Uploaded May 2024 | Updated September 2026, 3 hours ago
In this video, we dive deep into the essential tools that empower data scientists to unlock the secrets of data.
Learn about:
◉ Databases: SQL vs NoSQL, Cloud Storage Options
◉ Coding Editors: Jupyter Notebooks, PyCharm, RStudio & More!
◉ Big Data Processing: Hadoop, Spark, Stream Processing Tools
◉ Data Visualization:Tableau, Power BI, Interactive Options
◉ Machine Learning Tools: TensorFlow, Kubeflow, MLOps
◉ Data & Model Version Control: Git, DVC
◉ DemeOps for Scalable ML
Whether you're a beginner or a pro, this video equips you to conquer the data science world!
Subscribe for more data science insights! Leave a comment with your questions below! Visit stratascratch.com for useful data science resources!
_____________________________________________________________________
👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+full+stack+ds+tools
______________________________________________________________________
Timeline:
Intro: (0:00)
Databases: (0:19)
Coding Editor: (1:39)
Big Data Processing: (2:55)
Data Visualization: (4:01)
Machine Learning OPS: (5:01)
Version Control: (6:51)
Conclusion: (7:44)
______________________________________________________________________
About The StrataScratch Platform:
StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+full+stack+ds+tools) 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 platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+full+stack+ds+tools. 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:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email us at team@stratascratch.com
______________________________________________________________________
#datascience #tools #machinelearning #bigdata #datavisualization #datascienceskills #datascientist
In this video, we dive deep into the essential tools that empower data scientists to unlock the secrets of data.
Learn about:
◉ Databases: SQL vs NoSQL, Cloud Storage Options
◉ Coding Editors: Jupyter Notebooks, PyCharm, RStudio & More!
◉ Big Data Processing: Hadoop, Spark, Stream Processing Tools
◉ Data Visualization:Tableau, Power BI, Interactive Options
◉ Machine Learning Tools: TensorFlow, Kubeflow, MLOps
◉ Data & Model Version Control: Git, DVC
◉ DemeOps for Scalable ML
Whether you're a beginner or a pro, this video equips you to conquer the data science world!
Subscribe for more data science insights! Leave a comment with your questions below! Visit stratascratch.com for useful data science resources!
_____________________________________________________________________
👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+full+stack+ds+tools
______________________________________________________________________
Timeline:
Intro: (0:00)
Databases: (0:19)
Coding Editor: (1:39)
Big Data Processing: (2:55)
Data Visualization: (4:01)
Machine Learning OPS: (5:01)
Version Control: (6:51)
Conclusion: (7:44)
______________________________________________________________________
About The StrataScratch Platform:
StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+full+stack+ds+tools) 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 platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+full+stack+ds+tools. 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:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email us at team@stratascratch.com
______________________________________________________________________
#datascience #tools #machinelearning #bigdata #datavisualization #datascienceskills #datascientist
![Most Common Data Science SQL Interview Question from DoorDash [window functions & partitions]
This is the most common data science SQL interview question from DoorDash, a food delivery company. This question tests your ability to split your data into percentiles using window functions. I’ll walk you through solving the question like we’re in an interview and give you some tips on how to approach the solution.
Go to the question through the link below and follow along with me.
Link to the question: https://platform.stratascratch.com/coding/2036-lowest-revenue-generated-restaurants?python=&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
👉 Subscribe to my channel: 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
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
Timeline:
Intro: (0:00)
Interview Question: (0:35)
Framework to solve the problem: (1:40)
Understand your data: (3:58)
Formulate your approach: (6:40)
Code Execution: (8:55)
Code Optimization: (14:35)
Conclusion: (17:08)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), 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?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
#DataScience #SQLInterviewQuestion Most Common Data Science SQL Interview Question from DoorDash [window functions & partitions]](https://i.ytimg.com/vi/T1UhSuKqy3A/mqdefault.jpg)









