞:- July 11, 2025 , at 7 PM

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🔢 PostgresSQL CRUD tutorial

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𝗪𝗮𝗻𝘁 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗜𝗻-𝗗𝗲𝗺𝗮𝗻𝗱 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 — 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 — 𝗗𝗶𝗿𝗲𝗰𝘁𝗹𝘆 𝗳𝗿𝗼𝗺 𝗚𝗼𝗼𝗴𝗹𝗲?😍 Whether you’re a student, job seeker, or just hungry to upskill — these 5 beginner-friendly courses are your golden ticket🎟️ No fluff. No fees. Just career-boosting knowledge and certificates that make your resume pop✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/42vL6br Enjoy Learning ✅️

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🔍 Real-World Data Analyst Tasks & How to Solve Them As a Data Analyst, your job isn’t just about writing SQL queries or making dashboards—it’s about solving business problems using data. Let’s explore some common real-world tasks and how you can handle them like a pro! 📌 Task 1: Cleaning Messy Data Before analyzing data, you need to remove duplicates, handle missing values, and standardize formats. ✅ Solution (Using Pandas in Python):

import pandas as pd  
df = pd.read_csv('sales_data.csv')  
df.drop_duplicates(inplace=True)  # Remove duplicate rows  
df.fillna(0, inplace=True)  # Fill missing values with 0  
print(df.head())

💡 Tip: Always check for inconsistent spellings and incorrect date formats! 📌 Task 2: Analyzing Sales Trends A company wants to know which months have the highest sales. ✅ Solution (Using SQL):

SELECT MONTH(SaleDate) AS Month, SUM(Quantity * Price) AS Total_Revenue  
FROM Sales  
GROUP BY MONTH(SaleDate)  
ORDER BY Total_Revenue DESC;

💡 Tip: Try adding YEAR(SaleDate) to compare yearly trends! 📌 Task 3: Creating a Business Dashboard Your manager asks you to create a dashboard showing revenue by region, top-selling products, and monthly growth. ✅ Solution (Using Power BI / Tableau): 👉 Add KPI Cards to show total sales & profit 👉 Use a Line Chart for monthly trends 👉 Create a Bar Chart for top-selling products 👉 Use Filters/Slicers for better interactivity 💡 Tip: Keep your dashboards clean, interactive, and easy to interpret! Like this post for more content like this ♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)

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Complete Data Analyst Interview Guide (0–2 Years of Experience) 🔹 Round 1: SQL + Scenario-Based Questions Q1. Get top 3 products by revenue within each category

SELECT *
FROM (
  SELECT p.product_id, p.category, SUM(o.revenue) AS total_revenue,
         RANK() OVER(PARTITION BY p.category ORDER BY SUM(o.revenue) DESC) AS rnk
  FROM products p
  JOIN orders o ON p.product_id = o.product_id
  GROUP BY p.product_id, p.category
) ranked
WHERE rnk <= 3;

Q2. Find users who purchased in January but not in February

SELECT DISTINCT user_id
FROM orders
WHERE MONTH(order_date) = 1
AND user_id NOT IN (
  SELECT user_id FROM orders WHERE MONTH(order_date) = 2
);

Q3. Avg. ride time by city + peak hours

SELECT city, AVG(DATEDIFF(MINUTE, start_time, end_time)) AS avg_ride_mins
FROM trips
GROUP BY city;

-- For peak hour detection (example logic)
SELECT DATEPART(HOUR, start_time) AS ride_hour, COUNT(*) AS ride_count
FROM trips
GROUP BY DATEPART(HOUR, start_time)
ORDER BY ride_count DESC;

⸻ 🔹 Round 2: Python + Data Cleaning Q1. Clean messy CSV with pandas

import pandas as pd

df = pd.read_csv('data.csv')
df.columns = df.columns.str.strip().str.lower()
df.drop_duplicates(inplace=True)
df['date'] = pd.to_datetime(df['date'], errors='coerce')
df.fillna(method='ffill', inplace=True)

Q2. Extract domain names from email IDs

emails = ['abc@gmail.com', 'xyz@outlook.com']
domains = [email.split('@')[1] for email in emails]

Q3. Difference: .loc[] vs .iloc[] • .loc[] → label-based selection • .iloc[] → index-based selection Q4. Handle outliers using IQR

Q1 = df['column'].quantile(0.25)
Q3 = df['column'].quantile(0.75)
IQR = Q3 - Q1
filtered_df = df[(df['column'] >= Q1 - 1.5*IQR) & (df['column'] <= Q3 + 1.5*IQR)]

⸻ 🔹 Round 3: Power BI / Dashboarding Tasks you should know: • Create a dashboard with weekly trends, margins, churn % • Use bookmarks/slicers for KPI toggles • Apply filters to show top 5 items dynamically • Exclude visuals from slicer using “Edit Interactions” → turn off filter icon on card visual 🔗 Try replicating dashboards from Power BI Gallery ⸻ 🔹 Round 4: Business Case + Logic-Based Thinking Q1. Sales dropped last quarter — what to check? • Compare YoY/QoQ data • Identify categories/geos with the biggest drop • Analyze order volume vs. avg. order value • Check marketing spend, discounts, stockouts Q2. App downloads ⬆️, activity ⬇️ — what’s wrong? • Check Day 1/7/30 retention • Is onboarding working? • UI bugs or crashes? • Compare install → sign-up → usage funnel Q3. Returns increasing — how to investigate? • Analyze return % by brand, category, SKU • Check return reasons (defects, sizing, etc.) • Compare returners’ order history • Seasonal impact? ⸻ 🔰 Free Practice Tools: • 🔹 SQL on LeetCode • 🔹 Python on Hackerrank • 🔹 Power BI Gallery

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𝟯𝟬+ 𝗙𝗥𝗘𝗘 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲𝗔𝗜 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 India's Biggest AI Challenge (13th To 15th July ) , Earn Free certificates & Boost your resume! 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:- https://pdlink.in/3Gx7lW7 Enroll For FREE & Become an AI Champion🏆

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SQL Joins – Essential Concepts 🚀 1️⃣ What Are SQL Joins? SQL Joins are used to combine rows from two or more tables based on a related column. 2️⃣ Types of Joins INNER JOIN: Returns only matching rows from both tables. SELECT * FROM TableA INNER JOIN TableB ON TableA.id = TableB.id; LEFT JOIN (LEFT OUTER JOIN): Returns all rows from the left table and matching rows from the right table. SELECT * FROM TableA LEFT JOIN TableB ON TableA.id = TableB.id; RIGHT JOIN (RIGHT OUTER JOIN): Returns all rows from the right table and matching rows from the left table. SELECT * FROM TableA RIGHT JOIN TableB ON TableA.id = TableB.id; FULL JOIN (FULL OUTER JOIN): Returns all rows when there is a match in either table. SELECT * FROM TableA FULL JOIN TableB ON TableA.id = TableB.id; 3️⃣ Self Join A table joins with itself to compare rows. SELECT A.name, B.name FROM Employees A JOIN Employees B ON A.manager_id = B.id; 4️⃣ Cross Join Returns the Cartesian product of both tables (every row from Table A pairs with every row from Table B). SELECT * FROM TableA CROSS JOIN TableB; 5️⃣ Joins with Multiple Conditions Using multiple columns for matching. SELECT * FROM TableA INNER JOIN TableB ON TableA.id = TableB.id AND TableA.type = TableB.type; 6️⃣ Using Aliases in Joins Shortens table names for better readability. SELECT A.name, B.salary FROM Employees A INNER JOIN Salaries B ON A.id = B.emp_id; 7️⃣ Handling NULLs in Joins Use COALESCE(column, default_value) to replace NULL values. IS NULL to filter unmatched rows in LEFT or RIGHT JOINs. Free SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v React with ❤️ for free resources Share with credits: https://t.me/sqlspecialist Hope it helps :)

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𝗪𝗮𝗻𝘁 𝘁𝗼 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗶𝗻 𝟮𝟬𝟮𝟱? 𝗛𝗲𝗿𝗲'𝘀 𝗬𝗼𝘂𝗿 𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗮𝘁𝗵!😍 Skip the pricey courses — and start learning with these 5 YouTube playlists that cover everything from Excel and SQL to Power BI and real-world portfolio projects👨‍💻 Whether you’re a student, career switcher, or just brushing up for interviews, this list will give you all the tools you need — step by step.📊📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4eAK4Pv Save this post & start watching today.✅️

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10 Coding Project Ideas to Boost Your Portfolio ✅ To-Do List App – Practice CRUD operations and UI/UX basics ✅ Weather App (API) – Learn to work with real-time APIs ✅ Blog Website – Build full-stack with auth, CMS, and comments ✅ Portfolio Website – Showcase your skills and projects professionally ✅ Expense Tracker – Handle forms, charts, and local storage ✅ Chat App – Real-time messaging using WebSockets or Firebase ✅ Movie Recommendation System – Intro to ML with collaborative filtering ✅ E-commerce Store – Simulate cart, checkout, payment logic ✅ SQL Dashboard with Power BI/Tableau – Combine backend + data viz skills ✅ AI Chatbot – Use NLP libraries like spaCy or transformers Python Projects: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a ENJOY LEARNING 👍👍

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𝗧𝗼𝗽 𝗠𝗡𝗖𝘀 𝗛𝗶𝗿𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁𝘀 | 𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄😍 - Infosys - Genpact - IBM - Virtusa - S&P Global Job Location:- Across India Qualification:- Graduate/Post Graduate Salary Range :- 5 To 21LPA 𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄👇 :- https://bit.ly/44qMX2k Select your experience & Complete The Registration Process Once your profile shortlisted , you will get call letter from recruiters

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𝗙𝗿𝗲𝗲 𝗔𝗜 & 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗖𝗼𝘂𝗿𝘀𝗲 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀😍 Want to explore AI & Machine Learning but don’t know where to start — or don’t want to spend ₹₹₹ on it?👨‍💻 Learn the foundations of AI, machine learning basics, data handling, and real-world use cases in just a few hours.📊📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/401SWry This 100% FREE course is designed just for beginners — whether you’re a student, fresher, or career switcher✅️

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Importance of AI in Data Analytics AI is transforming the way data is analyzed and insights are generated. Here's how AI adds value in data analytics: 1. Automated Data Cleaning AI helps in detecting anomalies, missing values, and outliers automatically, improving data quality and saving analysts hours of manual work. 2. Faster & Smarter Decision Making AI models can process massive datasets in seconds and suggest actionable insights, enabling real-time decision-making. 3. Predictive Analytics AI enables forecasting future trends and behaviors using machine learning models (e.g., sales predictions, churn forecasting). 4. Natural Language Processing (NLP) AI can analyze unstructured data like reviews, feedback, or comments using sentiment analysis, keyword extraction, and topic modeling. 5. Pattern Recognition AI uncovers hidden patterns, correlations, and clusters in data that traditional analysis may miss. 6. Personalization & Recommendation AI algorithms power recommendation systems (like on Netflix, Amazon) that personalize user experiences based on behavioral data. 7. Data Visualization Enhancement AI auto-generates dashboards, chooses best chart types, and highlights key anomalies or insights without manual intervention. 8. Fraud Detection & Risk Analysis AI models detect fraud and mitigate risks in real-time using anomaly detection and classification techniques. 9. Chatbots & Virtual Analysts AI-powered tools like ChatGPT allow users to interact with data using natural language, removing the need for technical skills. 10. Operational Efficiency AI automates repetitive tasks like report generation, data transformation, and alerts—freeing analysts to focus on strategy. Share with credits: https://t.me/sqlspecialist Hope it helps :) #dataanalytics