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Why Data Engineering Is Better Than Data Science (Seriously, Fight Me)
🔥 Data science may be sexy… but data engineering is marriage material.
In this brutally honest breakdown, we’re settling the ultimate tech debate: Why being a Data Engineer isn’t just better—it’s cleaner, faster, and way less full of lies.' From robust pipelines to dodging Schrodinger’s spaghetti code, here are 6 reasons data engineers rule the data world! 💪
We'll discuss:
🎯 Why most companies aren’t ready for data science (and how data engineers save the day)
🎯 The chaos of data science notebooks vs. the beauty of CI/CD pipelines
🎯 How data engineers build the foundation for data scientists’ “guest” work
🎯 Why data engineering is just software engineering with bigger JSONs
🎯 The real-world demand for skilled data engineers (unicorns, anyone?)
Tech Topics Covered: Data pipelines, CI/CD, Terraform, Airflow, Kubernetes, DBT, Prometheus, Jupyter notebooks, XGBoost, and more!
🔔 Like, Subscribe, and Hit the Bell for more no-nonsense tech content! If you’re a data engineer tired of cleaning up data science messes or a data scientist who feels the burn, drop a comment and let us know your thoughts! 👇
💬 Which side are YOU on—data science or data engineering?
___________________________________
📚 Resources to Level Up Your Data Science Career
👉 Join our channel for no-BS data science advice : https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Playlist for data science projects: https://bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+data+engineers+vs+data+scientists
______________________________________________________________________
📅 Video Timeline:
0:00 –Intro: Data Science vs Data Engineering
0:14 – Reason #1: Why most companies shouldn’t do data science
0:48 – Reason #2: Schrodinger’s deliverables
1:16 – Reason #3: CI/CD vs Notebooks
2:00 – Reason #4: Who actually ships
2:24 – Reason #5: Bigger JSONs, bigger problems
2:57 – Reason #6: Job market reality
3:39 – Conclusion
______________________________________________________________________
About StrataScratch:
StrataScratch (https://platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+data+engineers+vs+data+scientists) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+data+engineers+vs+data+scientists. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from the StrataScratch team, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
📧 Contact Us: Got questions or feedback? Drop them in the comments or email us at team@stratascratch.com.
_____________________________________________________________________
#datascience #dataengineering #datascienceinterview #machinelearning #dataanalytics #sql #python #datasciencejobs #techcareers #interviewtips #codinginterview #memes #machinelearningengineer #careeradvice #datascientists #techinterviewprep #faang #trending #coding #interviewtips #interview #techhumor #ml #ai #pandas #jupyter #careerintech #datapipeline
Видео Why Data Engineering Is Better Than Data Science (Seriously, Fight Me) канала StrataScratch
In this brutally honest breakdown, we’re settling the ultimate tech debate: Why being a Data Engineer isn’t just better—it’s cleaner, faster, and way less full of lies.' From robust pipelines to dodging Schrodinger’s spaghetti code, here are 6 reasons data engineers rule the data world! 💪
We'll discuss:
🎯 Why most companies aren’t ready for data science (and how data engineers save the day)
🎯 The chaos of data science notebooks vs. the beauty of CI/CD pipelines
🎯 How data engineers build the foundation for data scientists’ “guest” work
🎯 Why data engineering is just software engineering with bigger JSONs
🎯 The real-world demand for skilled data engineers (unicorns, anyone?)
Tech Topics Covered: Data pipelines, CI/CD, Terraform, Airflow, Kubernetes, DBT, Prometheus, Jupyter notebooks, XGBoost, and more!
🔔 Like, Subscribe, and Hit the Bell for more no-nonsense tech content! If you’re a data engineer tired of cleaning up data science messes or a data scientist who feels the burn, drop a comment and let us know your thoughts! 👇
💬 Which side are YOU on—data science or data engineering?
___________________________________
📚 Resources to Level Up Your Data Science Career
👉 Join our channel for no-BS data science advice : https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Playlist for data science projects: https://bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+data+engineers+vs+data+scientists
______________________________________________________________________
📅 Video Timeline:
0:00 –Intro: Data Science vs Data Engineering
0:14 – Reason #1: Why most companies shouldn’t do data science
0:48 – Reason #2: Schrodinger’s deliverables
1:16 – Reason #3: CI/CD vs Notebooks
2:00 – Reason #4: Who actually ships
2:24 – Reason #5: Bigger JSONs, bigger problems
2:57 – Reason #6: Job market reality
3:39 – Conclusion
______________________________________________________________________
About StrataScratch:
StrataScratch (https://platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+data+engineers+vs+data+scientists) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/coding?code_type=2&page_size=100&utm_source=youtube&utm_medium=click&utm_campaign=YT+data+engineers+vs+data+scientists. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from the StrataScratch team, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
📧 Contact Us: Got questions or feedback? Drop them in the comments or email us at team@stratascratch.com.
_____________________________________________________________________
#datascience #dataengineering #datascienceinterview #machinelearning #dataanalytics #sql #python #datasciencejobs #techcareers #interviewtips #codinginterview #memes #machinelearningengineer #careeradvice #datascientists #techinterviewprep #faang #trending #coding #interviewtips #interview #techhumor #ml #ai #pandas #jupyter #careerintech #datapipeline
Видео Why Data Engineering Is Better Than Data Science (Seriously, Fight Me) канала StrataScratch
data science coding AI data analyst data scientist data engineering ai machine learning data engineer data data analytics engineer data engineer roadmap big data data engineering projects aws data engineer analytics big data engineer tech consulting python deep learning artificial intelligence data science roadmap business analyst data analysis
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13 августа 2025 г. 21:25:00
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