Why Cloud Computing is Critical for a Data Scientist
👉 Download Our Free Data Science Career Guide:✅https://bit.ly/30Yxtlj
👉 Sign up for Our Complete Data Science Training:✅https://bit.ly/35unmWn
Why cloud computing is critical for data scientists? If small companies want to level the playing field, cloud computing is critical for their data science teams.
✅Get a SPECIAL OFFER for The 365 Data Science Program: https://bit.ly/35unmWn
To understand the advantages cloud computing provides when it comes to data science, let’s imagine a world with as much data as we have today, but without servers. In such an unfortunate scenario, firms would need databases that run locally, right?
So, every time when you, as a data scientist, want to engage in new analyses or refresh an existing algorithm, you’d have to transfer information to your machine from the central database, and then proceed to operate locally. This unfortunate world would have several main drawbacks...
For example, manual intervention would be necessary to retrieve data... Your machine becomes a single point of failure for the analyses you have worked on locally... Processing speed would be equivalent to the computing power of your computer... Chances are you will be able to work with a limited amount of data due to the limited computing resources at your disposal... Moreover, under this setup, you wouldn’t be able to leverage real-time data to build recommender systems or any type of machine learning algorithms that require ‘live’ data.
👇🏻Follow us on YouTube
✅https://www.youtube.com/c/365DataScience?sub_confirmation=1
Doesn’t sound like the perfect scenario, does it? Well, that’s why we invented servers. And then these servers had drawbacks of their own.
Fortunately, we now have clouds. They overshadow local servers in almost every conceivable aspect. And, in fact, data scientists should be focused on developing great algorithms, testing hypothesis, taking advantage of all available data without having to wait hours to see the results of the tests they are performing and certainly without having to worry how much memory space they have left on their computer. And yes, sometimes data scientists do end up waiting for long hours for an algorithm to train, but with a cloud, they have the option to pay more and get the job done faster. That’s yet another advantage of cloud computing over servers.
👇🏻Get a SPECIAL OFFER for the Data Science Training
✅https://bit.ly/35unmWn
👇🏻Connect with us on our social media platforms:
✅Website: http://bit.ly/33a4BWx
✅Telegram: https://t.me/c365datascience
✅LinkedIn: https://www.linkedin.com/company/365datascience
✅Medium: https://medium.com/@365datascience
✅Twitter: https://twitter.com/365datascience
✅Facebook: https://www.facebook.com/365datascience
✅Pinterest: https://www.pinterest.com/365datascience/
✅Reddit: https://www.reddit.com/user/365datascience
✅Tumblr: https://www.tumblr.com/blog/365datascienceblog
✅Instagram: https://www.instagram.com/365datascience
✅Q&A Hub: https://365datascience.com/qa-hub/
👇🏻Prepare yourself for a career in data science with our comprehensive program👇🏻
✅http://bit.ly/3378UlA
Get in touch about the training at:
support@365datascience.com
Comment, like, share, and subscribe! We will be happy to hear from you and will get back to you!
#CloudComputing #DataScientist #DataScience
Видео Why Cloud Computing is Critical for a Data Scientist канала 365 Data Science
👉 Sign up for Our Complete Data Science Training:✅https://bit.ly/35unmWn
Why cloud computing is critical for data scientists? If small companies want to level the playing field, cloud computing is critical for their data science teams.
✅Get a SPECIAL OFFER for The 365 Data Science Program: https://bit.ly/35unmWn
To understand the advantages cloud computing provides when it comes to data science, let’s imagine a world with as much data as we have today, but without servers. In such an unfortunate scenario, firms would need databases that run locally, right?
So, every time when you, as a data scientist, want to engage in new analyses or refresh an existing algorithm, you’d have to transfer information to your machine from the central database, and then proceed to operate locally. This unfortunate world would have several main drawbacks...
For example, manual intervention would be necessary to retrieve data... Your machine becomes a single point of failure for the analyses you have worked on locally... Processing speed would be equivalent to the computing power of your computer... Chances are you will be able to work with a limited amount of data due to the limited computing resources at your disposal... Moreover, under this setup, you wouldn’t be able to leverage real-time data to build recommender systems or any type of machine learning algorithms that require ‘live’ data.
👇🏻Follow us on YouTube
✅https://www.youtube.com/c/365DataScience?sub_confirmation=1
Doesn’t sound like the perfect scenario, does it? Well, that’s why we invented servers. And then these servers had drawbacks of their own.
Fortunately, we now have clouds. They overshadow local servers in almost every conceivable aspect. And, in fact, data scientists should be focused on developing great algorithms, testing hypothesis, taking advantage of all available data without having to wait hours to see the results of the tests they are performing and certainly without having to worry how much memory space they have left on their computer. And yes, sometimes data scientists do end up waiting for long hours for an algorithm to train, but with a cloud, they have the option to pay more and get the job done faster. That’s yet another advantage of cloud computing over servers.
👇🏻Get a SPECIAL OFFER for the Data Science Training
✅https://bit.ly/35unmWn
👇🏻Connect with us on our social media platforms:
✅Website: http://bit.ly/33a4BWx
✅Telegram: https://t.me/c365datascience
✅LinkedIn: https://www.linkedin.com/company/365datascience
✅Medium: https://medium.com/@365datascience
✅Twitter: https://twitter.com/365datascience
✅Facebook: https://www.facebook.com/365datascience
✅Pinterest: https://www.pinterest.com/365datascience/
✅Reddit: https://www.reddit.com/user/365datascience
✅Tumblr: https://www.tumblr.com/blog/365datascienceblog
✅Instagram: https://www.instagram.com/365datascience
✅Q&A Hub: https://365datascience.com/qa-hub/
👇🏻Prepare yourself for a career in data science with our comprehensive program👇🏻
✅http://bit.ly/3378UlA
Get in touch about the training at:
support@365datascience.com
Comment, like, share, and subscribe! We will be happy to hear from you and will get back to you!
#CloudComputing #DataScientist #DataScience
Видео Why Cloud Computing is Critical for a Data Scientist канала 365 Data Science
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Cloud Computing Tutorial for Beginners | Cloud Computing Explained | Cloud Computing | SimplilearnBest Data Science Degrees to Get HiredData Scientist vs Data Analyst | Which Is Right For You?AWS Vs Azure Vs GCP - Which cloud to pick for better career and pay?Data Engineering and Data Science: Bridging the Gap | DataEDGE 2016George Gilder: Forget Cloud Computing, Blockchain is the FutureWhich Technology to Learn? | Blockchain | MLHow to learn data science... the cloud way | future-proof & more employable!Use of Data Science and AI in the Banking SectorAWS vs Azure vs GCP | Amazon Web Services vs Microsoft Azure vs Google Cloud Platform | IntellipaatCloud Computing In 6 Minutes | What Is Cloud Computing? | Cloud Computing Explained | SimplilearnPython Jobs to Pursue in 2021Data Analyst vs Data Engineer vs Data ScientistReal-world application of the Central Limit Theorem (CLT)Top 10 Highest Paying Jobs For 2021 | Highest Paying IT Jobs in 2021 | Best IT Jobs 2021 | EdurekaBuilding a Modern Data Platform on AWSWhat is Cloud Computing?Top Benefits of Cloud ComputingBuild Your First Big Data Application on AWSAWS In 10 Minutes | AWS Tutorial For Beginners | AWS Training Video | AWS Tutorial | Simplilearn