๐น ๐ฅ Pro Tips for Aspiring Data Engineers
1. Learn SQL deeply โ it's still the foundation of everything
2. Understand data formats: JSON, Parquet, Avro, ORC
3. Master Apache Spark โ it's everywhere
4. Learn to use Airflow for orchestrating workflows
5. Practice writing ETL pipelines โ build your own mini data warehouse
6. Get comfortable with cloud platforms (start with AWS/GCP free tiers)
7. Version-control your work using Git + DVC for data versioning
8. Learn Docker & Kubernetes basics โ modern data infra depends on it
9. Explore real-time processing: Kafka, Flink, and Spark Streaming
10. Follow best practices for data modeling โ star/snowflake schemas, SCDs, etc
1. Learn SQL deeply โ it's still the foundation of everything
2. Understand data formats: JSON, Parquet, Avro, ORC
3. Master Apache Spark โ it's everywhere
4. Learn to use Airflow for orchestrating workflows
5. Practice writing ETL pipelines โ build your own mini data warehouse
6. Get comfortable with cloud platforms (start with AWS/GCP free tiers)
7. Version-control your work using Git + DVC for data versioning
8. Learn Docker & Kubernetes basics โ modern data infra depends on it
9. Explore real-time processing: Kafka, Flink, and Spark Streaming
10. Follow best practices for data modeling โ star/snowflake schemas, SCDs, etc
โค3
Forwarded from Python Projects & Resources
๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ถ๐ป ๐๐๐๐ ๐ฏ ๐ ๐ผ๐ป๐๐ต๐ ๐๐ถ๐๐ต ๐ง๐ต๐ถ๐ ๐๐ฟ๐ฒ๐ฒ ๐๐ถ๐๐๐๐ฏ ๐ฅ๐ผ๐ฎ๐ฑ๐บ๐ฎ๐ฝ๐
๐ฏ Want to Master Data Science in Just 3 Months?๐
Feeling overwhelmed by the sheer volume of resources and donโt know where to start? Youโre not alone๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/43uHPrX
This FREE GitHub roadmap is a game-changer for anyoneโ ๏ธ
๐ฏ Want to Master Data Science in Just 3 Months?๐
Feeling overwhelmed by the sheer volume of resources and donโt know where to start? Youโre not alone๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/43uHPrX
This FREE GitHub roadmap is a game-changer for anyoneโ ๏ธ
โค1
Learning and Practicing SQL: Resources and Platforms
1. https://sqlbolt.com/
2. https://sqlzoo.net/
3. https://www.codecademy.com/learn/learn-sql
4. https://www.w3schools.com/sql/
5. https://www.hackerrank.com/domains/sql
6. https://www.windowfunctions.com/
7. https://selectstarsql.com/
8. https://quip.com/2gwZArKuWk7W
9. https://leetcode.com/problemset/database/
10. http://thedatamonk.com/
1. https://sqlbolt.com/
2. https://sqlzoo.net/
3. https://www.codecademy.com/learn/learn-sql
4. https://www.w3schools.com/sql/
5. https://www.hackerrank.com/domains/sql
6. https://www.windowfunctions.com/
7. https://selectstarsql.com/
8. https://quip.com/2gwZArKuWk7W
9. https://leetcode.com/problemset/database/
10. http://thedatamonk.com/
โค3๐1
๐ Mastering Spark: 20 Interview Questions Demystified!
1๏ธโฃ MapReduce vs. Spark: Learn how Spark achieves 100x faster performance compared to MapReduce.
2๏ธโฃ RDD vs. DataFrame: Unravel the key differences between RDD and DataFrame, and discover what makes DataFrame unique.
3๏ธโฃ DataFrame vs. Datasets: Delve into the distinctions between DataFrame and Datasets in Spark.
4๏ธโฃ RDD Operations: Explore the various RDD operations that power Spark.
5๏ธโฃ Narrow vs. Wide Transformations: Understand the differences between narrow and wide transformations in Spark.
6๏ธโฃ Shared Variables: Discover the shared variables that facilitate distributed computing in Spark.
7๏ธโฃ Persist vs. Cache: Differentiate between the persist and cache functionalities in Spark.
8๏ธโฃ Spark Checkpointing: Learn about Spark checkpointing and how it differs from persisting to disk.
9๏ธโฃ SparkSession vs. SparkContext: Understand the roles of SparkSession and SparkContext in Spark applications.
๐ spark-submit Parameters: Explore the parameters to specify in the spark-submit command.
1๏ธโฃ1๏ธโฃ Cluster Managers in Spark: Familiarize yourself with the different types of cluster managers available in Spark.
1๏ธโฃ2๏ธโฃ Deploy Modes: Learn about the deploy modes in Spark and their significance.
1๏ธโฃ3๏ธโฃ Executor vs. Executor Core: Distinguish between executor and executor core in the Spark ecosystem.
1๏ธโฃ4๏ธโฃ Shuffling Concept: Gain insights into the shuffling concept in Spark and its importance.
1๏ธโฃ5๏ธโฃ Number of Stages in Spark Job: Understand how to decide the number of stages created in a Spark job.
1๏ธโฃ6๏ธโฃ Spark Job Execution Internals: Get a peek into how Spark internally executes a program.
1๏ธโฃ7๏ธโฃ Direct Output Storage: Explore the possibility of directly storing output without sending it back to the driver.
1๏ธโฃ8๏ธโฃ Coalesce and Repartition: Learn about the applications of coalesce and repartition in Spark.
1๏ธโฃ9๏ธโฃ Physical and Logical Plan Optimization: Uncover the optimization techniques employed in Spark's physical and logical plans.
2๏ธโฃ0๏ธโฃ Treereduce and Treeaggregate: Discover why treereduce and treeaggregate are preferred over reduceByKey and aggregateByKey in certain scenarios.
Data Engineering Interview Preparation Resources: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C
1๏ธโฃ MapReduce vs. Spark: Learn how Spark achieves 100x faster performance compared to MapReduce.
2๏ธโฃ RDD vs. DataFrame: Unravel the key differences between RDD and DataFrame, and discover what makes DataFrame unique.
3๏ธโฃ DataFrame vs. Datasets: Delve into the distinctions between DataFrame and Datasets in Spark.
4๏ธโฃ RDD Operations: Explore the various RDD operations that power Spark.
5๏ธโฃ Narrow vs. Wide Transformations: Understand the differences between narrow and wide transformations in Spark.
6๏ธโฃ Shared Variables: Discover the shared variables that facilitate distributed computing in Spark.
7๏ธโฃ Persist vs. Cache: Differentiate between the persist and cache functionalities in Spark.
8๏ธโฃ Spark Checkpointing: Learn about Spark checkpointing and how it differs from persisting to disk.
9๏ธโฃ SparkSession vs. SparkContext: Understand the roles of SparkSession and SparkContext in Spark applications.
๐ spark-submit Parameters: Explore the parameters to specify in the spark-submit command.
1๏ธโฃ1๏ธโฃ Cluster Managers in Spark: Familiarize yourself with the different types of cluster managers available in Spark.
1๏ธโฃ2๏ธโฃ Deploy Modes: Learn about the deploy modes in Spark and their significance.
1๏ธโฃ3๏ธโฃ Executor vs. Executor Core: Distinguish between executor and executor core in the Spark ecosystem.
1๏ธโฃ4๏ธโฃ Shuffling Concept: Gain insights into the shuffling concept in Spark and its importance.
1๏ธโฃ5๏ธโฃ Number of Stages in Spark Job: Understand how to decide the number of stages created in a Spark job.
1๏ธโฃ6๏ธโฃ Spark Job Execution Internals: Get a peek into how Spark internally executes a program.
1๏ธโฃ7๏ธโฃ Direct Output Storage: Explore the possibility of directly storing output without sending it back to the driver.
1๏ธโฃ8๏ธโฃ Coalesce and Repartition: Learn about the applications of coalesce and repartition in Spark.
1๏ธโฃ9๏ธโฃ Physical and Logical Plan Optimization: Uncover the optimization techniques employed in Spark's physical and logical plans.
2๏ธโฃ0๏ธโฃ Treereduce and Treeaggregate: Discover why treereduce and treeaggregate are preferred over reduceByKey and aggregateByKey in certain scenarios.
Data Engineering Interview Preparation Resources: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C
โค1
Forwarded from Artificial Intelligence
๐ง๐ผ๐ฝ ๐๐ผ๐บ๐ฝ๐ฎ๐ป๐ถ๐ฒ๐ ๐๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐๐๐
๐๐ฝ๐ฝ๐น๐ ๐๐ถ๐ป๐ธ๐:-๐
S&P Global :- https://pdlink.in/3ZddwVz
IBM :- https://pdlink.in/4kDmMKE
TVS Credit :- https://pdlink.in/4mI0JVc
Sutherland :- https://pdlink.in/4mGYBgg
Other Jobs :- https://pdlink.in/44qEIDu
Apply before the link expires ๐ซ
๐๐ฝ๐ฝ๐น๐ ๐๐ถ๐ป๐ธ๐:-๐
S&P Global :- https://pdlink.in/3ZddwVz
IBM :- https://pdlink.in/4kDmMKE
TVS Credit :- https://pdlink.in/4mI0JVc
Sutherland :- https://pdlink.in/4mGYBgg
Other Jobs :- https://pdlink.in/44qEIDu
Apply before the link expires ๐ซ
๐ฐ ๐๐ฟ๐ฒ๐ฒ ๐ฃ๐๐๐ต๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐๐ผ ๐๐ผ๐ผ๐๐ ๐ฌ๐ผ๐๐ฟ ๐ฅ๐ฒ๐๐๐บ๐ฒ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ๐
Want to Boost Your Resume with In-Demand Python Skills?๐จโ๐ป
In todayโs tech-driven world, Python is one of the most in-demand programming languages across data science, software development, and machine learning๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Hnx3wh
Enjoy Learning โ ๏ธ
Want to Boost Your Resume with In-Demand Python Skills?๐จโ๐ป
In todayโs tech-driven world, Python is one of the most in-demand programming languages across data science, software development, and machine learning๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Hnx3wh
Enjoy Learning โ ๏ธ
Forwarded from Generative AI
๐ ๐ฎ๐๐๐ฒ๐ฟ ๐ฒ ๐๐ป-๐๐ฒ๐บ๐ฎ๐ป๐ฑ ๐ฆ๐ธ๐ถ๐น๐น๐ ๐ณ๐ผ๐ฟ ๐๐ฅ๐๐!๐
Want to boost your career with highly sought-after tech skills? These 6 YouTube channels will help you learn from scratch!๐จโ๐ป
No need for expensive coursesโstart learning for FREE today!๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Ddxd7P
Donโt miss this opportunityโstart learning today and take your skills to the next level!โ ๏ธ
Want to boost your career with highly sought-after tech skills? These 6 YouTube channels will help you learn from scratch!๐จโ๐ป
No need for expensive coursesโstart learning for FREE today!๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Ddxd7P
Donโt miss this opportunityโstart learning today and take your skills to the next level!โ ๏ธ
๐ฆ๐ค๐ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐ฟ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐๐
SQL is the backbone of data analytics. Whether youโre cleaning data, generating reports, or exploring trendsโSQL helps you turn raw information into actionable insights.
๐๐ข๐ง๐ค๐:-
https://pdlink.in/43lI7CO
Use ChatGPT like a developer โ not just a casual userโ ๏ธ
SQL is the backbone of data analytics. Whether youโre cleaning data, generating reports, or exploring trendsโSQL helps you turn raw information into actionable insights.
๐๐ข๐ง๐ค๐:-
https://pdlink.in/43lI7CO
Use ChatGPT like a developer โ not just a casual userโ ๏ธ
Kavitha's Journey to become a Data Engineer ๐๐
1. Startup to Dream Job Journey:
- Started at a startup in India, transitioned to Infosys, then grabbed UK opportunity.
- Shifted from legacy Mainframe to AWS Cloud, pursued Master's from illinoisstateu, and secured dream job at Statefarm.
2. Learn Fundamentals:
- Assess skills, understand role.
- Gain proficiency in Python, SQL.
- Learn data technologies.
3. Database and Modeling Skills:
- Understand databases, gain proficiency.
- Learn data modeling principles.
4. Master ETL, Warehousing, and Visualization:
- Understand ETL, data warehousing.
- Gain experience in building warehouses.
- Familiarize with visualization tools.
- Got Certified as AWS Solutions Architect.
5. Utilize LinkedIn for Job Search:
- Network and connect with professionals.
- Showcase skills and achievements.
- Utilize job search feature, leading to dream job at Statefarm.
Data Engineering Interview Preparation Resources: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C
1. Startup to Dream Job Journey:
- Started at a startup in India, transitioned to Infosys, then grabbed UK opportunity.
- Shifted from legacy Mainframe to AWS Cloud, pursued Master's from illinoisstateu, and secured dream job at Statefarm.
2. Learn Fundamentals:
- Assess skills, understand role.
- Gain proficiency in Python, SQL.
- Learn data technologies.
3. Database and Modeling Skills:
- Understand databases, gain proficiency.
- Learn data modeling principles.
4. Master ETL, Warehousing, and Visualization:
- Understand ETL, data warehousing.
- Gain experience in building warehouses.
- Familiarize with visualization tools.
- Got Certified as AWS Solutions Architect.
5. Utilize LinkedIn for Job Search:
- Network and connect with professionals.
- Showcase skills and achievements.
- Utilize job search feature, leading to dream job at Statefarm.
Data Engineering Interview Preparation Resources: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C
โค1
Forwarded from Python Projects & Resources
๐ฑ ๐ ๐๐๐-๐๐ผ๐น๐น๐ผ๐ ๐ฌ๐ผ๐๐ง๐๐ฏ๐ฒ ๐๐ต๐ฎ๐ป๐ป๐ฒ๐น๐ ๐ณ๐ผ๐ฟ ๐๐๐ฝ๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐๐ถ๐๐๐ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ๐
Want to Become a Data Scientist in 2025? Start Here!๐ฏ
If youโre serious about becoming a Data Scientist in 2025, the learning doesnโt have to be expensive โ or boring!๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4kfBR5q
Perfect for beginners and aspiring prosโ ๏ธ
Want to Become a Data Scientist in 2025? Start Here!๐ฏ
If youโre serious about becoming a Data Scientist in 2025, the learning doesnโt have to be expensive โ or boring!๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4kfBR5q
Perfect for beginners and aspiring prosโ ๏ธ
โค1
Kavitha's Journey to become a Data Engineer ๐๐
1. Startup to Dream Job Journey:
- Started at a startup in India, transitioned to Infosys, then grabbed UK opportunity.
- Shifted from legacy Mainframe to AWS Cloud, pursued Master's from illinoisstateu, and secured dream job at Statefarm.
2. Learn Fundamentals:
- Assess skills, understand role.
- Gain proficiency in Python, SQL.
- Learn data technologies.
3. Database and Modeling Skills:
- Understand databases, gain proficiency.
- Learn data modeling principles.
4. Master ETL, Warehousing, and Visualization:
- Understand ETL, data warehousing.
- Gain experience in building warehouses.
- Familiarize with visualization tools.
- Got Certified as AWS Solutions Architect.
5. Utilize LinkedIn for Job Search:
- Network and connect with professionals.
- Showcase skills and achievements.
- Utilize job search feature, leading to dream job at Statefarm.
Data Engineering Interview Preparation Resources: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C
1. Startup to Dream Job Journey:
- Started at a startup in India, transitioned to Infosys, then grabbed UK opportunity.
- Shifted from legacy Mainframe to AWS Cloud, pursued Master's from illinoisstateu, and secured dream job at Statefarm.
2. Learn Fundamentals:
- Assess skills, understand role.
- Gain proficiency in Python, SQL.
- Learn data technologies.
3. Database and Modeling Skills:
- Understand databases, gain proficiency.
- Learn data modeling principles.
4. Master ETL, Warehousing, and Visualization:
- Understand ETL, data warehousing.
- Gain experience in building warehouses.
- Familiarize with visualization tools.
- Got Certified as AWS Solutions Architect.
5. Utilize LinkedIn for Job Search:
- Network and connect with professionals.
- Showcase skills and achievements.
- Utilize job search feature, leading to dream job at Statefarm.
Data Engineering Interview Preparation Resources: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C
Greetings from PVR Cloud Tech!! ๐
๐ Course : Azure Data Engineering
๐ Time : 8:00 PM to 9:00 PM IST
Duration : 3 months
Day-1 : Introduction To Azure Data Engineering Recording
https://drive.google.com/file/d/10BxpB-DcNW4901EpMqrsEWYpHVqufonS/view?usp=sharing
โ Registration link:
https://forms.gle/nQb1q8aJPHsdPmNQ8
Cheers๐
Team PVR Cloud Tech :)
+91-9346060794
๐ Course : Azure Data Engineering
๐ Time : 8:00 PM to 9:00 PM IST
Duration : 3 months
Day-1 : Introduction To Azure Data Engineering Recording
https://drive.google.com/file/d/10BxpB-DcNW4901EpMqrsEWYpHVqufonS/view?usp=sharing
โ Registration link:
https://forms.gle/nQb1q8aJPHsdPmNQ8
Cheers๐
Team PVR Cloud Tech :)
+91-9346060794
โค3
Forwarded from Artificial Intelligence
๐ ๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ผ๐บ๐ฝ๐๐๐ฒ๐ฟ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ณ๐ผ๐ฟ ๐๐ฟ๐ฒ๐ฒ ๐ณ๐ฟ๐ผ๐บ ๐๐ฎ๐ฟ๐๐ฎ๐ฟ๐ฑ, ๐ฆ๐๐ฎ๐ป๐ณ๐ผ๐ฟ๐ฑ, ๐ ๐๐ง & ๐๐ผ๐ผ๐ด๐น๐ฒ๐
Why pay thousands when you can access world-class Computer Science courses for free? ๐
Top institutions like Harvard, Stanford, MIT, and Google offer high-quality learning resources to help you master in-demand tech skills๐จโ๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3ZyQpFd
Perfect for students, self-learners, and career switchersโ ๏ธ
Why pay thousands when you can access world-class Computer Science courses for free? ๐
Top institutions like Harvard, Stanford, MIT, and Google offer high-quality learning resources to help you master in-demand tech skills๐จโ๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3ZyQpFd
Perfect for students, self-learners, and career switchersโ ๏ธ
Python Detailed Roadmap ๐
๐ 1. Basics
โผ Data Types & Variables
โผ Operators & Expressions
โผ Control Flow (if, loops)
๐ 2. Functions & Modules
โผ Defining Functions
โผ Lambda Functions
โผ Importing & Creating Modules
๐ 3. File Handling
โผ Reading & Writing Files
โผ Working with CSV & JSON
๐ 4. Object-Oriented Programming (OOP)
โผ Classes & Objects
โผ Inheritance & Polymorphism
โผ Encapsulation
๐ 5. Exception Handling
โผ Try-Except Blocks
โผ Custom Exceptions
๐ 6. Advanced Python Concepts
โผ List & Dictionary Comprehensions
โผ Generators & Iterators
โผ Decorators
๐ 7. Essential Libraries
โผ NumPy (Arrays & Computations)
โผ Pandas (Data Analysis)
โผ Matplotlib & Seaborn (Visualization)
๐ 8. Web Development & APIs
โผ Web Scraping (BeautifulSoup, Scrapy)
โผ API Integration (Requests)
โผ Flask & Django (Backend Development)
๐ 9. Automation & Scripting
โผ Automating Tasks with Python
โผ Working with Selenium & PyAutoGUI
๐ 10. Data Science & Machine Learning
โผ Data Cleaning & Preprocessing
โผ Scikit-Learn (ML Algorithms)
โผ TensorFlow & PyTorch (Deep Learning)
๐ 11. Projects
โผ Build Real-World Applications
โผ Showcase on GitHub
๐ 12. โ Apply for Jobs
โผ Strengthen Resume & Portfolio
โผ Prepare for Technical Interviews
Like for more โค๏ธ๐ช
๐ 1. Basics
โผ Data Types & Variables
โผ Operators & Expressions
โผ Control Flow (if, loops)
๐ 2. Functions & Modules
โผ Defining Functions
โผ Lambda Functions
โผ Importing & Creating Modules
๐ 3. File Handling
โผ Reading & Writing Files
โผ Working with CSV & JSON
๐ 4. Object-Oriented Programming (OOP)
โผ Classes & Objects
โผ Inheritance & Polymorphism
โผ Encapsulation
๐ 5. Exception Handling
โผ Try-Except Blocks
โผ Custom Exceptions
๐ 6. Advanced Python Concepts
โผ List & Dictionary Comprehensions
โผ Generators & Iterators
โผ Decorators
๐ 7. Essential Libraries
โผ NumPy (Arrays & Computations)
โผ Pandas (Data Analysis)
โผ Matplotlib & Seaborn (Visualization)
๐ 8. Web Development & APIs
โผ Web Scraping (BeautifulSoup, Scrapy)
โผ API Integration (Requests)
โผ Flask & Django (Backend Development)
๐ 9. Automation & Scripting
โผ Automating Tasks with Python
โผ Working with Selenium & PyAutoGUI
๐ 10. Data Science & Machine Learning
โผ Data Cleaning & Preprocessing
โผ Scikit-Learn (ML Algorithms)
โผ TensorFlow & PyTorch (Deep Learning)
๐ 11. Projects
โผ Build Real-World Applications
โผ Showcase on GitHub
๐ 12. โ Apply for Jobs
โผ Strengthen Resume & Portfolio
โผ Prepare for Technical Interviews
Like for more โค๏ธ๐ช
โค3
Forwarded from Artificial Intelligence
๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐ณ๐ผ๐ฟ ๐๐ฟ๐ฒ๐ฒ ๐ผ๐ป ๐ฌ๐ผ๐๐ง๐๐ฏ๐ฒ โ ๐๐ผ๐บ๐ฝ๐น๐ฒ๐๐ฒ ๐ฃ๐น๐ฎ๐๐น๐ถ๐๐ ๐๐๐ถ๐ฑ๐ฒ๐
๐ฅ YouTube is the ultimate free classroomโand this is your Data Analytics syllabus in one post!๐จโ๐ป
From Python and SQL to Power BI, Machine Learning, and Data Science, these carefully curated playlists will take you from complete beginner to job-readyโจ๏ธ๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4jzVggc
Enjoy Learning โ ๏ธ
๐ฅ YouTube is the ultimate free classroomโand this is your Data Analytics syllabus in one post!๐จโ๐ป
From Python and SQL to Power BI, Machine Learning, and Data Science, these carefully curated playlists will take you from complete beginner to job-readyโจ๏ธ๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4jzVggc
Enjoy Learning โ ๏ธ
Forwarded from SQL Programming Resources
ETL vs ELT โ Explained Using Apple Juice analogy! ๐๐ง
We often hear about ETL and ELT in the data world โ but how do they actually apply in tools like Excel and Power BI?
Letโs break it down with a simple and relatable analogy ๐
โ ETL (Extract โ Transform โ Load)
๐ง First you make the juice, then you deliver it
โก๏ธ Apples โ Juice โ Truck
๐น In Power BI / Excel:
You clean and transform the data in Power Query
Then load the final data into your report or sheet
๐ก Thatโs ETL โ transformation happens before loading
โ ELT (Extract โ Load โ Transform)
๐ First you deliver the apples, and make juice later
โก๏ธ Apples โ Truck โ Juice
๐น In Power BI / Excel:
You load raw data into your model or sheet
Then transform it using DAX, formulas, or pivot tables
๐ก Thatโs ELT โ transformation happens after loading
We often hear about ETL and ELT in the data world โ but how do they actually apply in tools like Excel and Power BI?
Letโs break it down with a simple and relatable analogy ๐
โ ETL (Extract โ Transform โ Load)
๐ง First you make the juice, then you deliver it
โก๏ธ Apples โ Juice โ Truck
๐น In Power BI / Excel:
You clean and transform the data in Power Query
Then load the final data into your report or sheet
๐ก Thatโs ETL โ transformation happens before loading
โ ELT (Extract โ Load โ Transform)
๐ First you deliver the apples, and make juice later
โก๏ธ Apples โ Truck โ Juice
๐น In Power BI / Excel:
You load raw data into your model or sheet
Then transform it using DAX, formulas, or pivot tables
๐ก Thatโs ELT โ transformation happens after loading
โค3๐1๐1
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