اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Data Engineers
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نمایش بیشتر📈 تحلیل کانال تلگرام Data Engineers
کانال Data Engineers (@sql_engineer) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 10 421 مشترک است و جایگاه 19 167 را در دسته آموزش و رتبه 38 949 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 10 421 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 23 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 189 و در ۲۴ ساعت گذشته برابر 9 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 14.46% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً N/A% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 0 بازدید دریافت میکند. در اولین روز معمولاً 0 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 0 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند sql, learning, analytic, engineer, link:- تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“Free Data Engineering Ebooks & Courses”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 24 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته آموزش تبدیل کردهاند.
10 421
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| تاریخ | رشد مشترکین | اشارات | کانالها | |
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| 01 ژوئن | +5 |
پستهای کانال
🚀Greetings from PVR Cloud Tech!! 🌈
🔥 Do you want to become a Master in Azure Cloud Data Engineering?
If you're ready to build in-demand skills and unlock exciting career opportunities, this is the perfect place to start!
📌 Start Date: 1st June 2026
⏰ Time: 09 PM – 10 PM IST | Monday
🔗 𝐈𝐧𝐭𝐞𝐫𝐞𝐬𝐭𝐞𝐝 𝐢𝐧 𝐀𝐳𝐮𝐫𝐞 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐥𝐢𝐯𝐞 𝐬𝐞𝐬𝐬𝐢𝐨𝐧𝐬?
👉 Message us on WhatsApp:
https://wa.me/917032678595?text=Interested_to_join_Azure_Data_Engineering_live_sessions
🔹 Course Content:
https://drive.google.com/file/d/1QKqhRMHx2SDNDTmPAf3₅4fA6LljKHm6/view
📱 Join WhatsApp Group:
https://chat.whatsapp.com/EZghn5PVmryDgJZ1TjIMRk
📥 Register Now:
https://forms.gle/LidHPdfxvNeg9LpeA
Team
PVR Cloud Tech :)
+91-9346060794
| 2 | 🚀 Top Skills Every Data Engineer Should Learn 📊🔥
🧠 1. SQL Mastery
✔ Complex Queries
✔ JOINS & Window Functions
✔ Query Optimization
✔ Data Modeling
✔ Stored Procedures
🐍 2. Programming Skills
✔ Python for Automation
✔ APIs & JSON
✔ Data Processing Scripts
✔ Error Handling
🛠 Libraries to Learn:
✔ Pandas
✔ PySpark
✔ Requests
⚡ 3. ETL & Data Pipelines
✔ Extract, Transform, Load
✔ Workflow Automation
✔ Scheduling Jobs
✔ Monitoring Pipelines
🛠 Tools to Learn:
✔ Apache Airflow
✔ dbt
✔ Prefect
☁️ 4. Cloud Platforms
✔ Cloud Storage
✔ Data Lakes
✔ Scalable Processing
✔ Cloud Security Basics
🛠 Platforms to Learn:
✔ AWS
✔ Microsoft Azure
✔ Google Cloud Platform
📊 5. Big Data Technologies
✔ Distributed Computing
✔ Real-Time Streaming
✔ Batch Processing
✔ Scalable Systems
🛠 Technologies to Learn:
✔ Apache Spark
✔ Hadoop
✔ Apache Kafka
🗄 6. Databases & Warehousing
✔ Relational Databases
✔ NoSQL Databases
✔ Data Warehouses
✔ Schema Design
🛠 Databases to Learn:
✔ PostgreSQL
✔ MongoDB
✔ Snowflake
✔ BigQuery
🔄 7. DevOps & Deployment
✔ Version Control
✔ Containerization
✔ CI/CD Basics
✔ Deployment Automation
🛠 Tools to Learn:
✔ Git
✔ Docker
✔ Kubernetes
💡 Data Engineers don’t just move data… they build the backbone of modern AI & analytics systems.
💬 Tap ❤️ if this helped you! | 1 636 |
| 3 | 📈 FREE Live Masterclass for Future Business Analysts!
📊 4 Steps to Become a Successful Business Analyst in 2026
📅 May 20th, 2026
⏰ 7:00 PM
🌐 English
🎟️ 90 Minutes of Career Guidance & Industry Insights
💡 Learn:
✔ Core Business Analytics Skills & AI usage
✔ Real-World Case Studies
✔ Career Roadmap for 2026
✔ Tools Used by Top Companies
🔥 Perfect for:
Students | Freshers | Working Professionals | Career Switchers
📌 Register Now:
https://rebrand.ly/Business-analyst-webinar | 1 549 |
| 4 | What is the difference between data scientist, data engineer, data analyst and business intelligence?
🧑🔬 Data Scientist
Focus: Using data to build models, make predictions, and solve complex problems.
Cleans and analyzes data
Builds machine learning models
Answers “Why is this happening?” and “What will happen next?”
Works with statistics, algorithms, and coding (Python, R)
Example: Predict which customers are likely to cancel next month
🛠️ Data Engineer
Focus: Building and maintaining the systems that move and store data.
Designs and builds data pipelines (ETL/ELT)
Manages databases, data lakes, and warehouses
Ensures data is clean, reliable, and ready for others to use
Uses tools like SQL, Airflow, Spark, and cloud platforms (AWS, Azure, GCP)
Example: Create a system that collects app data every hour and stores it in a warehouse
📊 Data Analyst
Focus: Exploring data and finding insights to answer business questions.
Pulls and visualizes data (dashboards, reports)
Answers “What happened?” or “What’s going on right now?”
Works with SQL, Excel, and tools like Tableau or Power BI
Less coding and modeling than a data scientist
Example: Analyze monthly sales and show trends by region
📈 Business Intelligence (BI) Professional
Focus: Helping teams and leadership understand data through reports and dashboards.
Designs dashboards and KPIs (key performance indicators)
Translates data into stories for non-technical users
Often overlaps with data analyst role but more focused on reporting
Tools: Power BI, Looker, Tableau, Qlik
Example: Build a dashboard showing company performance by department
🧩 Summary Table
Data Scientist - What will happen? Tools: Python, R, ML tools, predictions & models
Data Engineer - How does the data move and get stored? Tools: SQL, Spark, cloud tools, infrastructure & pipelines
Data Analyst - What happened? Tools: SQL, Excel, BI tools, reports & exploration
BI Professional - How can we see business performance clearly? Tools: Power BI, Tableau, dashboards & insights for decision-makers
🎯 In short:
Data Engineers build the roads.
Data Scientists drive smart cars to predict traffic.
Data Analysts look at traffic data to see patterns.
BI Professionals show everyone the traffic report on a screen. | 1 849 |
| 5 | ✅ Skills Required to Become a Data Engineer ⚙️🚀
🧠 PROGRAMMING
1. Python (Data Pipelines)
2. Java / Scala
3. Object-Oriented Programming
4. Scripting (Automation)
5. Debugging Skills
6. Code Optimization
7. API Handling
8. Version Control (Git)
🗄️ DATABASES
1. SQL (Advanced Queries)
2. NoSQL (MongoDB, Cassandra)
3. Database Design
4. Data Modeling
5. Indexing Partitioning
6. Query Optimization
7. Data Warehousing
8. OLTP vs OLAP
⚙️ ETL / ELT
1. Data Extraction
2. Data Transformation
3. Data Loading
4. Pipeline Building
5. Workflow Automation
6. Data Integration
7. Batch Processing
8. Real-time Processing
☁️ BIG DATA TECHNOLOGIES
1. Hadoop
2. Spark
3. Kafka
4. Hive
5. Flink
6. Distributed Systems
7. Cluster Computing
8. Stream Processing
☁️ CLOUD PLATFORMS
1. AWS (S3, Redshift, Glue)
2. Azure (Data Factory, Synapse)
3. Google Cloud (BigQuery)
4. Cloud Storage
5. Serverless Architecture
6. Data Lakes
7. Security IAM
8. Cost Optimization
📊 DATA PIPELINES
1. Building Scalable Pipelines
2. Data Orchestration (Airflow)
3. Scheduling Jobs
4. Monitoring Pipelines
5. Error Handling
6. Logging Systems
7. Data Reliability
8. Performance Tuning
🧱 DATA ARCHITECTURE
1. Data Lakes
2. Data Warehouses
3. Lakehouse Architecture
4. Schema Design
5. Data Governance
6. Data Security
7. Metadata Management
8. Scalability Planning
🔍 DEVOPS TOOLS
1. Docker
2. Kubernetes
3. CI/CD Pipelines
4. Linux Basics
5. Shell Scripting
6. Git GitHub
7. Monitoring Tools
8. Infrastructure as Code
💬 Tap ❤️ if this helped you follow for more Data Engineering content! | 1 874 |
| 6 |  Every day you login... Work.. and logout.
Days become months.
Months become years.
But nothing changes.
Same role. Same work. Same pay.
Meanwhile, others are moving into Cloud & Data Engineering…
building real systems and earning better.
If you are looking to get into Azure Data Engineering then..
𝗝𝗼𝗶𝗻 𝘁𝗵𝗲 3 months 𝗟𝗶𝘃𝗲 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
📌 Start Date: 20th April 2026
⏰ Time: 9 PM – 10 PM IST | Monday
👉 𝐌𝐞𝐬𝐬𝐚𝐠𝐞 𝐮𝐬 𝐨𝐧 𝐖𝐡𝐚𝐭𝐬𝐀𝐩𝐩:
https://wa.me/917032678595?text=Interested_to_join_Azure_Data_Engineering_live_sessions
🔹 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲:
https://forms.gle/DRXEhvyG9ENDsNYR9
🎟️ 𝗝𝗼𝗶𝗻 𝗪𝗵𝗮𝘁𝘀𝗔𝗽𝗽 𝗚𝗿𝗼𝘂𝗽:
https://chat.whatsapp.com/GCG3Si7vhrJD1evV9NAbhL
🏀 𝗖𝗼𝘂𝗿𝘀𝗲 𝗖𝗼𝗻𝘁𝗲𝗻𝘁:
https://drive.google.com/file/d/1QKqhRMHx2SDNDTmPAf3_54fA6LljKHm6/view | 514 |
| 7 | 🧠 SQL Interview Question (Running Total of Sales)
📌
sales(order_id, order_date, amount)
❓ Ques :
👉 Calculate the running total of sales for each day
👉 Return order_date, daily_sales, running_total
🧩 How Interviewers Expect You to Think
• Aggregate sales per day 📊
• Use window function for cumulative sum
• Order data correctly for running calculation
💡 SQL Solution
WITH daily_sales AS (
SELECT
order_date,
SUM(amount) AS daily_sales
FROM sales
GROUP BY order_date
)
SELECT
order_date,
daily_sales,
SUM(daily_sales) OVER (
ORDER BY order_date
) AS running_total
FROM daily_sales;
🔥 Why This Question Is Powerful
• Tests window functions (must-know) 🧠
• Very common in real-world reporting
• Frequently asked in analyst & BI roles
❤️ React for more SQL interview questions 🚀 | 1 994 |
| 8 |  🔰 Python function with an example | 1 709 |
